knowledge integration in action 2017 summer...service framework for co-creation solutions &...

KnowledgeIntegrationin Action

Toward Digital Transformation

Service Framework for Co-creation

Solutions & Technologies

Embarking on the "Digital Journey"Part 1

Gathering of Information→ Idea Creation → Lean Startup withthe OODA Loop as its backbone.

Part 2

Seven key technologies, including the cloud,AI, and the IoT, among others.

Part 3

2017 Summer

Reality of Digital Journeyand 6 items to address before embarking ona Digital Journey and formulatingDigital Bisiness Archtecture(DBA).

01 Toward Digital Transformation 02 ［Prologue］ Now Departing for the Digital Journey

05 ［Historical Context］ Exponential Technology Evolution: Emerging Countries' Talents Driving the Disruption

08 ［Preparing for the Journey］ Improving Procurement capability of Digital Business Architecture: Initial Preparations for the Journey

11 ［Interview］ Transforming for the Journey: Using Mutually-invested Fulltime Human Resources to Build an Organization of 1200 People in 3 Years

15 Service Framework for Co-creation 16 ［Overview］ Compass for the Digital Journey The "Service Framework for Co-creation"

19 ［Gathering of Information］ Understanding Latest Practices and Technological Trends Through Analysis, Surveys, and Talking to Practitioners

24 ［Idea Creation］ Idea-a-thon Implementation Drawing Attention as an Idea Creation Method

29 ［Lean Startup］ Real Software Technology for a Rapid Evolution of Services

34 ［Places of Co-creation］ "Co-creation Places" Seen in PLY & HAB-YU Honest Discussion, Devising Innovative Ideas

37 ［Column］ Sample Case of the Service Framework for Co-creation and Measures for Making PoC Successful

41 Solutions & Technologies 42 ［Overview］ Gearing Up for the Digital Journey: Developing a Broad and Deep Understanding of Technologies

45 ［Cloud Infrastructure］ Foundations for Digital Business The Next Generation of FUJITSU Cloud Service K5

50 ［Analytics］ The Road to Data-driven Management The Increasing Significance of Analytics

53 ［AI］ Core Technologies of Digitization, AI Understanding the Whole Picture

59 ［IoT］ From Sensors to IoT Platforms, Fujitsu's IoT Endeavors

64 ［AR/VR/MR］ Significance & Impact of AR/VR/MR as Powerful Tools to Enhance the Customer Experience

67 ［Security］ Risk-based Cybersecurity Measures Developing Technology for Mission Assurance and Business Continuity

72 ［API Management］ Launchpad for Digital Business Understanding API Management

C O N T E N T S


Embarking on the "Digital Journey"

2017 Summer

PART 1

PART 2

PART 3

PART 1


Let us look at how to fundamentally reworkand adapt management, organizations, business, products, and services for digitalization.

This sort of digital transformation cannot be tackled in a single day.Rather, it takes persistent and dedicated effort.

In other words, companies today must pursue a long "Digital Journey" that is fraught with challenges.Here in Part 1 we will examine the environment and preparations for that journey.

C O N T E N T S

1-1 ［Prologue］Now Departing for the Digital Journey

1-2［Historical Context］Exponential Technology Evolution: Emerging Countries' Talents Driving the Disruption

1-3［Preparing for the Journey］Improving Procurement capability of Digital Business Architecture: Initial Preparations for the Journey

1-4［Interview］Transforming for the Journey: Using Mutually-invested Fulltime Human Resources to Build an Organization of 1200 People in 3 Years

02

11

08

05

1 │ Knowledge Integration in Action │

PART 1-1

Toward Digital Transformation P ro l o g ue

Fig.1: Top 5 from Japan Management Association's compiled list of "Business Challenges of Japanese Enterprises 2016." There were 20 items in total with items (choices) such as "Utilizing IT and Strategic IT Investment" and "Penetration & Review of Corporate Mission/Vision/Values" remaining at below 15th in 2016.

Current Business Challenges (previous survey in 2014) （n=294）

1st Strengthen Human Resources (Recruiting/Training/Diversifying) 38.4

2nd Improve Profitability 35.6

3rd Improve Sales & Market Share (incl. Strengthening Sales Force) 34.7

4th Development of New Products/Services/Businesses 28.2

5th Globalization (Global Management) 23.1

Current Business Challenges (recent survey in 2016) （n=211） Variance

1st Improve Profitability 44.5 8.9

2nd Strengthen Human Resources (Recruiting/Training/Diversifying) 39.3 0.9

3rd Improve Sales & Market Share (incl. Strengthening Sales Force) 33.6 -1.1

4th Development of New Products/Services/Businesses 32.7 4.5

5thStrengthening & Restructuring Business Base(M&A/Alliances/Selecting & Concentrating Existing Businesses)

20.9 0.9

Now Departing for the Digital Journey

AI , IoT, and other digital technologies have had an unprecedented, disruptive influence on existing industries. Companies that do not meet the digital transformation challenge head-on will not survive. Though the reality of the current digital landscape should be self-evident, there seem to be more than a few individuals and enterprises who still eye it with skepticism.

Does Management Lack Interest in Digital Technology?

An example can be found in a survey conducted by the Japan Management Association that identified the top business challenges of Japanese enterprises for 2016. While improving profitability, strengthening human resources, including diversity, increasing sales and market share (Fig. 1) landed in the top five, Utilizing IT and Strategic IT Investment only came in at number 17.

Let's consider another perspective. Nearly 20 years ago,

there was a boom in EC (e-commerce), and retailers with brick and mortar stores were forced to downsize. Despite this long-established trend, major retail stores (supermarkets, department stores, fashion outlets, bookstores, and electronics stores) continue to have a presence in today’s market. Even in today's harsh economic environment, looking at listed enterprises, there are more than a few companies making reasonable strides.

The digitization of money has also not advanced greatly. According to a public opinion survey on the financial habits of households (2016), the use of electronic money for payment was 13.9% when under ¥1000, 11.4% for ¥1000-5000, and in the single digits for amounts higher than that. Cash and credit cards are still overwhelmingly the preferred form of payment. Looking at it this way, there is a certain persuasive power to phrases like "the digital transformation is exaggerated" and the view that "it's just a line used by IT vendors to boost sales."

Jun Taguchi　General Manager of IT Leaders Editorial Department(Impress Corporation)

Tatsuhiko Shibasaki　SVP, Head of Digital Transformation Business Unit


PART 1-1

Toward Digital TransformationP ro l o g ue P r o l o g ue

Huge chains Tower Records, Block-buster, and Border's Group have already disappeared from the U.S. For the everyday yellow cabs synonymous with taxi services, dispatching services and automated driving technology rapidly approaches.

The Storm of "Disruption" Starting in the U.S. in the 2000s

An IT watcher currently located in Silicon Valley, the U.S., Mr. Masaki Yamaya (Just Skill, Inc.), has said that

“since the 2000s in the U.S. there are cases, one after another, of large companies being ‘destroyed’.”

Take for example, the famous U.S. record/CD store chain Tower Records (corporate name: MTS Inc.) that for several decades was remarkably prosperous. Consider, as well, Blockbuster, once the largest video rental chain in the U.S., and Borders Group, once the second largest bookseller chain in the U.S. All three once formidable enterprises went bankrupt-in 2006, 2010, and 2011, respectively. And the number-one bookseller in the U.S., Barnes & Noble, has been forced to reduce its presence considerably. Although there are other underlying causes, "there is no doubt that digital companies and services like Apple's iTunes, the online streaming service Netflix, and Amazon.com had an impact," according to Mr. Masaki Yamaya.

Prominent IT analyst R "Ray" Wang, Chairman of the U.S. -based Constellation Research, has pointed out the threat of digital technology in stating that "the iPhone has disrupted 27 businesses, including music, PCs, software, digital cameras, car navigation systems, and so on. Organizations, jobs, and people will no longer be returning to these industries."

The landscape continues to evolve, and the rate at which it does is accelerating.The most obvious examples are probably the widely-known yellow cabs of the taxi industry being pushed out by vehicle dispatching services like Uber and Lyft, and the challenge to the hotel industry posed by Airbnb. In addition, AI has come to have an elevated presence in law and accounting firms, leading to a reduction in the recruitment of new staff. Even in the world of stocks and commodities, computer programs are replacing human traders.

Change is Necessary to Avoid Destruction

The finance industry has been assaulted by waves of FinTech. The manufacturing industry is now facing the realities of the Industrial Internet and 3D printing. The IoT and drone technology have a growing importance in agriculture. And even in education will soon be impacted by a disruptive movement of some kind. This is also true for the automotive and related industries as rapid developments are made in automated driving technology. It can be said that "there are virtually no industries or companies that will go unaffected by the disruptive changes brought on by digitization."

In Japan as of August 2016, AI discovered a treatment that had gone unnoticed by human doctors . This "incident" that occurred saved patients. IDOM (formerly Gulliver), the largest buyer and seller of used cars, started car sharing services that could destroy its core business, and services such as airCloset and Mechakari that allow for the borrowing of as many clothes as you like at a fixed price have also been seeing an increase in users. Waves of disruptive transformation are steadily coming in like a tide.

This being the case, it seems it cannot be said that "the digital transformation is exaggerated" and "it's too early for us to incorporate this into our business." Not only have technologies such as IoT, 3D printers, the fusion of robots and AI, etc. now emerged, but there is no doubt


PART 1-1

Toward Digital Transformation P ro l o g ue

Fig.2: The Pathway of the Digital Journey (an example)

Transformationof Operation・ Business review & Reform・ Supply chain optimization・ Customer engagement

InternalResistance

Lack ofIdeas

Changes inEconomic

Environment

Threat ofCyber

Security

Competitor'sStrategies

Weakness ofTechnical

capabilities

Creation of New Products/Services/Businesses・ Add innovative features to products・ Convert from product sales to providing services・ Data-driven decision making

Increase EarningOpportunities・ Ecosystem formation・ Platform creation・ Business & industry transformation

Autonomization/Automation・ Removal of human limitations・ Varying levels of products & services・ Non-existent products & services

that other new technologies will shortly be coming into existence.

Embarking on a Digital Journey

So what is to be done? The answer is that there is no choice but to switch from the side being disrupted and being destroyed to the side doing the disrupting. That is to say it is time for business innovation, and for that we have the "Digital Transformation (DX)." DX means taking the necessary steps to change the corporate organization and culture to respond to the digital age, allowing for existing businesses to be reformed, new services to be created, and for data-driven rapid

decision making. Since IT is at the root of this, CIOs and information system departments will be responsible for taking the lead in DX.

These efforts to change are referred to as the "Digital Journey." Unlike a trip or travel, a journey has the nuance of being a long road where it takes time for one situation to transition into another. The digital journey is a path of trial-and-error to arrive at DX, and there will be unexpected events and challenges along the way (Fig. 2). This book is intended to act as a guide for companies and people interested in embarking on just such a journey.


Toward Digital Transformation H i s t o r i c a l C o n t e x t

PART 1-2

Batch Processing Systems

Transaction Systems

Enterprise Systems (SoR*)

Systems of Engagement (SoE)

Digitally-based Systems

Era 1960s 1980s 1990s+ 2005+ 2015+

Core Technology Transistors LSI Networks, Internet Cloud, Mobile IoT, AI

Software Assembly High-level Language Commercial Packages Open-source Software API Economy

Development Craftsmen Waterfall Waterfall Agile CI/CD

Data Size Kilobyte (103) Gigabyte (109) Terabyte (1012) Exabyte (1018) Zettabyte (1021)

Data Format File Network DB Relational DB NoSQL Data Lake, Block Chain

Principal UsersGovernment agencies, some large companies

+ Big enterprises + Normal companies+ Venture companies, individuals, high-end electronics

Everyone

Application Examples

Complex calculations, aggregates

Online processing, MRP

ERP, CRM, Web Smartphone apps, analytics Automation / Autonomization

Table 1: The journey from computers to ICT and then digitalization. The speed of evolution is accelerating.*Systems of Record

In Part 1-1, we saw a part of the influence and threat posed by digital business. However, even with a firm grasp of the situation, there are also some opinions such as the following.

"There certainly are companies and industries that are

dramatically affected by the advance of technology.

However, that is not new, and ups and downs have

been occurring for a long time. For example, the rise of

infrastructure such as highways, railways, aircraft, etc.

changed the way people move, and as a result, related

industries and companies were affected. There are

many similar examples in terms of industrial products,

new kinds of fibers, medical technology, and so on. Why

should the influence of digital technology be viewed

with such great importance?"

Let's consider that question here afresh from a technological perspective.

Technology Evolves Exponentially

Take a look at Table 1. Since the creation of ENIAC, the first digital computer, in 1946, computer technology has

been on a steady march forward. Still, during the 20th century, computers were owned by government agencies and corporate enterprises for about 60 years. This was due to the high costs of installation and operation.

In the 21st century, this has changed completely. Cloud computing appeared around the same time as smartphones in the mid-2000s. These things together made it so that venture businesses and individuals were able to use high-performance (i.e., expensive) computer resources without even really being conscious of doing so. For instance, we can now instantly search millions and tens of millions of documents to retrieve the documents we need or perform a complex analysis of billions of points of diverse data.

Over the next decade, 3D printing and drone technology spread, and the penetration rate of smartphones exceeded 70% in developed countries. The IoT and AI also arrived on the scene. Combining them with the cloud and big data brought us to a place where we had "enabled the impossible." In fact, there is no shortage of topics such as sharing economies, the maker movement, and FinTech. Within this environment, AI has been


Exponential Technology Evolution:Emerging Countries' Talents Driving

the Disruption


Toward Digital Transformation H i s t o r i c a l C o n t e x tH i s t o r i c a l C o n t e x t

PART 1-2

Fig. 1: The prices of processors, storage, and networking, which are the foundation of ICT, continue to fall rapidly (note the even scale on the vertical axis). The data source is from "Internet Trends 2014" published by Kleiner Perkins Caufield Byers in May of that year.

＄1,000.00

＄100.00

＄10.00

＄1.00

＄0.10

＄0.011990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014

＄527 ＄569

＄1,245

＄16

＄0.05

＄0.02

Cost per Gbps

Cost per Gigabyte

Cost per 1mil Transistors

ProcessorsStorageNetworking

a disruptive innovation. Throughout these various backdrops, there has been a driving force of nonlinear technological advancement referred to as "exponential technologies."

The "Grain of Rice" anecdote provides a good example of how these technologies progress. The story goes that an adviser to Hideyoshi Toyotomi was to receive a reward for his efforts and when asked what he wished for, he replied "Give me a grain of rice today. Tomorrow, double it to two, and may I humbly receive double the grains every day for a month." This meant that while by the 6th day he received only 32 grains, on the 8th day only 128, and on the 11th day only a meager 1,024, on the 21st day, he received 1,048,676 grains; for the 31st day he was to receive over a billion. Hideyoshi apologized saying "I have made an error. Forgive me this debt."

“Since 2000, the mode has changed.”

The same principle applies to digital technology in the form of Moore's law, which states that "the number of transistors in a dense integrated circuit doubles every 18 to 24 months" (Figure 1). Advancements that once fell within the realm of what we expected have recently reached levels that exceed our imagination. Were we to compare today to the "Grain of Rice" story, we might be at around the 35th day.

Hironao Kubo (Senior at Nakashima Propeller Co. Ltd.), who independently studies this phenomenon, says the following. "With each year technology such as machinery, electronics, and construction become cheaper and performance improves. However, since the speed of advancement is linear, what will happen next can be predicted. If you put forth the effort, you can stay caught up. ICT was this way before, but since 2000, the mode has changed. Advancements have progressed at an exponential and explosive speed. It is not possible to imagine what the future will be like, and ordinary efforts are insufficient to catch up."

As is widely known, the performance of today's smartphones surpasses the CRAY-1 supercomputer of 20 years ago that cost tens of millions of dollars. In that short period of time our current smartphones have come to be several centimeters in size, and have a price that is becoming cheap enough to ignore. This is one exponential technology.

However, many believe that Moore's law is not indefinite, and that its limits are drawing near. Semiconductors have been miniaturized down to 14nm (nanometers), and the world of molecules (several nm) and atoms (0.1nm) is just around the corner. The next level of miniaturization (performance improvement) is said to be a major hurdle



PART 1-2

H i s t o r i c a l C o n t e x t

in terms of manufacturing technology and electric power management. Even so, technology such as the improvement and parallelization of architectures and the practical application of quantum computers is also drawing near.

Human Resources in Emerging Countries Drive Digitalization

In addition, exponential technology is not limited to semiconductors. Participants engaged in digital business are also increasing. In 2015, the number of internet users worldwide exceeded three billion, and by 2019, it is expected to exceed four billion. Still, the populations of developed countries such as Europe, America, Japan, and Singapore are around 1.25 billion. The number of internet users in developing countries and emerging economies such as China and India will be much larger.

Here the prevalence of semi-genius/genius individuals among the population is a figure of 0.25%. If the number of internet users in developing countries and emerging economies is around two billion people, then two billion × 0.0025 = five million human resources with exceptional minds that can overcome language barriers and access various content through a multitude of sources such as

MOOC (Massive Open Online Course). Naturally, those with a hungry spirit will also help to vigorously drive innovation as human resources.

There is one other enormous investment. Table 2 shows the policies of governments in focusing on AI. The extensive budgets and researchers involved with the BRAIN Initiative in the United States and the Human Brain Project in Europe, among others, is easy to see. On the other hand, in the U.S. private companies are more motivated to invest in R&D than the government is. According to CB Insights in the U.S., in 2016 more than 550 companies raised a total of US $5 billion for AI ventures.

Major investment in ICT is even more substantial. According to Bloomberg, numbers for R&D investment in 2016 were led by Amazon.com at US $14.2 billion, Alphabet (Google) at US $13.5 billion, Microsoft at US $12 billion, and Apple at US $9.7 billion, exceeding one trillion Japanese yen. Everything within these budgets is not necessarily tied to the field of AI, and their results will not necessarily be connected either. Even so, it is wise to understand that the synergistic effect between human resources and investment will bring about technological breakthroughs that have yet to be seen.

USA BRAIN InitiativeLaunched by the Obama administration, this brain science project will span the 12 years from 2013 to 2025. In addition to DARPA, the FDA, ARPA, NIH, NSF, and DOE participate. The total budget is estimated to be over US $4.5 billion.

Europe Human Brain Project

Working to identify the mechanisms of the brain from the view of researching the brain as a living body and using computer simulations to understand brain functions. Started in 2013 with a 10-year plan and a total budget of €1.2 billion. There are 12 subprojects such as using neuromorphic computing to use IT to imitate brain nerves.

China -

As a national policy, the intent is to become a top level science and technology nation in the world by 2020. In relation to AI, the Brain Research Instrument Innovation Center (BRIIC) was established under the umbrella of the Chinese Academy of Sciences in 2015, along with a mind and intelligence research center, etc. Research themes being tackled include brain information processing, brain network modeling, etc.

UK -The Department for Business, Innovation and Skills established the Centre for Cognitive Computing Research (GB £113 million) and The Alan Turing Institute (GB £42 million). The latter is notable for collaborating with the prominent universities of Cambridge, Edinburgh, and Oxford, among others.

Table 2: Programs related to AI in each country. In the U.S., other projects include "SyNAPSE" and "Big Mechanism," and in Europe there is "SpinNNaker."


Toward Digital Transformation P r e p a r i n g f o r t h e J o u r n e y

PART 1-3

Fig.1: Actual circumstances of digital transformation according to IDC USA; survey conducted in March 2015, involving the heads of business divisions for 317 major companies worldwide

0

5

10

15

20

25

30

35

Digital Resister Digital Explorer Digital Player Digital Transformer Digital Disruptor

14

32 33

14

8

IDC.2015; n= 317 IT and LOB Executives, March, 2015

● Digital Resister: Has done almost nothing apart from using digital technology in response to external threats● Digital Explorer: Provides fragmentary or ad hoc digital goods and services, but has no fixed plan of action● Digital Player: Provides products and services using digital technology at the enterprise level; however,

cannot be said to have made disruptive changes● Digital Transformer: Business and IT are highly integrated, and management is committed to digital goods

and services● Digital Disruptor: Has created something new using its own strengths, establishing a competitive advantage

How many companies have embarked on a digital journey (a journey to become a digital enterprise)? Figure 1 shows the results of a survey conducted by IDC USA in March 2015 investigating the process of digitalization for 317 major enterprises.

What accounts for a large portion of the companies are "Digital Explorers" that provided fragmentary or ad hoc digital goods and services without a fixed course of action, and "Digital Players" that provide digital goods and services at the enterprise level but cannot be said to be causing any kind of disruptive change. Even though they are only about halfway there, 65% have stepped out on their journey.

In contrast, the percentage of "Digital Resisters" is surprisingly low at 14%. Since it has been two years since this survey was taken, it seems very likely that this situation has progressed even further. In fact,

though there is not enough space here to go into too great of detail, a similar survey conducted by IDC Japan in January 2017 of 533 Japanese companies with over 1,000 employees revealed how this situation had been progressing.

What 6 Things Does IDC Say You Need to "prepare for the journey"?

However, simply setting out on the digital journey is not advisable. Aside from cases of exceptional luck, there are doubtless to be many difficulties faced in adjusting to any degree of change. Therefore, some preliminary preparations are needed. Robert Parker (group vice president) of IDC USA who headed the survey from Figure 1 has also pointed this out. "To all CIOs who must embark on a digital journey, there are six things I would like to recommend."


Improving Procurement capability of Digital Business Architecture:

Initial Preparations for the Journey


Toward Digital Transformation P r e p a r i n g f o r t h e J o u r n e yP r e p a r i n g f o r t h e J o u r n e y

PART 1-3

Fig.3: Elements of the Gartner-advocated "Digital Business Architecture (DBA)"

Fig.2: 6 items to address before embarking on the digital journey

Vision & Strategy

GoalsStrategic ActionBusiness ResultsOpportunities &

Threats

Component BlocksProcess

TechnologyApps/Applications

Information

TouchpointsIntegration

SecurityGovernance

Analytics

InfrastructureDelivery

NetworkingOperations

Scale, Speed, Recovery

CapabilityBusiness Model

DesignMarkets & Products

Economy

1. Build a scalable IT infrastructure

2. Prepare the capability for integration of micro-services

3. Provide resources to support insight

4. Establish a consistent interface and agile procedures

5. Anchor procurement capability as a core competency

6. Regulate security policies of the digital economy

These six things are shown in Figure 2. From creating scalable IT infrastructure to regulating security policies, each of these seems fairly natural and agreeable. Of these, "anchor procurement capability as a core competency" may require some explanation. Parker has said that companies need to build relationships with a number of vendors, including venture companies, and that relationship should be a partnership where prospective fates are shared. This being the case, procurement capability = having the knowledge to accurately evaluate the ability, technical strength, and performance of vendors; being able to do this needs to be made a core ability. The six things, including this point, urge changes in IT departments.

Gartner, Inc. Advocates Digital Business Architecture (DBA)

Even once these six items are in place, a company is still not completely ready. In the digital journey, it is said that rapid small failures are the quick route to success (i.e., Fail Fast). However, without some postulation or guidelines, whether or not something has been a failure cannot be judged, and where to return to in the event of failure will not be known.

Marcus Blosch , a VP of Research at Gar tner, recommends the formulation of "Digital Business Architecture (DBA)." Blosch has equated advancing

an enterprise without creating DBA to constructing buildings without urban planning: efficiency is poor, and worse, you can end up with a slum.

He states that DBA consists of five elements: ① Vision and Strategy, ② Capability, ③ Touchpoints, ④ Component Blocks, and ⑤ Infrastructure (Fig. 3). For instance, vision and strategy are A) goals for a company's business objectives, B) strategic action to reach those goals, C) desired business results, and D) the opportunities and threats involved (a company's strengths and weaknesses). These need to be realized, as well as visualized, according to the circumstances of each company.



PART 1-3

P r e p a r i n g f o r t h e J o u r n e y

This may seem abstract and difficult to understand, but if thought of as an expansion of the four layers from Enterprise Architecture (EA)-business, data, application, technology-that dominated the business world in the 2000s, DBA may be easier to imagine. As Blosch has said, the depth of the content descriptions varies by company, but companies like General Electric, DHL, Goldman Sachs, Acme Bank of New York, etc. have formulated and are also expanding upon DBA.

Necessity of Developing a Technology Platform

Blosch has also provided us a diagram of the technology layer (Fig. 4). Of the five elements of DBA, focusing on ④ Component Blocks and ⑤ Infrastructure apportion four Platforms (system groups) to be engaged in each target area. There is (1) the Information Systems Platform which comes from existing system groups like the back office, etc.; (2) the Customer Experience Platform made up of the websites and SNS directed at customers; (3) the IoT Platform for physical assets and goods; and (4) the Ecosystems Platform that connects to outside companies and marketplaces through API sharing.

As a common element among all the Platforms, a carefully positioned (5) Data and Analytics Platform is necessary at the center. Setting aside physical implementation, logically, it is clear that data and information must be unified. This point is undoubtedly connected to what Parker of IDC points to in "③ Provide resources to support insight." Review of existing systems (SoR) is essential.

Fig.4: Gartner's "The Digital Business Technology Platform"

Partners

Customer Employees

Things

Ecosystems Platform

IoT Platform

Data and AnalyticsPlatform

CustomerExperience Platform

InformationSystems Platform


Toward Digital Transformation I n t e r v i e w

PART 1-4

The path companies take on their digital journeys is by no means an uneventful one, and Fujitsu has been deeply involved with user enterprises in the field of enterprise systems, So what actions are we taking?

We sat down and spoke with Mr. Kazuo Miyata, EVP, Head of Digital Transformation Business Group, and Mr. Kazuo Imada, SVP, Vice Head of Digital Transformation Business Group to f ind out . ( Interviewer : Junji Kawakami, Head Editor for IT Leaders)

Changing Values and Personnel Moving from SoR to SoE

─ The exponential evolution of technology has shown the importance of transforming to join the digital age. How do you see the current situation for Japanese companies?Miyata : Led by the U.S., disruptive innovations are occurring one after another globally. Despite that, there seems to be little sense here of crisis or tension over what is going on. I think that puts Japan in a dangerous spot. Aside from a few major companies, if things continue this way, many Japanese companies will literally

be wiped out. As one university professor familiar with this area has pointed out, "Top management in Japan has not discovered the value of ICT,” and a low level of sensitivity to the technology of Japanese management teams seems to be a primary culprit.

Essentially, there is a lack of leaders with strong awareness and sense of responsibility when it comes to putting a digital transformation into action. Since Japanese companies tend to favor generalists, it can be said that there really isn't an environment that is set with a career path - even for CIOs - where a person will emerge ahead of the pack as a "pro in that area." I think that 70% of IT human resources in Japan being on the IT vendor side of things has also had a notable influence.

─ Up to now, Fujitsu has been deeply involved with corporate information systems. What do you think about your involvement?Miyata: Naturally, the reality of this low sensitivity and receptivity to ICT cannot be solely attributed to the side of user companies. We make and deliver the system our users ask for. You only catch the balls you're thrown. As a result of going along with that sort of arrangement, we haven’t been looking ahead to accumulate the talent, skills, and know-how necessary to win the game by looking ahead to what's coming. We on the Fujitsu side have much to reflect on.

Now that global competition is intensifying, powerful user companies are looking to create new modalities of competition through working with influential partners. That might be Google, some foreign consultant, or maybe

Transforming for the Journey:Using Mutually Invested Fulltime Human Resources to

Build an Organization of 1200 People in 3 Years

Mr. Kazuo Miyata, EVP, Head of Digital Transformation Business Group

photo by koji Matono


Toward Digital Transformation I n t e r v i e wI n t e r v i e w

PART 1-4

Mr. Kazuo Imada,SVP, Vice Head of Digital Transformation Business Group

a startup that's bringing something new to the table. To be honest, there's a sense of crisis that was left behind with the Fujitsu of the past.

Looking at the realities we face, there are some changes we need to make first. We need to reflect on the things we should and put all our energy into moving forward. If we think that way, we can recover what we've lost. First, we need to add the capability to support our customers, and then we can demonstrate to the world what we can do through achievements. So the thinking right now is to strengthen both our organization and to improve our solutions.

─ So that means pivoting the business to be in line with the arrival of the digital age?Miyata: Up to now, in the field of core systems, we've focused on what is now known as SoR. From our deep engagement with enterprises, I am confident that we have made systems together that we can be proud of.

Of course, SoR continues to be important. That hasn't changed, but from here, while we remain actively involved with our customers and provide a wealth of experience, a major theme is the concept and practical ability of SoE to build mutually beneficial relationships. There is also this area of many companies about to take their first steps on a digital journey.

To say we are "becoming professional guides" is a bit presumptuous, and we recognize that there are many unexplored areas even for our company. In blazing a new trail there is no easy approach; our only choice is to start walking and gain further experience. And with experience, even in trying situations, you know how to reach out and grab hold and find your footing; you're equipped with an underlying strength. That is our fundamental thinking.

So what mindset, skills, and know-how is necessary to

open the way for our clients? We concluded that it was essential that along with careful and thorough analysis, we needed well-equipped human resources in a structure and organization that could move flexibly. With that in mind the Digital Front Business Group was officially launched this January.

Fostering Digital Innovators who can Talk Business from the Technology Side

─ Could you please explain the role of the Digital Front Business Group?Miyata: Digital change is foremost a journey, so no one can see a clear path at the beginning. In light of that, over the past few years our customers and our company have pursued initiatives to explore the possibilities of utilizing new technologies in the form of PoC. The Digital Front Business Group is the next step, as we approach from the perspective of "What role will this technology play in business?"

Making these things happen begins with human resources . Last year we announced a "Service Framework for Co-creation", but to achieve that result, the human resources that think and discuss today's technology and the technology that is coming out, that consider the next business venture together with customers, and that put it all together, are indispensable.

─ These are the human resources that Fujitsu calls "Digital Innovators," correct? Is there a lack of such people at present?



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I n t e r v i e w

Imada: Although information about them hasn't been properly conveyed to the world at large, our company participates in communities and consortiums related to ICT, and there are a number of engineers highly praised from outside the company. Although not necessarily project managers active in the field of SoR up to now, they have a keen and extraordinary insight into the possibilities of technology.

However, in-house evaluation of these personnel was not necessarily high. Moving forward, we want these people to be seen as "model personnel" and shine a spotlight on them. They will be evaluated as individuals by the customers, and nurtured as engineers who can be counted on. By moving out front with confidence and pride, we believe it will be possible for Fujitsu will be an active organization in providing support.

Fostering 200 Human Resources in 1 Year as an Upfront Investment

─ Specifically, what sort of initiatives are you interested in?Miyata: Human resource development doesn't happen overnight. Organizational structure and evaluation criteria, work style, providing a place to learn and educational content... There are a great many things that must be addressed. Since there is no single, correct answer, we have to proceed using trial and error. The real charm of making the digital journey together with customers is in how it rewards those involved and produces the motivation for the next challenge. Looking at it from this side, the number of people who aim to take on a role and responsibilities grows. To create this kind of virtuous circle, requires long and careful thinking.

We have established Digital Front Business Group to be positioned as a part of such efforts. First, each quarter 40 to 50 engineers were selected from within the entire company, bringing together 200 people within a year. The present approach is that through intensive training, three types of human resources are developed. "Developers" dig into technology, "designers" come up with ideas for businesses, and "producers" lead in co-creation with

customers. Of course, they are separated from the work onsite, so we need to change the evaluation system to something more appropriate for the digital age.

We are working actively with idea-a-thons and hack-a-thons as places to cultivate collaborative human resources. In 2015, over 1,500 people attended, and those with the experience needed to be effective are steadily increasing. Know-how is also being garnered. Using this as a foothold, the Digital Front Business Group aims to nurture 1,200 capable human resources over the next three years.

Utilizing Cloud Services to Fill the Gaps between Technology and Business

─ In order to improve Japanese companies' digital business, in addition to human resources, the means for giving shape to ideas is also important.Imada: As indicated, it is important for the service to be given shape and implemented as it cannot be verified if it isn't actually moving yet. In that respect, we pursue lean and agile development that makes use of cloud services. Since this is very different from how we have developed services up to this point, this will be a challenge for us, but fortunately, we have a cloud environment with various middleware and APIs running that allow us to operate at a rapid pace. We have an environment prepared where even without creating things anew, we can combine elements to implement a new service.

In addition, as a result of working with open source software for nearly twenty years, we have software engineers who specialize in the tools and container technologies for putting DevOps into practice. They can make use of the know-how, even in digital business, of their experience in the same agile development they worked with in big data and analytics, as well as in the field of mobile development. How quickly can we create an application and implement a service, and how do we best expand the cloud environment for it? These sorts of goals are clear. That is why we can say "we will get to that later."

Furthermore, the experience we accumulate through new undertakings should be called "design patterns," and



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I think these will be able to provide know-how for even faster development. The number one thing in digital business is speed, so patterning is an effective approach, even if there are some limits to its applicability. Neither ready-made nor entirely custom-made, we can implement services speedily with a kind of semi-custom tailoring.

─ I think "lean and agile development" is important, but in actual business things, including drawing up contracts, things are often not so straightforward.Imada: That is precisely the challenge. Since our clients define the requirements, we do not simply make the service, but we must work together with them to shape what is needed from our thoughts. The way that roles are shared and even contracts where the rewards are shared (revenue sharing) are being considered. Already, we have contracts in place where the incentives are based on performance-based compensation with certain companies.

Using Digital Technology to Make Dreams a Reality

─ New technologies arise one after another. Some startup companies will likely be good at this as well. What advantages does Fujitsu have in particular?Imada: Certainly the latest technology always needs to be evaluated. That being the case, the best approach is to test it out first. We build our knowledge and learning through trial-and-error use within the company, and even our failures teach us a lot. Our company has the size, strength, and organizations in place to make that possible. In addition to the Digital Front Business Group, we have the Service Technology Unit, and Fujitsu Labs, among others, all working together so that we can achieve our aim of being a key figure in determining the future roles of new technology.

The achievements we have accumulated in working with SoR also provide a great advantage. Even if you make an aggressive business model or system, you have to be able to connect that somewhere to the backend of the basic system. SoR knowledge becomes indispensable in doing so, allowing us to consider methods of linking together

applications and data, while also being able to identify the range of impact when trouble occurs. In that respect, we can make use of our abundant customer base, knowledge of the industry, and knowledge of systems.

─ Finally, could you discuss the issues faced in your company's efforts central to the Digital Front Business Group?Imada: Although I said this before, we pursue training as many people as possible with the spirit and insight to set out on a digital journey, along with the ICT fundamentals and methodology needed to give the ideal shape to ideas. To that end, my mission is to prepare the corporate culture and structures to allow free movement in that direction to put things into practice.

Miyata: In order to ensure that our efforts in working with customers don't come down to mere experiments, we also have to put these elements into practice at our place of business. There are many places to actually test such things within our company. While engaging in a good deal of PoC, we have also been able to connect with customers. In "FUJITSU Knowledge Integration Base PLY" we have offered a place for co-creation, and daily idea-a-thons and hack-a-thons are being held with participants reaching 17,000 in the past 10 months.

However, it cannot be denied that there were not enough engineers to make use of these sorts of places. As Imada has said, increasing the number of innovators who can take concrete action in digital journeys is an urgent matter.

Our personnel has been evaluated and nurtured by our customers, which is something difficult to experience in the matured SoR world we have today. Still, the world of SoE that is now moving into full swing will provide a great many opportunities. This is a great chance for us.

By creating new businesses with customers in the field of SoE, we can get customers up and running on the wheels of both SoE and SoR. That is precisely the value of our company's mission working as a partner with Japanese companies.


PART 2

Service Frameworkfor Co-creation

The "Service Framework for Co-creation" has been established as a guide for going on the digital journey. With the OODA Loop as its backbone,

it consists of ① Gathering of Information, ② Idea Creation, and ③ Lean Startup. There is no need to fear being different;

this is instead the new orthodox, and can even be called the steady path. Here the ingenuity behind co-creation will be explored, including the meaning of the "place" where it occurs.

C O N T E N T S

2-1［Overview］Compass for the Digital JourneyThe "Service Framework for Co-creation"

2-2［Gathering of Information］Understanding Latest Practicesand Technological TrendsThrough Analysis, Surveys, and Talking to Practitioners

2-3［Idea Creation］Idea-a-thon Implementation Drawing Attention asan Idea Creation Method

2-4［Lean Startup］Real Software Technology for a Rapid Evolution of Services

2-5［Places of Co-creation］"Co-creation Places" Seen in PLY & HAB-YUHonest Discussion, Devising Innovative Ideas

［Column］Sample Case of the Service Framework for Co-creation and Measures for Making PoC Successful

16

34

37

29

24

19


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Service Framework for Co-creation Ove r v i ew

Compass for the Digital JourneyThe "Service Framework for Co-creation"

We have been thrust unexpectedly into the era of the "VUCA" world. Recently, it has become an oft-heard phrase. VUCA is an acronym standing for Volatility, Uncertainty, Complexity, and Ambiguity. The idea is that our ordered, stable society has now headed in an uncertain and unpredictable direction.

One of the driving forces behind VUCA is digital technology. A new, nameless company suddenly emerges or an unexpected technology is born, and one after another events that shake up the old elements of competition and business composition take place. The trumpeting of Digital Transformation (DX) is now why every company must also seek to address DX. There is no choice but to follow the path of the digital journey fully aware that difficulties lie ahead.

Yet this can be a challenge for many companies. One thing that can be difficult to figure out in how to walk the digital journey is where to start. Businesses cannot simply follow the path of a predecessor (advanced company). While normally a company would just end up playing second fiddle, in the digital world the result of that is usually failure. There is also the matter of tackling digital technologies that are not necessarily related to the main business. It is essential to acquire a talented and reliable partner.

The OODA PatternService Framework for Co-creation

Fujitsu first advocated the concept of "Knowledge Integration (KI)" two years ago. This was a declaration of Fujitsu's goal to realize business innovations by making use of wisdom/knowledge from both inside

and outside user companies. And in May of 2016 , the evolution of KI called "Knowledge Integration in Action" and the "Service Framework for Co-creation" were announced. The approach can be summarized as working as partner of user companies to jointly formulate business innovation and creation.

A year later, Fujitsu further built upon its Service Framework for Co-creation and engaged in continuous trials to make the system ready and solid for practical application. Metaphorically speaking, the theory was that "we need a guidebook for walking the digital journey"; we needed to develop a substantial, concrete method that could be executed for moving from starting out, to discovering innovations, and then cultivating them. That will be explained in this part with the new "Service Framework for Co-creation." Still, it is not intended to be some special or fancy thing, but instead, orthodox.

The basis for the framework is the "OODA Loop" (Figure 1). This is the best method when the situation is changing every day and is a theory showing the process relating to decision making. Ikujiro Nonaka, Professor Emeritus at Hitotsubashi University, in his paper "Management by Knowledge Maneuverability," recently has attracted a lot of attention referring to this also in the realm of cyber security.

You are likely already aware of this but to briefly explain, the process begins with Observe, based on that, you Orient and Decide, and then end with Act. These four elements are performed rapidly and sometimes concurrently as the skeleton for completing an objective. Compared with PDCA (plan, do, check, act), Observe takes top priority. With the rapid changes that can occur

Yutaka Osada　Senior Manager, Strategic Planning Division, Business Management Unit

Toshikuni Yoshida　Strategic Planning Division, Business Management Unit


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Service Framework for Co-creationOve r v i ew Ove r v i ew

in the business environment, we need to respond quickly, and in order to be proactive in our approach, it is clear that this theory is appropriate.

Fujitsu has had a focus on the OODA Loop since around 2013 and has had repeated discussions. It seems only natural to establish the OODA Loop as the base of the guide for the digital journey. The result has been that the "Service Framework for Co-creation" consists of three phases: ① collect information as widely and deeply as possible concerning trends and new examples, etc., of emerging digital technologies; ② based on that information, consider ideas for business innovations and creation; ③ quickly perform trial-and-error tests using these ideas. Like OODA, these three phases need not occur in a set order, and it should be noted that they can occur at the same time, that the order can be switched, or a part can be skipped.

Practicing Co-creation by3 Phases

Let me explain this a little more concretely. Figure 2 shows the overall picture of undertaking co-creation. In the initial "Gathering of Information" phase, we collect information and knowledge as widely and deeply as possible in order to determine the theme for proceeding on the digital journey. Fujitsu's role in helping to carry this out is that with bases around the world, we can take advantage of being a global company with a human network. In particular, we aid in the gathering of information about advanced case studies and trends in

digital technology through research, surveys, and other methods via implementing overseas visits, professional engineers, and researchers.

At the risk of repeating myself, there is a lot of waste and risk in making something new based on insufficient information. What technology should R&D focus on, what are the possibilities, what companies are making strides and changes in what areas, what are the policies and regulations for each country's government, etc. are elements that will not impede success so long as the newest and most detailed information is available. I think this phase is incredibly important.

In the "Idea Creation" phase, we form a substantial idea of how to proceed based on the theme determined from the collected information and the circumstances of the company involved. This corresponds to the orient and decide portion of the OODA Loop. The older version of this is the KJ method, and while recently there has been a myriad of Future Center and design thinking, etc. in the Service Framework for Co-creation, the basis is the "idea-a-thon." Fujitsu has a lot of practice and experience related to idea-a-thons (hack-a-thons), and they have proven to be very effective methods as techniques for involving various stakeholders.

In the final "Lean Startup" phase, we develop the necessary applicat ions and try them out . This corresponds to action in the OODA Loop, and the feasibility is verified using PoC (Proof of Concept) / PoB (Proof of Business).

Figure 1: Flow of the OODA Loop; the figure is the OODA Loop taken from maneuver warfare theory as developed by John Boyd

UnfoldingCircumstances

OutsideInformation

Observations

Implicit Guidance& Control

FeedForward

FeedForward

FeedForward

Implicit Guidance& Control

FeedbackFeedback

Unfolding Interactionwith Environment

Unfolding Interactionwith Environment

Decision(Hypothesis)

Action(Test)

Observe Orient Decide Act

Analysis &Synthesis

CulturalTraditions

GeneticHeritage

NewInformation

PreviousExperiences


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Service Framework for Co-creation Ove r v i ew

The key to this phase is the latest in software development processes and a development and execution environment created using cloud technology. Frankly, we realize that Fujitsu is a bit late to the scene in this area, and therefore we do not stick to using Fujitsu's own cloud environment. We also use AWS, Azure, or IBM BlueMix as necessary. Of course, the MetaArc (K5) cloud environment in Japan is also necessary, and we are working to help strengthen and expand it.

In addition, in the stage where the digital transformation is producing results, it is necessary for operations to be compatible with new systems and services as well as existing systems. With regards to this aspect, we can proudly say that we have a respectable advantage. In the subsequent sections of Part 2, the actual efforts being made within these phases will be explained more substantially.

Figure 2: Overall picture of the co-creation effort

Gathering of Information (Gather info &

knowledge widely)

Co-creationPhase

Resources

Technology

High-speed Response

Define Themes to Undertake・ On-site studies・ Investigation agents・ Lectures by experts & specialists・ Digital business training

Lean Startup(Develop and test)

Take Ideas to Markets・ Lean Startups・ Agile Development・ Digital Business Platform

Idea Creation(Forming ideas related to

discovered problems)

TeamCustomer(Traveler) x Fujitsu(Partner)

Put Chosen Themes intoConcrete Ideas

・ Idea-a-thons・ Hack-a-thons・ Workshop with designers and consultants

Digital Journey

Resources & Technology to Support a Digital Journey

Fujitsu Group(Fujitsu, Fujitsu Research Institute, Fujitsu Design,

Fujitsu Learning Media, Fujitsu Social Science Laboratory,

Fujitsu FSAS, Others*)

R&D (Research Bases: Domestic/America/Europe/China)

Contributions to Development(Standardization Organization, OSS Community, Participation in Industry Groups)

Partner Company(domestic/overseas) Crowdsourcing

※ About 500 Consolidated Subsidiaries, Approx. 156,000 Employees(As of June,2016)

Digital Technology of Our Company/Other Companies(Cloud, Analytics, AI, IoT, API, Security, etc.)


Service Framework for Co-creation G a t h e r i n g o f I n f o r m a t i o n

PART 2-2

Many companies are moving full steam ahead in trying to address digital business. However, often it can be difficult to see where to start, and ideas coming from the company can seem just like rehashing. So while they are working hard, it can be difficult to try and move beyond simply trying to improve upon existing business, and we often hear that it is too hard to find an innovative idea.

Is not a major reason behind this that there is a lack of information for creating new ideas? For instance, looking at IoT, big data, AI, etc., say you have studied what can happen if you connect your products to the internet. But the resulting usage will not always reflect everyday life, and there is a natural limit to the ideas and concepts we come up with. In short, without the input of new knowledge in relation to digital technology, coming up with an innovative idea is difficult.

Of course, you can get certain information by searching professional journals or the internet , and if you participate in IT vendor conferences or seminars where experts gather, you will come into contact with more fresh information. And while there is no doubt that this kind of information gathering has its merits, it is certainly not sufficient in terms of the OODA Loop's "Observe" step.

In times of war, the emphasis is on primary information that you have gained through your own reconnaissance. You naturally do not trust newspapers or rumors. Similarly, information from the internet and seminars is a kind of secondary information. The important thing is to act directly using your own senses to learn, or think deeply on information acquired from serious discussion and debate. Such information gathering activities are crucial to going on the digital journey.

However, it is no easy task for companies to aggregate information on the daily-changing digital business that relates to their circumstances. So Fujitsu, in the past, has brought together its research efforts into practices, and summarized them into a kind of single step that is the "Service Framework for Co-creation" Here its contents will be discussed. Now, this is not a completed format, and this seems only natural in the evolution of information gathering programs such as supplementing menus, etc. I wanted to acknowledge this in advance.

Research Programs Gathering Information from the Field

The program for information gathering proceeds from largely four items: on-site visits, investigative surveys by representatives, lectures by experts and specialists, and training (Figures 1 and 2). The most important of these is on-site visits(field work surveys). Many advanced initiatives head overseas, so what kind of technology and efforts are over there, what awareness do companies possess in terms of the issues they are dealing with, what technologies and services have been put to use locally, and what measures and procedures are used? These questions and more arise. This takes time and money, but seeing something firsthand is worth so much more than just hearing about it, so this makes for the most effective and shortest path overall.

So specifically how is this handled? First we draw up a plan for about 1.5 to 3 months. Based on corporate objectives and requests, we use Fujitsu's internal network to determine sites to visit, and then make appointments and confirm a schedule. Specific programs for individual companies are treated as confidential and will not be revealed, so from here let me present

Shozo Sakai　Senior Manager, Digital Transformation Business Unit

Understanding Latest Practicesand Technological Trends

Through Analysis, Surveys, and Talking to Practitioners


Service Framework for Co-creation G a t h e r i n g o f I n f o r m a t i o nG a t h e r i n g o f I n f o r m a t i o n

PART 2-2

Figure 1: Process and Example for On-site Visits

(1) On-site VisitSupport for understanding real circumstances through a field survey from interviews and proposals at the site to on-site attendanceand creating a visit report.

1-2 Months 0.5-1 Month 3-5 Days 1 Month

Interviews, Study of Site to Visit Confirming Schedule On-site Attendance Report

Flow of Visiting Programs

Field Enterprise Overview

Common -Get up close with the forefront of digital business and learn the facts. Visit startups on the west coast, visit sites utilizing advanced technologies such as robots, etc., meet up with local engineers, and visit the d.school at Stanford, etc. over the course of 3-5 days.

Finance Major BankExplore FinTech trends. Visit 6 companies in 2 days on America's west coast and 2 days on the east coast. Visit local financial institutions to see initiatives and actual stores' responses to digital currencies like Bitcoin, including on-site learning about money-less payment, etc.

Communications Mobile Communications

3-day on-site visit to build connections with foreign companies. Annual mobile solutions business meeting/exhibition in Barcelona, Spain to meet up with other companies. Observe latest trends in communication infrastructure, such as wireless communications (5G), etc.

Home Electronics Manufacturing / Communications

Focus on CES event held in Las Vegas, and learn about the latest developments in consumer electronics (smart appliances) utilizing voice recognition, etc. See how latest devices are utilized and meet up with several venture companies.

Example Visit

a sort of sample tour of Silicon Valley in the U.S. as an example. It should provide a clear enough image of how proceedings are conducted.

When staying on site for 3 days, it might look something like the following. On the first day, after receiving lectures on the latest trends from local analysts and specialists from Fujitsu, go see the technology being put to use. For example, you might see a 2-meter tall egg-shaped robot manufactured and sold by Knightscope that patrols carparks in place of security guards, and a "Robot

Butler" that can work as a hotel clerk. After this onsite visit, the first day finishes by participating as a guest in a meetup with local business people and engineers.

For the second day, we visit the Plug and Play Tech Center incubation facility and hear the story of a venture company. Allow me to list a few of the companies that were visited in 2016. Arx Pax is a company that specializes in magnetic field technology, and they are currently working on temporarily floating an entire building off the ground using magnetic force. There is a

Figure 2: Experts Study Specific Themes and Lecture

(2) Investigative Survey by RepresentativeExperts investigate and report on initiatives for digital business in Japan and overseas on the latest technological trends.● Discover specific issues through on-site visits and have an expert act as a representative when further investigation is required● Consider companies' leading-edge initiatives and business models● Look at the latest technological trends (IoT, big data, AI, security, etc.) and see what the next promising trends are

(3) Lectures from Experts and SpecialistsDiversifying perspectives by exchanging ideas and opinions with experts and specialists from specific industries/businesses and technological backgrounds.(Example) Roundtable exploring possibilities for AI's use in improving contact with customers (1/2 to 1 day)● Lectures from experts (learn about trends in sophistication of contact with customers, etc.)● AI specialists present on possibilities of AI in customer contact● Exchange opinions, closing (share awareness of problems and topics)

(4) Fujitsu Digital Business CollegeFour kinds of training courses to nurture human resources for advancing and implementing digital business at the corporate level● Digital Strategies Course: foster a mind and perspective to lead in digital business● Design Thinking Course: learn business creation methods in design thinking● AI/Analytics Course: utilize advanced technologies such as AI and machine learning, etc., and develop human resources who can use them practically in businesses● Security Course: understand security trends, and acquire knowledge of system design and operations based on tendencies of attacks



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G a t h e r i n g o f I n f o r m a t i o n

possibility that they will fundamentally change the way we think about earthquake-resistant technology. Modbot is a company that allows for robots to be built using different combinations of parts like Lego blocks. Their aim is to offer affordable robots that have functions corresponding to their users' requests.

Through visits and Q&A sessions with these companies, we were able to come in contact with the most cutting-edge technology, and there is a clear advantage in being able to go to these sites and experience both the development methods and the speed with which they work. The third day is similar. For instance, we visit local financial institutions to explore the trends in FinTech, and by inspecting stores, we can observe payment methods. Afterwards, we visit Stanford University's d.school, known for its design thinking, and finish our tour.

This is a very brief explanation. Every day, so long as there is room in the schedule, there are conferences being held that can be visited, and we also encourage you to stretch your legs a bit and visit other areas on the east coast, etc. It is not enough to visit only one location, and other places need to be examined as well, such as Germany, China, and Israel's high-tech field, along with the governmental efforts in various countries such as in northern Europe. Where we visit changes according to the circumstances, whether it be to venture companies, large enterprise, or government institutions. This allows for a full, three-dimensional grasp of things.

3 Information Gathering Activities are Prepared:Investigative Surveys, Meeting with Experts, etc.

The second method of an investigative survey is set up to complement the visits to the sites. For example, the means of communications in the IoT is daily being watched and studied by researchers, and engineers working with blockchain technology and its applications are entering Fujitsu. Instead of companies themselves going to sites and conducting interviews, these people investigate and report. This is effective when there is not time to do an inspection or there would be benefits to a highly qualified professional doing it.

The third means is setting up a program of meetings for the exchange of ideas with experts and specialists from certain industries and academia. Experts from within Fujitsu and the assigning of human resources they have using personal connections can facilitated if necessary. Listening to opinions can allow you to strategize for on-site visits or deepen your understanding of specific themes after a visit; this is a great way to diversify your perspective. For instance, some things that may be discussed are in the financial industry if advancements are being made in contacting customers using digital technology or what sort of business is AI making headway into corporations.

The fourth approach is the Fujitsu Digital Business College research course started by Fujitsu in 2017, aimed at the leadership of information systems departments. The systems department, in addition to developing and operating business systems, is required to take up the role of promoting digitalization through the entire company. To that end, we think that it is necessary to acquire systematic knowledge and skills as a place to start rather than ad hoc seminars and training. Human resources that will further digital business are fostered through lectures and workshops given by experts in various fields and our own engineers within four established themes: Digital Strategies, Design Thinking, AI/Analytics, and Security.

Networking and Conducting Collaborative Research with Ventures and VC

We have just covered the outline of the information gathering program. In order to make these things possible, various activities are needed, like networking connections with companies and people, in addition to quickly apprehending trends in cutting-edge technology and the efforts of advanced companies. As a global company, Fujitsu with its R&D and business bases in various locales engages daily in these kinds of activities.

This is why we are able to negotiate onsite visits with companies, assign domestic and foreign experts and researchers, and arrange places for discussions. It is important to make full use of these in information gathering



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G a t h e r i n g o f I n f o r m a t i o n

for companies, and they are the skeleton of the information gathering process in the Service Framework for Co-creation. That being the case, what exactly are the Fujitsu R&D bases? I would like to talk about those a bit more here.

First of all, Fujitsu's research organization is made up of four parts that in addition to research centers in Japan includes Fujitsu Laboratories of America (FLA), Fujitsu Laboratories of Europe (FLE), and Fujitsu Research & Development Center (FRDC). Domestically our research centers have around 1,200 researchers, and they work in a wide range of fields that include advanced materials and next-gen elements, networks, research and development of cloud systems, and creation of next-gen solutions. Some of these researchers are those that perform the on-site investigations as representatives for other companies and engage in the exchanges of ideas and opinions discussed before.

On the other hand, the FLA, which was established in Sunnyvale, California in 1993, also now has a base in Richardson, Texas with researchers consisting of 60 people and small households. However, 70% of them hold a doctorate, and are engaged in research and development in advanced fields, ranging from hardware such as processors and beam transmission devices to software such as blockchain and AI. We also conduct joint research with local universities and startups, specifically in areas of FinTech, ManuTech, and MediTech, etc. involving influential ventures and VC.

Using our geographical advantages, we are also active in studying and disseminating information on the latest trends, and have brought together leading-edge information on topics such as FinTech and AI with reports published to the Fujitsu Research Institute website (http://www.fujitsu.com/jp/group/fri/column/). In our annual event "Fujitsu North America Technology Forum," we strengthen our connections in the area.

FLE: Skilled in Big Data Analysis and FRDC: Making achievements in Image Analysis

FLE was established in the outskirts of London

in 2001, and with about 40 researchers , it was a very diverse research institute with more than 15 countries represented. There we study Applications of supercomputers, such as ocean, organic lifeforms, and biological simulations, Big Data, and Network services centered on next-gen wireless technology. As a founding member of the 5G Innovation Centre headed up by the University of Surrey, we are currently working on developing technology as a member of the 5G PPP (5G Public-Private Partnership Association) on a collaborative research project in the field of communication infrastructure in Europe.

Work in the healthcare field is also being done. For instance, we engaged in field trials to support the decision-making of specialists in mental disorders, collaborating with Fujitsu Spain. Combining the big data analysis technology of FLE and the anonymization technology of Fujitsu Laboratories, we succeeded in calculating the potential risk of alcoholism in patients with an accuracy of over 85%.

Established in 1998 in Beijing, the FRDC now also has bases in Shanghai and Suzhou. It consists of 120 people in the three research departments of information processing, communications technology, and media analysis technology. With regards to easy-to-understand results, there exist the following facts. Early detection and extinguishing of fires is an urgent task with 9,000 incidents a year in China, causing the equivalent of 10,000 Tokyo Domes of forest to disappear. The FRDC used image sharpening and object recognition technology to develop technology that will automatically detect the initial signs of a fire. It was decided to be put into use after showing a detection accuracy of 99.36% in a benchmark test in Fujian Province. It is currently not limited to only fires, and is being developed into wide-area video monitoring.

Participating in Consortiums maximizing the acquired information on R&D

Fujitsu also participates in various ICT-related consortiums and standardization-related groups, and



PART 2-2

puts that into working on technological development and formulating standards. Table 1 shows a part of this. We commit to activities involving cloud technology, the IoT, OSS, etc., with the main purpose of discovering new results, and while forming close connections through participating and contributing, we get a handle on the latest trends and where technology is headed. Therefore, we see the Service Framework for Co-creation as something that contributes back into companies.

Let's use the "Container technology" that is invaluable in developing and evolving applications quickly as an example. As technology development moves along among advanced companies, specifications can be a bit jumbled, and as early as 2015, there were concerns about problems with the portability of containers. As a result, US venture companies and leading ICT companies in the U.S. using container technology organized the "Open Container Initiative (OCI)” in June 2015 and began setting standards. Fujitsu was the only Japanese company to join as a founding member and contribute to standardization.

The same is true for blockchain, which is being used in various fields throughout Europe and the U.S. We were involved in a co-creation project setup by The Linux Foundation in December 2015, called "Hyperledger." We have been contributing and performing demonstration experiments involved with development. As an example, technologies to prevent the misuse and exploitation of digitals keys, which has proven a problem for blockchain, have been developed by Fujitsu Laboratories and FLA, and we have made great contributions toward their practical use. The raw information obtained from these front line activities have a value that cannot be obtained from websites, etc., and that can be provided quickly to companies incorporating digital businesses.

That concludes the general overview of the content of the research programs, Fujitsu's system for supporting them, and the efforts we have made. Currently, we are preparing a program release for the first half of 2017. We will certainly deliver the latest information by taking full advantage of Fujitsu's global network.

Table 1: Examples of consortiums and organizations Fujitsu is committed to. Only overseas bases and management committees, etc. with a central role have been included.

Subject Consortium, Standards Organization Overview of Activities

Cloud

Container Technology

Open Container Initiative (OCI)Container technology standards body that enhances the rapid development and portability of applications. Fujitsu has participated as the only Japanese member of the group since its inception. Members include IBM, Microsoft, and Amazon, among others.

Cloud Native ComputingFoundation

An organization promoting the development of technologies for creating cloud applications and services, where container technology is at the core. Fujitsu has been engaged with it since the beginning. Members include Google, IBM, Intel, NEC, and RedHat, among others.

PaaS Cloud FoundryUnified method provided through OSS for control of executions and communication of working applications on a PaaS. In addition to providing things to OSS, Fujitsu also contributes to community management. Members include IBM, Intel, HP, VMware, NTT, Hitachi, and others.

IoT

Common Services

ITU-T (Study Group 20)International standards organization for telecommunications. Study Group 20 (SG20) was established as a research council in June 2015 for a wide range of issues, including IoT, M2M, ubiquitous sensor networks, etc. Fujitsu helped drive activities as an SG20 vice chair. Participation came from many countries in Europe, Asia, India, and Africa.

oneM2M

An international standardization organization operating with major network standardization organizations in Asia, the U.S., and Europe. Establishes specifications for common services that manage IoT devices, communications, etc.Fujitsu has contributed to formulating specifications as a WG3 (protocol field) vice chair. Members include IBM, Intel, Cisco, NEC, Hitachi, and Huawei, among others.

Edge OpenFog Consortium A consortium to encourage standardization organizations and develop edge architecture, test beds, etc. Fujitsu is working as a Japanese team member.

Core Network 5G PPP An academic-industrial collaborative project in European telecommunications infrastructure. FLE works in the R&D project SESAME on small cell technology.

Industry Digitalization

Industry Internet Consortium (IIC)An international consortium established by GE, IBM, AT&T, Intel, and Cisco in March 2014. Fujitsu acts on the steering committee and as a WG co-chair of security. A proposed test bed based on IoT practice cases was officially approved August 2015.

Plattform Industrie 4.0A community to help produce advancements in the manufacturing industry led by Germany. Members mainly include German companies, such as Siemens, Bosch, and SAP, among others. Fujitsu's independent subsidiary FTS works as a WG3 (security) member.

Finance Blockchain Hyperledger ProjectProject for the standardization of blockchain in data management technology and P2P distributed processing as used in Bitcoin. Fujitsu has contributed to the practical usage in the development of security technology within the technical steering committee.

IT Infrastructure Linux The Linux Foundation

A nonprofit organization promoting the spread of Linux. Fujitsu has been deeply involved since the group's inception, and was recognized for its contributions to Linux kernel development in receiving an achievement award in November 2012. Fujitsu became a vice chair through the steering committee. Continues to make notable contributes to growth and improving reliability.


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After visits, interviews with experts, and repeated discussions, we have collected our information. Looking to the OODA Loop, it will still be necessary to continue to practice information gathering during the digital journey. However, we cannot spend all our time on that alone. We need to create ideas and put them into practice to develop businesses and innovations. Here we will look at "Idea-a-thons," which are a powerful tool for achieving that.

Finding Ideas Different from Outside the Existing Pathways

Various methods have been devised in the past for formulating new ideas. They are too numerous to mention with everything from the KJ method, to brainstorming, to mind maps, to Mandal-Art, and so on. Recently, future centers have acted as places to engage in dialogue about mid-to-long-term issues and themes, and design thinking as a means of pursuing the essence of problems and how to approach them has been attracting attention. An additional method that can work with this for collecting extensive external knowledge is crowdsourcing.

While making use of these methods and places when they are suited to the task, Fujitsu has also focused on and practiced a method called the idea-a-thon for the past three years. The name comes from combining the words "idea" and "marathon." A large number of participants come together as a team to share ideas about a specific theme, resulting in a method for formulating ideas in a way that creates competition while bringing together a wide range of ideas. One reason that Fujitsu has given great attention to this approach is that multiple organizations or companies can participate, and it works

as an effective method for finding ideas different from any single current line of thought through interaction.

Another reason is that since participants are together at the same time in the same place, the effect of the shared experience is also an important advantage over some other methods. Going beyond just positions and titles, a wide range of participants will have different backgrounds and skills that come into play while discussing a shared theme. Through this experience, people tend to prioritize their organization or company, or you could say that by putting everyone on equal footing in the sharing of ideas, you can expect to open a hole to let in a fresh gust of air. This can also provide a look at matters from different angles than those that come from small group discussions, interviews, and onsite visits, etc.

Benefits and Flow of Idea-a-thons

To sum up, an idea-a-thon is suitable for situations where:・ Although the need for a new approach is understood,

a specific direction remains unclear;・ A sense of urgency is shared across departments,

and interest and awareness about new businesses is increased;

・ More diverse perspective and ideas are found that offer alternate courses for the future. At this stage where information gathering and problem discovery are used to clarify the challenges the company faces, much needed ideas can be revealed, and many stakeholders can be involved while brushing up ideas.

However, idea-a-thons are not all-purpose either. One

Akihiro Kuroki　Chief Senior Consultant, Consulting Unit, Fujitsu Reserch Institute

Hidehiro Takeda　Digital Transformation Business Unit

Idea-a-thon Implementation Drawing Attention as an Idea Creation Method


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No. Program Overview Duration Schedule

1 OrientationShare the background and purpose of the event, the theme and schedule, and evaluation points with participants. Increase participants' understanding by explaining the aim and backdrop for implementing the idea-a-thon.

30 min 9:00-9:30

2 Keynote(20 min/person, 2-3 people)

Lectures to gain perspective and hints for formulating ideas by deepening an understanding of the theme. Normally 2-3 people are assigned to provide a multifaceted perspective. 40 min 9:30-10:10

3 Idea Creation

Participants determine issues for the themes, and do a series of workshops to develop ideas for solutions. By combining individual and pair work, various possibilities for solving the problem are explored and visualized. Also, ideas are shared, and ideas that are agreed upon are presented, creating a pillar for team building. At that time personals ideas and suggestions should be recommended.

120 min 10:10-12:10

Lunch (~1 hour)

4 Team Building WorkshopsFocusing on presenters of well-liked ideas and participants motivated to work on them form teams. Teams may also be decided in advance by the organizer or recruit participants via team entry, but since emphasis is on participants to demonstrate their individuality and creativity, teams are often organized on the spot.

30 min 13:10-13:40

5 Development BrainstormingEach team refines the ideas. Easy to prepare materials are used, such as Styrofoam or cardboard, blocks, simili paper, and markers, are used rather than just theorizing in order to judge whether an idea will work through trial and experience using the body and objects, making the "whose" and "what is being resolved" concrete.

140 min 13:40-16:00

6 PresentationEach team presents for 3-5 minutes; afterwards they have a question-and-answer session with judges. This portion is not only done in a presentation format, but there are also cases where ideas are explained or questioned in an exhibition format.

60 min 16:00-17:00

7 Judging & CommendationsAnnounced ideas are judged and awards are commendations are given. The foremost point becomes the organizer deciding if something should continue to be worked on. Afterwards, there is a social gathering, providing an opportunity for participants to connect and form lasting relationships.

60 min 17:00-18:00

Free Discussion & Networking

Table 1: Typical Idea-a-thon Flow

Photo 1: In this idea creation workshop individuals create idea sketches, roughly writing out thoughts.

Photo 2: Each team brainstorms to refine ideas. This is the culmination of the idea-a-thon.

major issue is that in many cases, they will end as a temporary event, and rather than the implementation of an idea-a-thon becoming a means, it becomes its own purpose. Fujitsu also has a good deal of experience with this. There is also the matter that a single idea-a-thon rarely gives rise to a particularly novel idea. In reality, regardless of the rare occasions where a great idea comes about in one go, seldom is the event held more than once.

So how can we implement an idea-a-thon that goes beyond the event and generates innovative ideas? Before getting to that point, let's look at the flow (procedure) for the idea-a-thon first. Table 1 shows an idea-a-thon conducted by Fujitsu.

The steps are ① orientation, ② keynote, ③ idea creation workshops (photo 1), ④ team building, ⑤ development brainstorming (photo 2), ⑦ presentations, ⑧ judging and commendations.

In our experience, these are preferable standard steps, but please be aware that this does not necessarily mean you must do it exactly this way. For example, keynote speeches by experts from inside and outside the



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company are not always necessary if the participants are already highly aware of the theme chosen, and apart from the idea-a-thon a study group format can also be used. Commendations or awards are also not something that absolutely must be done.

All that aside, the event usually takes one or two days and has from 20 to 40 participants. In addition to an emphasis on creating ideas within an environment where everyone is on even footing regardless of position or status, casual dress that is easy to move around in is desirable since sometimes people will move around during workshops. Since the time required will vary based on the theme and number of participants , flexibility is required. When holding the event over two days, not only is there time for drawing up ideas, but the amount of input can be increased as necessary through incorporating field work, etc.

5 Points of Success Born from Practice

Let's return to the main topic. In order to implement an idea-a-thon that extends beyond the event and creates feasible and innovative ideas, what do we do? There are essentially five points to follow.

① Boil Down the Purpose/Theme

Certain important things need to be prepared ahead of time. You need to start by clarifying the purpose and theme of the idea-a-thon, the time it will be held, and the participating members and judges, etc. Apart from rare circumstances of exceptionally good fortune, it can be said that thorough preparation will decide the event's success or failure. For example, when considering possible themes related to automobiles, is "considering automobiles of the future," "considering transportation in the future," or "how we will get around in the future" best?

With the first theme of "considering automobiles of the future," it can be difficult to get ideas that go beyond just thinking about cars. "Transportation" will yield a broader range of ideas, especially if it is put as "how

we will get around." As another example, take a high ideal like "how to make such-and-such 100 times more appealing," and an awareness of the need to get beyond just following existing trends increases. However, if it is taken too far, participants' motivation to think on the topic will disappear. It is not about what is good or bad, but instead preparation is important for creating a close link to your purpose.

Even Fujitsu sometimes struggles with determining a purpose and theme, as there is no clear guidance as to how to approach it. But it is without a doubt worth the effort. Additionally, in making preparations there is a kind of hypothesis. Even if the expected result is not what you get, if you have a hypothesis of "next time let's change this and try it," then you can develop policy. It is necessary to make thorough preparations based on the information and findings obtained during the information gathering phase.

② Consider "People"

As a part of preparations, considering people is also important. Even if it is just inside the company, when there is a bias toward certain departments and age groups there will also be a bias in ideas, but if you have a diversity of job positions, skills, age, or nationality, etc., then normally it is easy to come up with ideas. If recruiting for participation is open, then it is inevitable that certain departments and strata will be focused on, so it is also important for the organizer to select people and speak out. In any case, "diversity" is the keyword when it comes to gathering participants.

Therefore, sometimes business partners, stakeholders outside the company, and ordinary people are involved. Although confidentiality is important, seeking diversity from outside the company provides opportunities to produce ideas rooted in understanding that could be difficult to obtain from within the company.

So what about keynote speakers? Those involved in the information collection phase and outside experts are good candidates, and when using outside experts, those operating in areas related to the theme and practitioners



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of digital business from different industries, etc. can be selected on a case-by-case basis. There is no need to be overly careful, but it is good to remember that the purpose of the keynote is to provide hints that can lead to ideas related to the purpose. In some cases prominent, charismatic guests are brought on in order to recruit participants, but this has no meaning unless their speeches link with the purpose and theme.

Judges are important for advancing new ideas into the next phase. Still, it is difficult to judge the ability to commercialize something in only a day at an idea-a-thon. Therefore, the organizer examines in advance what level of business creation or deployment the idea-a-thon will involve, and during preparations judging criteria should be determined. The standard is would the idea actually be worth a try and could there be an expected development potential? Based on this, those with the authority or responsibility of carrying projects forward or investing act as judges. It can also be effective to assign outside experts, investors, etc., to act as judges.

③ Repeated Divergence and Convergence of Ideas

Of course, novel ideas do not spring to mind just because we are talking in teams. Even within a single idea-a-thon, it is important to explore various possibilities through "divergence" and then narrow down ideas with merit through "convergence"; this should also be repeated several times. To that end, various methods for formulating ideas should be adopted. Specific methods are shown in Table 2.

Idea sketching from Table 2 is useful. Participants

just scribble using letters, figures, onomatopoeia, etc., concerning what kind of users they are thinking of, what problems they want to solve, etc. While artistic aptitude is nice, it is not particularly necessary. The effects of visualization are surprisingly significant in that it gives substance to the idea and further expands it.

In addition to these, we like to try and also take an "illogical" approach in response to what is considered obvious, natural, or common sense with regards to a theme. For instance, it seems natural that when you buy something you pay for it, but what about considering the opposite circumstance, where you pay for something from having tried it. In relation to the sensible "calling a taxi," there is also the nonsensical "a taxi will come." This is easy to do, but when using an effective idea method, helping participants to recognize their own biases makes it easier to come up with original ideas.

Using these methods, the facilitator fills the role of controlling how and when to switch between divergence and convergence. Creating an atmosphere where it is okay to say something absurd out of curiosity allows for further exploration of possibilities.

④ Clarifying Ownership of Rights, etc., in Terms of Participation

When inviting clients, customers, or users to participate in an idea-a-thon, it is important to clarify the terms of participation, including the handling of rights, in advance. Some might think "that's a bit rude," but if it is not done, then there are likely to be problems if a revolutionary new idea is thought of during the process.

Method Overview Positioning

Idea Camera Using photos to perform pseudo field work and discover issues from the users' point of view. Photos are prepared by the office or as an advance assignment for participants. Divergence

Speed Storming Participants pair up and dialogue ideas about the theme. By having people change partners several times, many ideas are generated. Divergence

Idea Sketch Ideas that each person finds interesting are roughly sketched out using letters, figures, sounds, etc. to give them substance. Convergence

Highlight Looking at each other's idea sketches, marks are applied where it seems that "this could have significant impact" or "this has future potential." Convergence

Dirty Prototyping Ideas are expanded by improvising simple prototypes using familiar tools like Styrofoam, toy blocks, simili paper, markers, etc. Divergence

Press Release Method While considering if it will resonate with users, an outline of the idea and its features is summarized in a press release format. To whom the idea applies, what problems it addresses, how it is different from previous solutions, etc. are described. Convergence

Table 2: Examples of methods for creating ideas.



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This can even be true for employees participating as a part of their job.

When holding an idea-a-thon in an open format, it is recommended to make any idea that is born belong to everyone who participated at that location. Rather than giving the rights to the idea to the organizers, we think it is important to create an environment where the opinions of the organizers and participants can collide and bring out creativity.

Contrarily, when disclosing confidential information about our company to draw up ideas , we find it necessary to have participants sign an NDA (non-disclosure agreement). At Fujitsu, based on the results and achievements of idea-a-thons thus far, we are preparing ways for appropriate handling of rights in both cases of open idea-a-thons and special closed idea-a-thons within a company.

⑤ Organizers Unite with Participants in Trial-and-error

Idea-a-thons are a great way to connect people who work at the same company that would not otherwise talk. Trial and error can be applied to one theme, and the effects of having the discussion be a co-experience have already been mentioned, though it loses meaning if everything ends after one time. We need to lay the groundwork that will allow for repeatedly addressing challenges in creating digital business.

In this respect, organizers and participants at idea-a-thons need to think along the same line. Members on the organizer side mixed in the participants need to dig deep on an issue and consider solutions. In order to connect a new idea back to business, the creative relationship between all participants, both organizers and participants, in exchanging with each other becomes important. An idea born at an idea-a-thon upon reaching that phase is helped through the human network of participants because from there it often can proceed on

to commercialization.

We announce the implementation of contents of idea-a-thons in the company newsletter, and inviting discussion on the company SNS can also be effective.

Creating Value from Ideas

Idea-a-thons are a means of creating ideas, and the goal is to have the idea realized in a way that allows it to grow as business. For that, it is important to consider development after the idea-a-thon is over. There are situations where "though I was commended at the idea-a-thon, I was not able to do anything further" or "we only repeat idea-a-thons, but there is no action to commercialize anything," which leaves only a feeling of having made empty efforts.

In order to overcome this kind of problem, as long as the organizers have those who proposed the idea or related parties that think "I want to give this idea some kind of shape," then even if the created idea is only now in its first phase, they should desire to put full support behind it. If additional information is gathered, a way to realize an idea can sometimes be seen; for example, by checking to see if there is already a similar business in the world, it can be thoroughly analyzed for its faults and chances can be identified.

"Now is a first step" is the decision of the judges, and beyond that the market may make a different judgement. More than anything, the cost of trying out and executing ideas is much lower than it has ever been. "Without many small failures, there will be no great successes" is the spirit of "Fail Fast" (to make many repeated small failures). The holding of an idea-a-thon is not itself meaningful; to be clear, it only has value when pursued by the implementation of the ideas created.


Service Framework for Co-creation L e a n S t a r t u p

PART 2-4

After creating ideas, it is finally time for service implementation. At this stage it is important that the service can be implemented quickly and put on offer with new feedback coming in so improvements can continue to be made. If things do not proceed as expected, it is time to return to idea creation or gathering information and start from the beginning. Although there are times when rework is needed, this is natural and a matter of course in terms of approach on the digital journey. So how do we allow for fast implementation and further improvements? In this section we will be focusing on those aspects.

In the "Lean Startup" phase of the Service Framework for Co-creation, we implement the idea formulated during the "Idea Creation" phase as an actual operating service or system. The goal is not to "make a service." We collect feedback from the service's users, then confirm the effectiveness of the idea, and finally refine the service or change the direction we are taking it. The true aim is to make the service successful using a so-called "lean startup" style.

Therefore, implementing a trial-and-error approach whereby the service is reworked or fails is the central premise. This is a significant difference from SoR. That said, a large rework or failure can become a waste of time and cost, which can cause the project to stop. That being the case, (1) small developments, (2) quick releases, (3) receiving feedback, and (4) determining directionality/goals are needed to perform an agile iterative development process where these elements cycle quickly, making small increments of progress.

Software Supporting Iterative Development

In iterative development, the process of development and delivery is repeated in a speedy and persistent manner. In order to incorporate feedback from the market, "agile development" and "DevOps" are important methods and practices to implement. Simply being agile at the level of the form is not enough, and the culture and climate of the organization and development teams responsible for the business projects need to be setup a certain way.

The software most effective for enabling this will now be introduced. In terms of functionality, ① "Project Management Capability" is important for visualizing the status of these projects that change from moment to moment, ② "Versioning Capability" is needed to manage the frequent changes made to assets being developed in an orderly manner, and ③ "CI/CD (continuous integration / continuous delivery) Functionality" will allow for the rapid cycle of development and delivery to be carried out smoothly; software that provides these functions and capabilities is indispensable.

① Project Management Capability

Japanese systems manage predicted progress using a bar chart (Gantt chart). However, the time from planning to executing is extremely short (usually several hours to a few days), and in repeated trial-and-error it can be necessary to frequently make changes to the plan once it is set up. For projects that prioritize rapid response to feedback, this method is not a reasonable approach.

In these types of projects, tools such as a "ticket management tool" (also called a "bug tracking system")

Real Software Technology fora Rapid Evolution of Services

Shinichi Kawakami　Customer Engagement Solution Dept. , Digital Transformation Business Unit

Yoichi Kurachi　General Manager, Digital Transformation Business Group


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and a "task board" are common means of management. Requests for improvement, bugs, etc., that need to be addressed immediately are registered in the management tool in the form of a ticket , and a task board is fundamental in visualizing the response situation (not started, being investigated, being implemented, etc.) (Figure 1).

② Versioning Capability

With frequent repetition of release and responding to feedback, there are many occasions when multiple members will need to make minor changes to the same source code concurrently. When this happens, there is a chance that some people might be working on the old source code as other people are working on a newer iteration of the source code, and the code's consistency

cannot be maintained. The important thing here is management of versioning. Without going into too much detail, a "tag" allows any previous version of the code to be restored immediately, a "branch" allows for parallel development without confusion, and a "pull request (or merge request)" helps release bug fixes in a consistent format with code integrity intact. These are common functions that version control tools have (Figure 2).

③ CI/CD Functionality

An indispensable tool in order to quickly execute iterative development cycles is "automation." Particularly when compiling and testing code, operations where the procedure has been decided in advance and needs to be repeated, speed will not increase without automation. For example, even in a single release with small changes,

Figure 1: Example of a task board (sample screen features use of the development support tool "GitLab")

Figure 2: Versioning Control System (Tag, Branch, Pull Request)

New Additional Function Branch

Master Branch

Bug Repair Branch

v1.0 v1.1 v1.2

Tag

Branch

Pull Request

v2.0

● Using the tag function, any version can be restored immediately.● Using the branch function, bug fixing and development of new functions can be done at the same time.● Using the pull request function, before code is integrated into the master branch, a consistency check (code review) can be performed.



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it is necessary to conduct tests that check the effects on the unchanged parts of the code as well. While this can be done manually, it can take a great deal of time. However, by automating these tests, the time from repair to release can be shortened.

A CI tool automates testing so that it occurs with the appropriate timing. For instance, if an update in version is registered using a version control system, these necessary tests will be automatically executed immediately. Furthermore, it is also possible to have an application that cleared the tests to be automatically deployed in the execution environment. By using CI/CD functionality, work that can take days and months can be completed in a matter of minutes and hours (Figure 3).

Providing Services Leanly through the Development and Execution Environment "MetaArc"

The software discussed in ① to ③ is indispensable in realizing agile iterative development, but of course that is not all there is. By using existing services' functionality or through the use of open source software (OSS) and Web API, and by adopting microservice architecture focused on container technology, today we can develop services and systems quickly and at low cost; the technology for making releases is spreading. The base environment for using this software and technology is the cloud, and in Fujitsu's case, MetaArc.

Next, using MetaArc as an example, let's consider this more in-depth.

When developing and implementing services operating on MetaArc, there are no restrictions on the development environment. If the team is familiar with Microsoft products, "Visual Studio Team Services" can be used. If the team specializes in software development using OSS, then the widely used OSS "GitHub" can be used. The development environment best suited to the project's circumstances and the team members' skill sets can be freely chosen.

So what about flexibility in setting the execution environment, which requires more computer resources than the development environment? Like many other cloud services, there is the ability to completely turn off the "build execution environment" function on MetaArc. This is "CF" and will be discussed next.

Service Execution Using CF

CF is an execution environment using the "Cloud Foundry" open source PaaS as a base . CF uses container-based virtualization to launch applications, so deployment processing that would take minutes with a hypervisor VM can be done in seconds. Of course, scale out to run many more instances can be performed with a single command. In this case as well container-based

Figure 3: Effects of Automated Testing and Continuous Integration / Continuous Delivery (CI/CD)

● Conventional (Manual) Case

Development Build Test Deploy Operation

Days to Months

● Case Using CI/CD and Automated Testing

Development Build Test Deploy Operation

Minutes to Hours



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virtualization is used, so it only takes seconds to startup. It is possible to operate by initially providing services with fewer instances and then increase the number of instances as usage increases. Since consideration for starting up with enough instances to provide sufficient room from the beginning is no longer necessary, no cost is wasted.

Functionality like that which CF provides is a must for providing services in a lean startup manner. Details on Cloud Foundry are omitted here as there are innumerable documents out there on it, but using the functionality mentioned, the cycle of (1) small developments, (2) quick releases, (3) receiving feedback, and (4) determining directionality/goals can be accelerated.

Further Accelerating Service Implementation

The development and execution environments already introduced are necessary measures for iterative development. However, even when these are made use of, when always using an abundance of cutting-edge technology to develop services, learning technology, technical verifications, and integration of multiple technologies takes time. For instance, when a company engaged in operating call centers thinks "we would like to mechanize this work using the wealth of response data accumulated in our company database," what exactly do they do?

There is already plentiful data. If "machine learning" is applied to the data, it seems like a service could be provided that accurately discerns the required answer for a user. Additionally, "chat" can be used for the user interface, and using "speech recognition technology" a telephone response is likely also possible. Still, how should they recognize the inquiry from the user? Perhaps "morphological analysis" can be used for that... Although the necessary technology can be aligned in this way, can it really be used effectively?

Of course, at Fujitsu we train engineers who are able to

do it. Unfortunately, there are not individual engineers familiar with all the available technology. They can build applications much faster than inexperienced engineers, but it will definitely take time. Perhaps during that time other companies will be making greater advances. In order to make sure that does not happen, a means of increasing the implementation speed is needed.

At Fujitsu, we advance our provided initiatives as a set of ① "an API group with integrated leading technology" and ② "software products converted to provide services with common functionality found in businesses" (Figure 4). Needless to say, these are not that versatile and are intended for use within a few specific scenarios. These methods are suitable for service development that is closer to SoR than SoE. Still, we think these are indispensable in a lean startup. These will enable the first steps, and by making those first steps run smoothly, there are also aspects that can be expanded to full-fledged SoE.

① API Group with Integrated Leading Technology

We prepa re serv ices that integ rate advanced technologies such as machine learning, chat, speech recognition technology, and morphological analysis. As an optimized micro-service and a service for a company's own system, there is also the ability to integrate these using a plug-in, and this enables short-term building of the service you wish to implement. It is advantageous to be able to implement services quickly, even if you are not familiar with the individual technologies. The matter of determining technological feasibility will be greatly reduced. In the case of the call center example from before, the time required for prototype development could be greatly reduced. Additionally, testing using actual data can start right away, speeding up service development.

② Software Products Converted to Provide Services with Common Functionality Found in Businesses

When using a chat bot for an automated response system in order to create a diversity of contact points with customers and improve service quality as mentioned in the call center example, the standard response


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process is to "receive, respond, and record." If a common function or template is used for the user interface for responding and tuned standard data for searching for and responding to a question, development can be sped up. These are provided as software components that can be used via the API. These software components also have functionality that allow for dynamic improvements. For example, "functions for automatic analysis of access logs and work-improvement proposal" or "functions for improving knowledge accuracy via self-learning using question and response history," etc. Using these functions, we can support the continued growth of services.

Establishing an Ecosystem of Continuous Growth

At Fujitsu, by providing this kind of grouping of services as quickly as possible, the implementation of business services is accelerated. Then, by using feedback obtained from the actual implementation of the service on site, the common services themselves will also continue to improve. In this way, both the business services and the common services have a mutually beneficial impact, and the intent is to establish an ecosystem that allows for continuous growth.

Figure 4: Software that Accelerates Service Implementation and API Use

Chat Application

Chat UI② Software Products Converted to Provide Services with Common Functionality Found in Businesses

① API Group with Integrated Leading Technology

External Services Company System

Natural LanguageAnalysis

Dialogue History Acquisition Knowledge Retrieval Authentication

SpeechRecognition API

MorphologicalAnalysis API

MachineLearning API

KnowledgeRetrieval API Authentication API

SpeechRecognition

PaaS

MorphologicalAnalysis PaaS

Machine LearningPaaS

KnowledgeSystem

AuthenticationSystem


Service Framework for Co-creation P l a c e s o f C o - c r e a t i o n

PART 2-5

Kouichi Hidaka　Manager, Advanced Technology Division, Service Technology Unit

Takashi Hirano　Director, Experience Design Department, Brand Design Strategy Division

Daisuke Takashima　Experience Design Department, Brand Design Strategy Division

"Co-creation Places" Seen in PLY & HAB-YUHonest Discussion,

Devising Innovative Ideas

It is hard for ideas to be born freely in conference room discussions. Some may respond that this is just not true. But please take a moment to imagine. The place where you sit has been determined by your job title and career history. There is usually only a whiteboard to use to aid discussion. And you aren't free to get drinks... Although conference rooms are suitable for transmitting information and sharing, it is clear that it is not a place for thinking through new things. This is not limited to Japan, and as a matter of fact, it is in Northern Europe that the "Future Center" was born. In order to encourage free and open-minded debate and innovative thinking, the idea was that the first thing that needed to be done

was change the environment.

More than anything, there are many ways to discuss and formulate ideas. Discussions without hierarchical relationships, brainstorming in groups, creating ideas in a circle, visualizing opinions using sticky notes, creating model representations, presenting in a theater format... Everything that can be useful needs to be included as much as possible. A space to work, a place to devise ideas, is needed. At Fujitsu, we have made several such places.

There is the FUJITSU Knowledge Integration Base

Photo 1: ① Full view of FUJITSU Knowledge Integration Base PLY and ② Usage Scene. ③ A variety of characteristic table types. ④ There is also a work room in one corner (FAB Space).

①

②

④③


Service Framework for Co-creation P l a c e s o f C o - c r e a t i o nP l a c e s o f C o - c r e a t i o n

PART 2-5

PLY (PLY), HAB-YU Platform (HAB-YU), TechShop, Minato-Mirai Innovation & Future Center, CO☆PIT, and FUJITSU Digital Transformation Center. Additionally, in April, Fujitsu Kyushu Systems Service opened Qube at the headquarters in Fukuoka. Here we will focus on introducing mainly PLY and HAB-YU.

Stimulating the Imagination at PLY

Fujitsu's engineers gather at Solution Square in Ota Ward, Tokyo. A corner of that which opened in May 2016 was PLY (Photo 1). PLY means to "twist and stack up." In the beginning, the only point was people and knowledge, and by connecting through lines of empathy and experiences, thanks to the creativity that emanates from will and passing, those lines became the face of the location and the face took shape as something more─those are the kinds of thoughts that went into this project.

Engineers and visitors have stimuli coming from this way, and the design is intended to be an open space

ripe for creating things. For example, trapezoidal tables with different angles are made to be able to combine into various shapes. Participants can either work closely together, or they can have their own wide-open space. Everything is movable, including a partition board, the position for a lecturer, and the placement of participants.

The chairs are hard. There is an opinion that "a relaxing sofa is best," but in order to encourage people to move around and talk, it works well if the seats are not overly comfortable. Although it does not necessarily have that effect, compared to a fixed arrangement, the potential is increased, and indeed, many participants so far have given evaluations such as "it was a gathering like I had never experienced before." There have also been many visits from other companies.

In PLY, there is a space setup called a "FAB Space" that has a 3D printer, laser scanner, laser cutter, etc. Although it cannot reach the level of the full-fledged facility "TechShop" in Roppongi, Tokyo, it is possible to do a bit of work and prototyping. Drones and robots have also been included so people who have never tried them

Photo 2: ① Overall view of HAB-YU and ② Usage Scene. ③④ Desks were made in a way that they can be arranged as desired.

①

②

④③


Service Framework for Co-creation P l a c e s o f C o - c r e a t i o n

PART 2-5

can have the experience of using them.

PLY received the Good Design Award of 2016. We received the high praise (from a judge): "A lot of co-creation places are made, but often the objective becomes to create a place. PLY's value comes from a lot of hack-a-thons and idea-a-thons already having been held, and as open communities are nurtured, this place has been created to accelerate their activities."

A Place of Design Thinking, HAB-YU

HAB-YU was opened in September 2014, two years before PLY, by Fujitsu Design's group of design experts (Photo 2). Naturally, the place's appearance is beautiful, and in developing the space the pursuit was to create a location for probing into design. The name comes from Human + Area + Business bound together with the verb in Japanese for binding or tying together being YU.

It is a place of co-creation managed by designers, and its six tables can each seat six people for workshops, and large events and sessions can include up to 60 people. The furniture can be re-arranged to setup an exhibition space.

The main use is as a workshop. For that purpose, pens can be used to write and erase freely on tabletops. The surrounding walls are all blackboards that you can draw and expand on as soon as you have an idea. Boxes can be used to adjust the height of the legs of the tables, and the chairs are lightweight and easy to stack. There are naturally tool boxes containing sticky notes and various writing instruments. With more than two years since it was built, it provides an environment where workshops can be carried out conveniently. In cooperation with the operating company of HAB-YU's building (MORI Building) and the region, field work and tests are also carried out.


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Sample Case of the Service Framework for Co-creation and Measures

for Making PoC Successful

Sony Bank specializes in internet banking. While characterized by an efficiency of not having stores, responding to users' inquiries had been an issue for a long time. Although there were contact centers operating during the day that could provide guidance and explanations concerning financial products and services, many users were business people and used the service predominantly at night. There was a mismatch. Of course, being a website there was a FAQ, but aside from those users who were accustomed to searching out information this way, the other users who were not had to engage in an excess amount of management.

Focusing on Chat bots

Meanwhile, Fujitsu had an R&D base in Silicon Valley, Fujitsu Laboratories of America, which explored the technology and business trends of the day. Among those efforts, "chat bots" began to emerge as a form of technology to enhance contact with customers. Chat bots were software that could communicate with other parties through a dialogue box on a website. The thinking was that "if this runs 24 hours a day 365 days a year, then user inquiries can be answered at any time." We invited Sony Bank staff, and through interviews together with local engineers and financial institutions, etc. , the applicability of this idea was assessed (information gathering/problem finding).However, this was of course not the end of it. While it was possible to respond to inquiries using natural

sentences and provide guidance on financial products, content changed daily. In order to stay in step with it, it became obvious during the information gathering phase that users would need to implement fine-tuning for machine learning and edit query data. Up to this point, the way Fujitsu's side had been in charge of building and operation presented problems in terms of cost and the speed with which functionality could be improved.

So what were we to do? We decided to develop a mechanism whereby the user companies could implement tuning of the machine learning and script editing. Specifically, a partnership was formed where Fujitsu provided the structure of the cloud service, and Sony Bank created the chat bot itself.

Using a Place of Co-creation for Implementation

Although the skeleton of "a service that allows users to create their own chat bots" had been decided, what kind of functionality it was to have was a whole other story. Since there was no external sample case to use as a reference, we had to devise this ourselves. A general-purpose chat bot that can answer any question is technically very difficult and has no meaning. One the other hand, if it is able to be narrowed down to guidance on a specific financial product, it is easy to make, but many chat bots would be needed. There would also be a need to have a method for guiding the user to communicate with the correct chat bot.

The "Service Framework for Co-creation" was considered theoretically and then created. Rather, the underlying elements of collaborations between Fujitsu and other companies were taken, and it was created taking strong commonalities abstracted from them. Here is one such project that I will describe, which is a comparatively easy to understand example of developing a chat bot while working together with Sony Bank. The objective will be to understand an overall image of the body of the system. In the second half, human resources at Fujitsu who worked on this project will explain the "key points for co-creation" not fully apparent in the same system. The most important point being "partnership."

Masakazu Nakamura　Digital Transformation Business Unit

Sample Case of a Lean Startup in PracticeDeveloping a "Chat Bot" with Sony Bank


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To determine the policy, we identified target users (new customers, existing customers, age groups, etc.), and sought out what kind of functionality you would want for a chat bot for each group and across sets of user groups. Personnel from Sony Bank and Fujitsu worked together and investigated these issues (Idea Creation). One theme was what tools would be used to build the service (web, messenger, native applications, etc.). When considering item identification in the user interface design and service implementation, designers from Fujitsu specializing in that field were also called in to engage in numerous discussions and research.

At the time, as an experiment, we used the co-creation site "HAB-YU" for discussion and examination. While a regular conference room might have been fine, and we were not doing any kind of comparative experiment, it was thought that the place of discussion yielded an effect and gave rise to clever ideas such as "the chat bot needs to be able to respond not just to standard Japanese but also to the Kansai dialect." We believe there are merits to having discussions in places like HAB-YU where the atmosphere that differs from the norm.

Repeatedly "Throwing Away While Creating"

After deciding the minimum necessary functions, the next step was development (Lean Startup). For our IT foundation, we used the cloud, our agile development tools included JIRA (ticket management), GitBucket

(source control), and Jenkins (automated building and testing), and we took advantage of SNS, etc., for communication. When Fujitsu had made a prototype, four to five people from both Sony Bank and Fujitsu participated in testing it out to discuss problems and improvements. The resulting ideas and requests were implemented in two to three weeks. That was the iterative flow (Service Implementation = PoC). A bit of an odd phrase would most accurately describe what this looked like at the time: "throwing away while creating."

When the stage was reached where it could be used, we approached the business division of Sony Bank and asked them to use it (Figure 1). This would determine if the users themselves could handle the processes of tuning the machine learning and editing scripts as described before, and also allowed us to check what needs the business division had (PoB). At the same time, we also visited Silicon Valley. Focusing on chat bots, we investigated the latest trends in AI and user interfaces to further our discussions.

Although little time had passed since the last time we had gathered information, it is important to always know what the most current situation looks like. By going into the field to investigate with a prototype that resembles what you hope to finally produce, the prototype can be improved and given greater depth. More recently, Sony Bank and Fujitsu were working in cooperation on the final steps toward launch during the first half of 2017.

General Customers

ExistingChat Gateway

ExistingChat Gateway

PartnerSite

CustomerSite

API Gateway

Speech Recognition Engine

FRAP* Chat

Speech Synthesis Engine

Script Editing Engine Machine Learning Engine

Bot

Finplex Robot Agent Platform

Customer/End User

4. API Gateway Function

3. Script Editing Function

1. Messenger Function

2. Synonym Editing Function

*short for Finplex Robot Agent Platform

Figure 1: The composition of the "chat bot" co-created by Sony Bank and Fujitsu


Yoshinobu Sawano　Manager, Fujitsu Laboratories of America

Connecting PoC to Real Services and BusinessesBreaking Away from Orders and Contractors

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Market analysis and test marketing are essential in developing new products and services. On a digital journey, we develop systems and services in response to them and then try to actually release them. By analyzing reactions and opinions we receive, we can add necessary functions and eliminate unnecessary ones. This is in the process of what is called PoC (Proof of Concept).

The necessity of this goes without saying. Even though an idea may seem excellent and destined for success, actually trying it out can reveal unexpected problems. Without doing this kind of check, there is a significant risk in developing full-fledged systems and services. Still, since the cost of developing operating systems and services has dramatically declined, it can seem only natural to try and make a system or service that goes straight into operation.

However, when Japanese put PoC into practice, it is not always easy to then take that and put into practical use as a service. I have frequently heard "it takes too much time and money for PoC" and "we did PoC, but the project ended there," and I have had similar experiences. So what obstacles lay in our way, and how do we surmount them?

─ Challenge #1 ─

POC Takes Time and Increases Expenses

As is well known, development volume (work hours) and cost are linked in system development in Japan, so there is a temptation to increase the amount of coding and draw out the process as long as possible. In this regard, it is clear that rigid budget enforcement and a waterfall model of development for the QCD framework are not common. In PoC, there is a focus on speed, and

it is necessary to get the review loop cycling quickly. To achieve that purpose, the parts that are to be newly created are reduced as much as possible and whatever can be used from open source or cloud services, etc., is put in place because it is important to minimize new development. At any rate, it is not reasonable to implement all the ideas from scratch, and though it is necessary to take the approach of starting small and raising the service to grow big, it can be hard to do.

─ Challenge #2 ─

Never Getting Past PoC

Even when PoC is implemented, there are many cases where it does not lead to development of full-scale systems and services. This is itself another intended use for PoC, so it cannot be called that significant of a problem. However, part of it is that within the constraints of some existing organizations the feedback obtained from users of the PoC cannot be handled, and the result is that commercialization can be judged as too difficult. That is to say that because which division of the ordering company is responsible for handling feedback or it cannot be decided whether the company placing the order or the contractor is responsible, there are cases where things just sort of get stuck in the air. It should be easy to imagine that when a company placing an order has an idea (request), traditional approaches where the contractor then implements it might not work out well.

Solutions

I work in R&D in Silicon Valley at Fujitsu Laboratories of America (hereafter, FLA), where I am engaged in the development of various new services, and there are


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things that I am keenly aware of on a daily basis. In the United States and Japan, there are big differences in the approaches that companies use in trying to create innovative services.

Many U.S. companies have fulltime human resources w ith in thei r compan ies that a l so col laborate with external communities and develop services independently. In contrast to this, at Japanese companies, aside from the basis of the relationship between the ordering company and the contractor, the employees and company have not moved away from a directly, mutually dependent relationship (of course, there are exceptions).

Take for example the process of report, communicate, discuss, and decide. This system is an important concept that acts as the base for how many Japanese companies organize communication, and Japanese companies based in Silicon Valley still often practice it. However, the lean style business creation process based on dialogue with the market is slowed down by this system, and the responsible team (person/people) loses its independence. A situation to the effect of "I have reported but not received a decision, so being late is unavoidable" arises.

In the OSS community for block chains where I serve as a board member, the mainstream technology and ideas change every few months. To handle this speed, it is essential to communicate daily, making full of use of things like SNS, etc. Since it is assumed that announcements and reporting will be handled via SNS, board members are always required check it. On the other hand, if there are no objections, it is standard that community members may independently proceed with gradual work on a project.

I think there is a lot that we can learn from these kinds of efforts. To put it succinctly, we can escape the relationship of ordering party and contractor. Specifically, a relationship is formed in an ICT partnership where fate is shared with pioneers of digital business. Additionally, it should be noted that the ordering party and contractor part of this may apply to cases of organizations within the same company as well as outside companies.

We have to address our in-house principles as well. If we try to complete projects using our own resources in areas where our company is less talented, the uncertainty of PoC increases along with the difficulty in execution. When a company is not good at something, it wastes a lot of time, and what should have been done from the beginning becomes inevitable. At FLA, our business creation projects specialize in the creation of core businesses, and in other incidental projects, we will optimize speed and cost by turning to our partners.

At FLA, we proactively pursue this approach, and as we involve human resources not just in Silicon Valley but from all over the world, we develop a lean business creation framework, evaluate it, and improve it. This know-how lives in the system of "Service Framework for Co-creation = Gathering of Informaiton, Idea Creation, and Lean Startup" (see Part 2-1). This framework, in addition to creating businesses, also focuses on the changing dynamism of organizational practices. To become a true partner to walk with on the digital journey, efforts that have begun with the organization of FLA to move out across the sea and seek to effect change in the way Fujitsu is on the whole.


Solutions & TechnologiesTechnology is an essential tool that we take with us on a digital journey.

If you know of it, about it, and can make use of it, then the choices available to you only become more numerous as you determine your path.

With that in mind, what new technologies and information is emerging? What do they enable us to achieve?

Here we will look at seven key technologies, including the cloud, AI, and the IoT, among others.

C O N T E N T S

3-1［Overview］Gearing Up for the Digital Journey:Developing a Broad and Deep Understanding of Technologies

3-2［Cloud Infrastructure］Foundations for Digital BusinessThe Next Generation of FUJITSU Cloud Service K5

3-3［Analytics］The Road to Data-driven ManagementThe Increasing Significance of Analytics

3-4［AI］Core Technologies of Digitization, AIUnderstanding the Whole Picture

3-5［IoT］From Sensors to IoT Platforms,Fujitsu's IoT Endeavors

3-6［AR/VR/MR］Significance & Impact of AR/VR/MR as Powerful Tools to Enhance the Customer Experience

3-7［Security］Risk-based Cybersecurity MeasuresDeveloping Technology for Mission Assurance and Business Continuity

3-8［API Management］Launchpad for Digital BusinessUnderstanding API Management

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PART 3


Solutions & Technologies O v e r v i e w

PART 3-1

Tomohiro Fukui　Manager, Technology Strategy O�ce, Service Technology Unit

Gearing Up for the Digital Journey:Developing a Broad and

Deep Understanding of Technologies

IDC coined the phrase "the third platform" to refer to the information environment formed by the four elements of cloud computing, mobile computing, big data, and social media. Gartner, Inc. refers to these same four elements as the "Nexus of Forces." They are also referred to by the acronym SMAC (social, mobile, analytics, and cloud). Label variants aside, the significance of these four elements is such that they warrant a special designation.

In short, these four elements are the source of furthering development in areas such as IoT, AI, robotics, 3D printing, etc., making them the driving force behind the "Fourth Industrial Revolution." As little as ten years ago, the ICT of digital technology had become positioned as a tool for streamlining and economizing labor, and has today become a driving force behind social, economic, and business innovation. It is also the reason why the "Journey of Digital Transformation" or "Digital Journey" discussed in Parts 1 and 2 is a trip we will all need to take.

With respect to this, we work to build an understanding of existing digital technologies as well as trends in

emerging ones, and carefully consider their applications in revolutionizing our business and formulating the new technologies we will be using in the future. These activities represent a critical mission for the CIO and IT department as those who put these technologies to practical use and are responsible for digital innovation. In this section, we will take a closer look at technologies such as cloud computing, AI, and IoT that are our essential expedition gear for our digital journey.

Understanding Emerging Important Digital Technologies

First, we start with which technologies are already out there and which could be further developed in the future. Since a comprehensive list of items would be far too lengthy to include, we have created a condensed list of what we consider to be the essentials, shown in Fig.1. Despite this abbreviated list, there remains a diverse range of important technologies relating to application development , user interfaces , and the autonomy/automation of things and ideas that are beyond the scope of this discussion. The seven technologies that will be

Fig.1: Here is an overview of various digital technologies. Those in red blocks will be explained in Part 3-2.

Application Development Next Generation Interfaces

Autonomy, Automation

Industry Applications

Next Generation Computing

Co-creative Approach

Agile Development, Model-based Development

DevOps, Virtual Container Systems

Displayless Computing

AR, VR, MR

AI (Artificial Intelligence)

Security

Internet of Things

Stream Computing

Wearable Computing

Smart Machine RoboticsElectronic Money, Micro-payments

Extreme Data

Next Generation Architecture

Quantum Computing

Blockchain

BRMS, RPAMicroservice Architecture

Open Source

WebAPI/API Management

Cloud Computing Analytics Data Lakes

Drones 3D Printers


PART 3-1

Solutions & Technologies Ove r v i ewO v e r v i e w

introduced here in Part 3 are marked in red, and should be understood to only represent a piece of the whole picture. We have purposely excluded certain things such as smart appliances, self-driving cars, as well as nanotechnology, etc.

As far as what technology should be adopted under what circumstances, the digital journey has no predetermined route. Of course, there are cases where the path may appear self-evident, such as adopting AI to automate forms of processing, but it remains important to keep an eye on how technologies interrelate and use trial and error to test how they might be utilized in combination with one another. It is necessary to try to understand diverse technologies that can be challenging to systematize by working to get a kind of bird’s-eye view of the situation.

R&D Efforts to Establish Core Technologies

Naturally, for companies like Fujitsu, thinking from a kind of big-picture perspective like this is a prominent theme. So while what we choose to emphasize may vary, we are engaged in a wide range of R&D and product/service development with the technologies listed in Fig. 1. Let’s briefly cover some of the technology that will not be discussed in Part 3-2 and the other parts following this one.

We’ll begin with a look at next-generation computing technology. The miniaturization of semiconductors has helped fuel exponential progress in technology, but limitations have started to become apparent. Still, neither the demand nor the quest for greater processing performance is likely to subside any time soon. In many cases, such as improving disaster recovery procedures, refining an investment portfolio, or increasing the efficiency of logistics, there remain numerous large-scale combinational optimization problems that are not fully handled by existing processors. As computer manufacturers, we are seeking a new breakthrough to address these circumstances.

One area that we are researching in order to achieve

these advances is quantum computing. However, because this type of computing utilizes physical phenomena that are difficult to control, it is challenging to reach a stage where it can be applied effectively to the various types of cases mentioned before. In order to further our research, Fujitsu has collaborated with the University of Toronto in Canada̶renowned for its advanced technological research̶and in October 2016, development of a new architecture that could compute combinational problems approximately 10,000 times faster than a standard computer was announced.

The trial model that was built and tested used 1,024 bits; however, for practical use, 100,000 to 1,000,000 bits will be necessary. We have plans to implement quantum computing in practical applications as soon as 2018, but there are major advantages to be found in implementing with existing semiconductor technology. For instance, we are developing parallelization technology based on ARM architecture that will be put into a processor for an exaFLOPS-grade supercomputer, exceeding our existing supercomputer, the K computer. Additionally,

Photo1: RoboPin developed by Fujitsu (not being marketed).


PART 3-1

Solutions & Technologies Ove r v i ew

we are creating a deep learning processor (this will be discussed further in the portion on AI).

"RoboPin" the New UI Robot

As for technology that intersects the point of contact between people and ICT in the physical world, we have been developing a robot. Dubbed "RoboPin," it works as a new kind of user interface that is an alternative to a display and keyboard or smartphone (Photo1).

Because it is meant to act as a user interface, it is not able to move around on its own, and is instead built with a focus on its ability to interact with people. Its design is reminiscent of a pin you might place on a map, and by moving its head and arms using six articulated joints, it is able to express emotions and give directions. A major feature of RoboPin is its six joints that can be used for a surprising variety of applications and expressions. Using them can give guidance to visitors in public places such as a shopping center, train station, or airport, while providing other information. In the field of nursing care, RoboPin is capable of watching over patients and holding a conversation.

Participating in Hyperledger to Advance Blockchain Technologies

Let's now touch on blockchains, which are currently poised as a very important technology. While blockchains are perhaps best known as the foundation for the virtual currency Bitcoin, their uses have expanded to include the logging and management of records and contracts. Diversification in the area of limiting usage to a particular user base, such as a consortium or private group, has also been progressing. Consensus algorithms for approving transactions have likewise seen marked improvements in performance.

In fact, a number of projects are progressing globally, including the open-source "Ethereum," which is a platform that can build distributed ledgers and smart contracts, and "Colored Coin" that allows for the trade of financial assets like real estate and securities, as

well as the issuing of an original currency for users. In the midst of these developments, Fujitsu has taken the approach of working with the "Hyperledger Project" hosted by The Linux Foundation. Although this is open-source blockchain technology, it is being put to use with a keen awareness of its applications in finance, IoT, businesses' supply chains, etc.

Fujitsu has taken part in the project as a premium member since its inception, and is especially committed to contributing in areas of safety, reliability, and usability. At the same time, using this as a base, we have added functionality that includes things like management of participating members and access control; in addition, we are developing a platform to make it usable for inter-enterprise transactions. This will presumably be used with consortium or private blockchains.

Of course, it cannot be emphasized enough that in all our efforts involving OSS, not just the Hyperledger Project, our interests amount to a great deal more than a passing phase. Since contributing to the Linux OS that suffered from reliability and stability issues early on, so that it could be used in mission critical situations, Fujitsu has been committed to a number of OSS projects. One example is our work with OpenStack that serves as a foundation software for IaaS. We are unique among Japanese companies in that we have joined community board members for the network-controlling "Neutron" and object store project "Swift" in working on enhancing functionality in areas like log and metric analyses.

Naturally, Fujitsu also develops its own original software in addition to taking part in OSS initiatives. Though today, in practice, it is difficult to disseminate software that is not in some way related to OSS. Due to these circumstances, in addition to making our in-house developed software open source, a key feature of Fujitsu’s software development strategy is contributing more OSS in the future. Through efforts such as these, we are certain that our digital journey will be directly connected to contributions to our users' companies well into the future.


Solutions & Technologies C l o u d I n f r a s t r u c t u r e

PART 3-2

Table 1: Main Services and Pricing for FUJITSU Cloud Service’s IaaS/PaaS

Type Service Summary Price (Reference)*

IaaS

ComputingTwo services for standard and SAP. Standard service offers 18 types of virtual servers ranging from a 1 virtual CPU, 512MB memory model to a 16 virtual CPU, 128GB memory model. The SAP service features three types of SAP-certified virtual servers.

P-1(1 virtual CPU, 0.5GB memory): ¥1.20/unit/hour

Dedicated Physical Server Services

Two services offered for dedicated physical servers or dedicated physical servers for SAP HANA. The dedicated physical server service provides physical servers and physical storage for each user. The dedicated physical server service for SAP HANA offers four types of physical servers for SAP-certified HANA application associates

Ded ica ted Phys i ca l Server (base) (14 cores×1 CPU, 32GB memory, 3 0 0 G B × 2 H D D ) : ¥261,713/unit/month

Storage Offers block storage, SSD storage, object storage, storage snapshot technology, etc. Block Storage (add-on): ¥0.022/GB/hour

Networking

Offers load balancer, DNS service, Global IP address offering, IPsec VPN, SSL-VPN (free), firewall (free), Internet-access service (free), etc. We also offer a network connection service between K5 regions for K5 and Fujitsu data center hosting environments and on-premises environments. A free menu is included depending on line speed.

Load Balancer (standard): ¥3.24/unit/hour

PaaS

CFPaaS architecture with OSS Cloud Foundry base. By selecting and combining various functionality and services provided from CF and other services, an information system can be created and implements quickly and at a low cost.

Buildpack:¥7.00/GB/hour

PFDevelopment and executable architecture for applications loosely coupled using API. Fujitsu develops and provides PF for companies mission-critical business systems, and uses development architecture with tested operations as a base.

Appl icat ion-DB(smal l scale): ¥98,000/month

SF

Foundation for automating system architecture to provide for continuous integration/delivery on IaaS. The greatest feature is that the infrastructure construction definitions (various defined configurations of multiple virtual servers and networks, software stack definitions, etc.) can be encoded to execute automatically.

Fixed Menu:¥70,000/month

API ManagementAPI integration platform that can manage and expose APIs over web services. Based on the Apigee API integration platform, which has a proven track record worldwide.

Basic Config. (standard: fixed menu 3M): ¥100,000/month

Database Services

Offers virtual servers with database functionality. Data synchronization between DBs, auto backup, etc. are available. For DB engines, in addition to PostgreSQL, Oracle DB (planned) is also available.

C-2 PostgreSQL(2 virtual CPUs, 4GB memory): ¥20.16/unit/hour

IoT Platform Architecture for storing and using data generated from various sensors and devices. Basic (economy): ¥50,000/month

Sharing Business Architecture Services

Architecture for providing services that allow the sharing of information on work force/capability, things, space (location), etc. between providers and buyers. Various available APIs for the developing and operating of applications for sharing services by business operators can be used with a metered rate (pay-as-you-go) format.

Basic Service: ¥10,000/month

*“Prices as of April 2017 in the East Japan Region.

Kiminori Yoshida　Director, Digital Technology Service Division, Service Technology Unit

Foundations for Digital BusinessThe Next Generation of

FUJITSU Cloud Service K5

The core of Fujitsu's digital business platform is our public cloud service FUJITSU Cloud Service K5. The name comes from the knowledge Fujitsu possesses from across five continents, which has gone into its development. It consists of various IaaS and PaaS that use the OSS (Open Source Software) OpenStack. Here we will dig into the latest information on K5, looking at the features of the services, the technology involved, and cover the reasons why certain technologies have been adopted. Further, we will cover the current

circumstances and future plans for K5 as it develops globally.

OpenStack has been adopted for K5 to virtualize computer resources such as CPU, memory, storage, etc., and to make them available as a virtual machine. There are numerous advantages to this. Since it is an OSS being developed by engineers globally, it embodies the most recent advancements in technology. At the same time, since OpenStack is now in use by many IT



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companies, its interoperability is quite high. Drawbacks of it being an OSS include potential issues with stability and reliability, but Fujitsu has been dedicated to improving the program, giving back to the OpenStack community. Consequently, OpenStack has reached a level where it can be used by corporations with few or no issues at all. So what services does K5 offer? Allow me to provide a brief explanation (Table 1).

Range of K5 Services

① ComputingComputing refers to virtual servers consisting of resources such as virtual CPUs, memory, system storage, networks, etc. Eighteen types of virtual servers are offered through K5 IaaS, ranging from the smallest model that has one virtual CPU and 512MB of memory to the highest-end model with 16 virtual CPUs and 128GB of memory. Virtual CPUs with a clock speed equivalent to 1.7 to 1.8GHz or equivalent to 2.6GHz are available. With 18 types of virtual servers and two types of virtual CPUs, there are 36 combinations available that can suit most needs.

This is a general-purpose virtual server, but since many companies also adopt dedicated virtual servers to run SAP ERP, we provide three server types for such purposes, suited to scale.

② Dedicated Physical Server ServiceDepending on the company, some may not wish to share a virtual server with others. Though it may raise costs, clients may prefer a physical server for use with the cloud. In K5, we can setup a physical server to meet those needs. In K5, physical servers are connected to other virtual servers over a network. This comfiguration is useful when for example a physical server is processing during its peak time, and capacity/speed can be increased by allocating part of the load to a virtual server.

We have expressed that virtual servers support SAP, but for our dedicated physical server services, the in-memory database SAP HANA is officially supported. We

offer four server types, ranging from 256GB of memory up to 2TB.

③ StorageStorage is largely divided into block storage and object storage. K5 offers both storage solutions. First, block storage is added to virtual servers for booting the OS of the virtual server and for additional storage. Storage snapshots are also used as a means of creating backups. For block storage, in addition to the more traditional HDDs, we have also begun offering high-speed SSDs.

With object storage, data is not stored as files or blocks, but is stored in units called objects. There is no hierarchical structure, and the information can be accessed using HTTP by K5-equipped virtual servers or by users. This method is generally effective for storing large amounts of data with few updates or revisions. Although it cannot be connected to a virtual server and used for system storage or a storage expansion, object storage is relatively inexpensive compared to block storage.

④ NetworkingK5's networking services include features comparable to those of other public cloud services, such as a load balancer, firewall, DNS, VPN connection, etc. Here I will describe two network services particulars to K5.

One is our private connection service that is a closed user group service connecting the K5 infrastructure with users' on-premises environment and hosting environment. Costs will be incurred based on the connection's line speed and connection point. However, a 10Mbps best-effort connection between K5 regions and a 100Mbps best-effort connection between K5 virtual server environments and the hosting environment of the Fujitsu Data Center are offered free of charge.

The other network service is our Internet-access service. Although K5-equipped systems are connected to the Internet, other IaaS often charge fees based on the amount of data traffic. K5's service is free regardless of the volume of traffic, and can be used without worrying



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Sharing Business ArchitectureDevelopment/execution ofapps for sharing businesses

Business SupportFunctionality supporting management ofcustomers/contracts & calculating fees

PFProven framework and execution

environment developedby Fujitsu for companies

Personium ServicePersonal Data Store using based

on the OSS Personium

Service Component Groups (partial selection)

InfrastructureOpenStack-based cloud infrastructure environment

Voice OperationSpeech recognition execution environment/

development kit

IoT PlatformData transmitting/receiving/

collecting using sensors and devices

Authentication ServiceSSO/biometricauthentication

CFCloud Foundry-based

development/executionenvironment

SFSystem configuring/software coding, assigning/reusing

API ManagementWeb API management/exposing/usage analysis

ApplicationDevelopment/Execution Layer

Infrastructure/Operations

Layer

Form ServiceDesign/creation

of PDF forms

Batch InfrastructureBatch job execution/

management

System Resources(virtual servers/storage/networking, etc.)

General-purpose Components (e-mail/CDN, etc.)

PaaS

IaaS

Fig. 1: K5 Service Stack

about a sudden surge in users.

Beginning use of IaaS as described above, as well as securing resources, deployment, and detailed settings are all accessible through a browser-based dedicated portal called the "Service Portal." The Fujitsu Service Portal is presently being updated, and we are planning to dramatically increase the service's levels of functionality and usability by adding services and functions that feature visual displays of usage statistics, etc.

Features of K5’s PaaS and Latest Info

Next we will take a look at PaaS. On the digital journey, there are many more opportunities to employ PaaS than IaaS. The development and execution of applications using PaaS in practice is described in 2-4. Here I will describe the foundation.

K5 PaaS consists of two layers (Fig.1). One is the PaaS used for the development/execution environment for Cloud Foundry and SoR systems. The other is the use of applications on that PaaS with API and PaaS groups (various service components).

① PaaS Development and Execution EnvironmentThere are three PaaS programs in the development/execution layer. First is the development/execution environment based on Cloud Foundry (CF). Cloud Foundry is an OSS PaaS used by many IT companies, including Pivotal and IBM.

Like those of other companies, Fujitsu’s K5 CF has added some functionality to Cloud Foundry. One such addition is a logging and monitoring service. The Cloud Foundry application log has no fixed-period access, and the log is deleted when the associated application is deleted. However, in the logs of applications used by companies, from the standpoint of operation verification and security, this is very important. To address this issue, K5's CF features new logging and monitoring functionality, and we have made it possible to use save, search/retrieve, and delete functions in the logs.

The second PaaS is called PF. It includes a Java application execution environment and allows for settings to the framework developed by Fujitsu to be made. The design and development environment of the applications deployed in PF can be incorporated into the Eclipse



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Fig.2: K5 Global Distribution

Finland Region 1

UK Region 1German Region 1

Spain Region

Asia Region (planning)

Australia Region (planning)

East Japan Region 1、East Japan Region 2 (1st half of 2017) North America Region (1st half of 2017)

West Japan Region 1West Japan Region 2

LegendIn OperationBeing ConstructedBeing Planned

OSS development environment by downloading a special plug-in from K5's portal site. Developed applications are deployed and executed in the K5 PF execution environment. The execution environment incorporates a database with operation verification and usage monitoring tools. It is deployed on IaaS as a virtual server group of web/AP/DB. Currently, we have made it possible to select from four different combinations to suit the system scale.

Lastly, various definitions encoded on virtual server environments deployed as IaaS are used for automation and are called SF. Various kinds of functionality are provided to offer continuous integration/delivery via IaaS. One feature of the K5 IaaS is that it can be used to build multiple virtual servers, implement the configurations for their OSs, middleware, networks,

firewalls, etc., and automatically implement them in the form of a software appliance called a workload package. SF provides the development and execution environment to operate these workload packages.

Developers can use a workload package that has been thoroughly tested in a development environment and grow their production environment through automation. Even if a failure occurs in the production environment due to a change in system configuration, the downtime of operations can be minimized by reloading the workload package that had been stable before.

Various PaaS Service Components

At Fujitsu, we offer service components capable of providing a variety of functionality on our PaaS.

A common question is "how are MetaArc and K5 different?" Allow me to briefly explain here. First of all, MetaArc is a collective term used to refer to the digital business platform of the various products and services provided by Fujitsu, (cloud, mobile, big data, IoT, AI services, etc.), and the integrated knowledge and know-how of Fujitsu SE.

We develop products and services for each technology component of MetaArc. For mobile we have the FUJITSU Cloud

Service MobileSUITE. For big data we work on FUJITSU Business Application Operational Data Management & Analytics. Our IoT offering is the FUJITSU Cloud Service K5 IoT Platform. And for AI we develop the FUJITSU Human Centric AI Zinrai.

However, FUJITSU Cloud Service K5 is a cloud service that acts as a layer of our IaaS/PaaS and provides a foundation for other services. It is one component of the whole that is MetaArc.

P o s i t i o n i n g o f K 5 i n M e t a A r c



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Naturally, these can be used with K5 as well. Here I will explain the "sharing business architecture." This service component is unique to the Fujitsu PaaS, and we are currently seeking a patent for it. Sharing business architecture is a PaaS offered to allow for the sharing of services such as human resources and capabilities, things, and space (locations), etc. for venture businesses and corporations. We offer essential and effective functionality for the development and operation of sharing services in the form of 120 types of APIs, and also equip an execution environment that includes a dedicated database.

Allow me to give an example. Say we have a group of people (users) who want to study English online, and suppose there is an English teacher (provider). The business operator offers a sharing service that allows for the lesson times to be adjusted to suit the circumstances of both parties, but building this service from the ground up takes time. The sharing business architecture we provide includes a collection of APIs necessary for a sharing business, such as information registration/searching/acquisition/deletion, registering/retrieval of reservation information, login authentication, billing information, etc. Of course, it is necessary to develop a

new process flow, screens, etc., but since Fujitsu offers a variety of templates, the amount of time required is shortened dramatically.

About Global Distribution

Finally, I would like to discuss the ongoing overseas development and distribution of K5. As of the end of April 2017, K5 is available in three regions domestically (East Japan, and West Japan×2) and four regions overseas (UK, Finland, Germany, Spain), where our IaaS/PaaS are operating. As of the first half of 2017, we have plans to open a second region in eastern Japan and another in North America. We are also planning to distribute K5 to Asia and Australia (Fig. 2).

In the preceding section, K5 has been explained. We are aware that in terms of functionality and level of service there are certain areas that do not exceed those of existing cloud services overseas. However, Fujitsu, as a cloud service provider from Japan and as a cloud service that Japanese companies can implement in their digital businesses globally, has every intention of expanding K5 day by day.


Solutions & Technologies A n a l y t i c s

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Youichi Kurachi　General Manager, Digital Transformation Business Group

The Road to Data-driven ManagementThe Increasing Significance of Analytics

In today's IoT era, various devices, such as smart devices, cameras, and sensors produce vast amounts of data. As the phrase "data-driven management" suggests, the ability to analyze and make use of all of this new data (in addition to existing business data) is decidedly important. So what do we need to do in order to put this big data to use? Here we will discuss the evolution of analytics, the construction of data lakes, and Fujitsu's own approach.

Evolution of Analytics

Generally speaking, data analysis offers insight into a situation where problems are not occurring. Analytics can also provide a visual representation of a problematic situation to better understand it. In the case of retailers going over sales trends and the transaction histories of their customers, or in the manufacturing industry when looking at quality data and shipment values, etc., statistical methods are used to get the most out of and check data.

But the analytics of today are not limited to this. They now include the following. In exploring the cause of an occurrence, diagnostic analytics are employed to make something that could not be observed before perceivable. We turn to predictive analytics to help us decide how we should proceed and to prescriptive analytics to tell us what to use. Conventional analysis is referred to as descriptive analytics.

To summarize: In descriptive analytics, the subject of the analysis is structured data that people are then responsible for making judgements about. In predictive analytics, unstructured big data, such as that collected by sensors, is used, and the relationships between

different factors of the data are extracted to build a model using machine learning. Using this model, we can make sample predictions about the future. Prescriptive analytics can provide information on how to operate in the future, (e.g., “since tomorrow is a midsummer's day, prepare for a 10% increase in beverage sales.”)

While the use of analytics is not simple or easy at this juncture, predictive analytics and prescriptive analytics used to "calculate the future" are becoming more generalized. This expansion of what analytics can do and observe is why data-driven management is crucial.

Data-driven Management & Data Lakes

At this point, data-driven management is essential, and our recommendation is to build a "data lake." A data lake is a system that accumulates and stores big data unitarily, and makes it possible to retrieve and analyze that data as need. It is "data storage for analytics" so to speak. The system takes in the water (data) from different streams and stores it neatly in a reservoir, which is then used as a supply for various purposes. The data warehouse (DWH) is a similar concept that applies to structured data. Data lakes cover unstructured data such as images, recordings, sensor data, etc. In this respect, they are mutually complementary.

There is no fixed method for building a data lake. ① Since it is a lake, the data is not pre-processed in any way for a specific purpose, and ② metadata management can be used to make the retrieval of necessary data easier to perform. If this can be achieved, then either an RDB or a file server can be used.

However, the general approach is to use Hadoop, which



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A n a l y t i c sA n a l y t i c s

Table 1: Main methods of analysis for demand forecasting

Method of Analysis OverviewRandom Walk The simplest method of getting a predictive value using the most recent actual value.

Multiple Regression Prediction using the correlation of factors (holidays, weather, etc.) and sales figures.

Poisson RegressionModel using a Poisson distribution for the error distribution in a multiple regression; particularly good for predictions involving low volumes of goods.

ARIMA Prediction from correlation between historical data points.

ARIMAX A method combining an ARIMA model and multiple regression.

Dynamic Linear ModelWhen data is added, the internal latent/potential state is updated and a prediction is made; handles dynamic changes extremely well.

Exponential Smoothing State Space

Makes predictions focused on trends and cycles.

Neural Network Prediction via mathematical model that imitates the human brain.

is software that handles big data processing. In addition to using Hadoop's HDFS (Hadoop Distributed File System) for file management, the managed files can also be extracted at high speeds using a parallel, distributed algorithm, processed, and also analyzed using MapReduce.

Speaking f iguratively, HDFS is a lake. In order to draw out particular waters, it is necessary to filter out the sediment, which is where MapReduce comes in. Specif ically, abnormal values and noise included in the data is removed, or the units and time stamps of different data can be adjusted to a format that can be analyzed. In so doing, visual analysis of the data using a general BI tool is also possible.

Notable Improvements in the Utility of Hadoop

However, the easily obtainable open source software version of Hadoop has several features that are difficult to use. Fujitsu has noted and has taken steps to solve these issues since Hadoop's early days through a variety of means. In order to show that Hadoop's practicality is now sufficient, here are two noteworthy improvements.

One of Hadoop's tasks is to take the accumulated data generated by various systems and transfer it to HDFS, but this is very time-consuming. This together with processing downloads from HDFS acted as a major bottleneck in operations. In response, Fujitsu developed a distributed file system that can access stored data through an ordinary interface, including data on HDFS (Fig.1). Since transmittal is no longer necessary, operation speed is improved greatly.

The second issue that we came across was that Hadoop's MapReduce processing had to be coded in Java. With

Distributed File System(HDFS)

Internet

SensorDevices

BusinessSystem

Interface for Normal File System(POSIX compliant) HDFS Interface

Hadoop System

Fig. 1: Hadoop with improved performance and operability


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Hadoop Streaming, other languages can be used, but there are other remaining restrictions. Fujitsu has developed a multi-file input/output technology called the Hadoop multiplexer. Using this, software written in R (programming language), etc., which supports machine learning, can also be operated on Hadoop. Of course, Fujitsu is not alone in having devised such measures. Within the trading area or ecosystem of Hadoop, problems are being resolved daily, and the software's convenience is improving.

The Race to Employ Analytics

Lastly, I would like to take a moment to address Fujitsu's approach to analytics. Without going into too great of detail, in predictive analytics we use random forests, etc. for machine learning tasks. Some of the various other methods of analysis we use include regression analysis, ARIMA models, clustering, etc. (Table 1). However, mastering these methods of analysis is still quite challenging. Simply pouring data into machine learning or analysis software will not produce precise or useful predictions.

Using a demand forecast as an example, since trends related to sale methods differ depending on store and product, it is known empirically that even if a certain analysis method is adopted uniformly, there will be no increase in precision. By combining data such as weather and temperature with the store's environment and number of customers, etc., practical results can eventually be obtained. Analytics requires trial and error.

At Fujitsu, in addition to accumulating this kind of know-how, we have been working on developing various solutions and services with the aforementioned data lakes at their core. One of them, our Operational Data Management & Analytics, uses Hadoop as its base, and uses data lakes and analytics, as well as integrated visualization technology, as a foundation for utilizing and analyzing data. However, there are many other solutions beyond those provided by Fujitsu. To anyone reading, I would encourage you to take advantage of them and try putting analytics into practice. The journey to data-driven management still has a long way to go and will not be completed overnight. The earlier you take initiative and engage with this technology the better.


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SearchMazes/Puzzles

Turing Software

HypertextGUI

Mouse

Expert Systems5th Gen Project (ICOT)

Research in Dialogue Systems (Eliza)

Big Data

Prevalence

AutomaticOperations

Image SearchSiri

Deep LearningCognitive (text)

IA:Intelligence Amplifier

AI:Artificial Intelligence

1950 1960 1980 2014

1st Wave 3rd Wave2nd Wave

Rule-based AI Data-based Learning (AI)Few developments due to rule

processing requirementsTechnology advances in learning from data

(Machine Learning, Deep Learning)

Knowledge

Broader rangeof applications

1st Gen AI

Age of Searching andDeductive Inference

2nd Gen AI

Age of KnowledgeAcquisition

3rd Gen AI

Age of Machine Learning

Fig.1: Evolution of AI

Kaoru Chujo　SVP, AI Services Business Unit

Tetsuro Takahashi　 Senior Researcher, Arti�cial Intell igence Laboratory

Core Technologies of Digitization, AIUnderstanding the Whole Picture

Until recently, the potential dangers of AI had always been the stuff of science fiction: people’s jobs stolen by machines or societies dominated by computers. However, now these seem like actual potential problems. If expressed more positively, there is an expectation that with AI we can do anything. However, as you are no doubt well aware, while AI can currently handle certain jobs, it would not be wise to take it too far.

The 1st and 2nd AI Booms

Let's take a little look at the history (Fig.1). In order to automate calculations that initially only humans could do, the machine called a computer was built. In the 1960s the first AI boom occurred, and the solving of puzzles and maze problems, as well as work on the inference and reasoning for proving mathematical theorems, was pursued. Development of machine translation had also already started by this time. However, computers were not powerful, and because they were also quite

expensive, the boom did not last for long.

The second AI boom came in the 1980s. With the spread of relatively inexpensive computers with high performance such as minicomputers and workstations, there were fresh opportunities. At that time, by inputting specialized knowledge and the logic of decision-making, the use of "expert systems" to solve complex problems was attempted. Various approaches were tested in a number of fields, such as in making diagnoses in medicine and loan decisions in the financial world.

However, the boom came to an end in the early 1990s. Even when storing a considerable amount of knowledge and decision logic, real-world problems proved far too complex for computers to solve. Because exceptions occurred frequently, it became clear that practical applications were somewhat limited. In addition, computers at the time were unable to keep up with processing needs of large amounts of data and decision



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In deep learning, feature extraction and learning are done together

Deep Learning

Training Data/Result

“Person”

Deep Learning

Feature Extraction & Learning Training Data/Result

“Person”

Input Image

Feature valuescreated manually

SVM or decision tree, etc.

Input Image Feature Extraction Learning

PastMachine Learning

Fig.2: Differences between deep learning and past machine learning

logic inputs, and it took many hours to get results. Once again, performance was a troublesome bottleneck.

Principles of Deep Learning

Now we arrive at the third AI boom going on today. The driving force behind it is a dramatic evolution in computer performance and functionality, along with the technology of deep learning frameworks (hereafter, DL). Thanks to the former, tens of millions of documents and data can be stored while maintaining their causal relationships and logical structures, and all of it can be searched through at near instantaneous speeds. A good example of this is IBM's Watson or any rule-based management system (RBMS), which automatically executes operations based on decisions.

The latter, DL, was developed from extensive studies of neural networks (NN) during the second AI boom. NNs are mathematical models based on the cerebral nervous system that put neurons into three layers: the input, hidden, and output layers. Omitting some details, the functioning of the neurons is tuned using a large amount of data (learning), and new data is classified according to how it relates to learned data (recognition) (Fig.2). An important source of the third AI boom’s inertia has been that large quantities of the data that has allowed DLs to learn has come mainly from the web.

This function of learning from data and classifying is a key point. As research has progressed, it has become clear that the ability to classify improves as layers and neurons increase. Moreover, the classification is not as simple as a straight line leading directly to a referent and creating a division (singular aspect). In order to successfully classify data with subtle differences and various factors, the line of reference (aspect) for a classification can be bent and made somewhat flexible through learning. And through multi-layering, it was discovered that there could be many of these pliable classification reference lines (aspects). It was proven that DL could be used even when there were a great deal of parameters, and the classification challenges were so complex as to seem contradictory from a logical standpoint.

Allow me to give an example. People can distinguish immediately between the faces of cats, dogs, and mice. But why? Naturally it is not because we infer logically (simply) that cats and dogs have different eye widths. Instead, I would like you to try and imagine that as a result of having seen numerous cats and dogs, there is a classifying space that consists of many vague or flexible reference faces in your mind. When looking at an image, it enters that classifying space and is instantly judged to be a cat. While it is not easy to try and explain why what you see is not a dog, there is a function or



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mechanism there that instantly recognizes the image as that of a cat.

Moreover, because DL can create a complex classifying space, there is no need for people to intervene to instruct it. A suitable classifying space can be created by learning from a large volume of data. The problem is that in DL that implements many neurons across multiple layers, the extensive number of calculations necessary for learning require an incredible amount of time. As for the number of neurons in the workstations of the 1990s, if I tell you that we somehow managed to make a three-layer neural network with ten units, you can likely deduce the vastness of the calculation process on your own. Even though we cannot say this problem is entirely gone today, through the progress made in cloud computing and parallel computing technology, the situation has at least become easier to manage.

What is the Google "cat paper"?

One achievement stemming from these results was Google's famous "cat paper" published in 2012. A DL learned from ten million photos extracted from YouTube and was able to recognize if a new image contained a cat. However, DL does not have a consciousness like that of humans, and since it also cannot speak, a little ingenuity is necessary for this process.

In order to explain what a thing is, first DL learns from a large number of images. If a large number of cat images are put into the DL, when monitoring the states of its many neurons, the specific neurons that respond to cat images can be located. Once that is known, if those neurons react strongly when inputting an unknown image, it can be judged that a cat is being displayed in the picture, or to put it another way, it can be thought that the DL is capable of image recognition.

This is called "unsupervised learning," and it is a major feature of DL. Though it is also a factor that leads to certain misconceptions along the lines of "the computer gained the ability to learn on its own and will surpass humankind." Further, Google has managed to work

backwards from the input side, working from the neurons reacting to cats, to succeed in generating an exceptionally cat-like image.

Alternatively, you can input the "images" and "name of the thing displayed" as a set for learning. It takes time and effort to prepare the set, but this way the DL, having learned the set, can output the "name of the thing displayed" when the input is an unknown image. This is "supervised learning," and when a DL is created for practical use in societies and businesses, for the time being, supervised machine learning is used.

One more thing I would like to make brief mention of is the AI-related technology being researched in affiliation with Google by DeepMind. They have developed a Go-playing program called AlphaGo. It performs a simulation of possible moves along several conditional branches and calculates the likelihood of winning for each. By repeating this process, it can choose the series of moves with the highest probability of winning. It uses the Monte Carlo tree search, which is a popular algorithm that has been adopted by many Go programs.

In AlphaGo, DL is used in order to improve the accuracy of the algorithm. For a DL to play against pro shogi players, who in a lifetime may at most play tens of thousands of games, 160,000 games needed to be studied for accurate pattern recognition to be realized. Further, by increasing its learning by playing many games against itself or other AIs, an AI became capable of beating a professional shogi player. Fifty years after the first AI boom, although Go was said at that time to be a game that computers could not defeat a human in, AI has now reached a level where humans can no longer win against it.

Previously, I provided a quick overview of the history of AI and introduced DL, which is currently a hot technology. I have a reason for explaining things in this way. DL is certainly an important and noteworthy technology, but when we talk about AI, I wanted it to be clear that the subject is not limited to DL. Additionally, the contents that DL learns cannot be read by humans,



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Table 1: A portion of AI-related APIs provided by major overseas IT companies; for example, Microsoft offers more than 20 APIs

Vendor API/Service Overview

IBM

Conversation Implements chat bots by providing information for the dialogue.

Natural Language Classifier Classifies text into pre-learned categories.

Message Sentiment When entering text, returns the presumed emotions of the writer.

Speech to Text Turns spoken sentences into lines of text.

Discovery Searches for specific information from news articles collected daily.

Google

Vision API Returns the names of objects in images.

Translate API Translates sentences into different languages.

Prediction API Learns and classifies based on uploaded data.

Speech API Uses voice entry and returns text data. Works with over 80 languages.

Natural Language API Performs analysis of entered text, such as extracting keywords and inferring emotions.

Microsoft

Recommendations Makes recommendations based on previously uploaded data.

Emotion API Recognizes faces in images and returns their emotions.

Computer Vision API Performs analysis such as tagging images and facial recognition.

Bing Spell Check API Checks spelling in sentences (English only).

Speaker Recognition API Analyzes voice data and identifies speakers.

and there is a problem in not being able to explain the reasoning for certain judgements. As mentioned in the example before, even if we as humans are able to judge that a cat is a cat by looking at it, we cannot explain the reason why so easily. DL has similar problems as well, being modeled on the human cerebral nervous system.

The research and development of knowledge bases has been ongoing for a long time, and more than anything else today their practical applications are spreading. Logical symbol processing is also important. Other specialized classifications, such as naive Bayes classifiers, support vector machine algorithms, and genetic algorithms, are also suitable methods for handling optimization problems. It is important for us to resolve problems by successfully combining these various technologies and techniques, which we recognize as the task we are now asked to pursue.

API Usage Promising for AI Application

Now with a sense of AI, and DL in particular, let's talk about how AI is actually used in system and service development. Understandably, fundamental research and development is left to specialized research institutes and IT companies, and companies should consider taking advantage of their achievements. From this standpoint, there are already many tools and solutions

available. Even if we only look at DL frameworks that are publically available as open source, there is Japan's preferred infrastructure and network Chainer, Google's TensorFlow, Microsoft's Cognitive Toolkit (formerly CNTK), and University of California, Berkeley BVLC's Caffe, among others.

There are even more application programming interface-based services (APIs) from cloud companies and ICT vendors that are easy to try out and use (Table 1).

Take Microsoft's Cognitive Services for example. The company offers more than 20 APIs; among them is an API that recognizes images and creates a corresponding thumbnail along with a description, an API for reading character data from images, an API that reads emotions from faces in photographs, an API that can convert both voice data and text, and an API for searching through academic literature and authors. In April 2017, they announced the Microsoft Translator Speech API for real-time translation. That same service has been implemented in Skype.

What about Google? They offer Vision API to detect and classify various objects in images, Translate API for language translation, and Natural Language API for extracting meaningful information from unstructured text, among others. Other companies who offer AI-



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related APIs include IBM, Amazon Web Services, and Salesforce.com.

In the US in particular, there are many specialized applications of AI solutions focusing on ventures, healthcare and manufacturing, finance, education, etc. Of course, it is not always possible to use English-based applications in Japanese. Nevertheless, in a service system aimed at cooperative creation, if we can meet and discuss research at the information gathering stage, that can play a big part in development. Testing to see what can be used and putting it to practical use is essential.

About Fujitsu’s “Zinrai”

Finally, I will discuss Fujitsu's AI solutions. Since the second AI boom, we have been continuously working on AI research and development, and in November 2015, we created an umbrella project for our practically minded research into topics like systematized neuroscience and deep learning-related technology development called Human Centric AI Zinrai. This unites various fields such as core technologies, image processing, emotion recognition, natural language processing, inferencing/planning, etc. We like to think of it as working from both the technology side and the applications side.

In November 2016, we announced multiple specific

services. One was Zinrai Deep Learning (ZinraiDL) that takes into consideration learning performance. A DL operations engine does generally not employ a standard CPU, and typically uses a GPU with many cores. However, regardless of whether a GPU or multiple GPUs are used, data sharing among GPUs often results in a bottleneck, and this prevents learning performance from improving.

ZinraiDL solves this problem with newly developed parallelization technology. While not perfectly linear, performance degradation is minimized by 14.7 times in a single GPU with 16 cores and by 27 times in one with 64 cores. As for the GPU, the aforementioned Caffe DL framework has been adopted onto the NVIDA TeslaP100. We began this form of service in April 2017 and plan to market it as a dedicated DL machine.

Developing of Dedicated Processors for DL

At the same time, we have also announced the development of a specialized DL processor, the DLU. Of course overseas, IBM and Google are also developing dedicated processors. The NVIDIA Tesla is an outstanding GPU originally made for exceptional image processing in video games, etc. Naturally, all this work comes from the idea that DLs need a dedicated processor. The DLU being developed by Fujitsu is based on the know-how polished in the creating of

By using our own parallelizationtechnology, deep learning processingwith multiple GPUs is accelerated

Based on external data such as LOD used asresponse knowledge, additional questionsand related information for digging deeper intocontent can be interwoven to generate answers

・ Extracts concept words from text groups and structuring by measuring similarities between each text・ Searches information using keywords based on structured data

Base APIs

Purpose-specific APIs

Sensing & Recognition Knowledge Processing Decision & Support

ImageRecognition

Speech/Text Conversion

EmotionRecognition

HandwritingRecognition

VoiceSynthesis

StateRecognition

Sight LineDetection

Text Analysis KnowledgeStructuring Classification

KnowledgeDiscovery

DecisionMaking

Inferencing Prediction Interaction/Dialogue Creation

Optimization

VideoRecognition

BehaviorRecognition

●Released April 2017

Semantic searchby specialized field

Company InformationSearching

DemandForecasting

Human ResourceMatching FAQ Search Chat Bot

DocumentTranslation

ConversationTranslation

TrafficImage Recognition Credit Scoring Delivery Planning Production &

Distribution Network

Fig.3: AI APIs to be released by Fujitsu starting April 2017



PART 3-4

A IA I

supercomputers with large-scale parallel processing and adopting that into architecture specialized for DLs. We go to great lengths with our power-saving design to also eliminate the problem of overheating. We plan to have the product ready in 2018.

Furthermore, the Fujitsu AI Solution Zinrai platform service of fers 18 APIs in 3 f ields : sensing and recognition, knowledge processing, and decision and support. 12 APIs with different purposes will be brought out in 2017. This April, we will release seven basic APIs for forecasting, searching and structuring of knowledge and information, handwritten character recognition, and voice synthesis, as well as two purpose-specific APIs for demand forecasting and semantic searching based on specialized fields. We plan to gradually expand from

there (Fig.3).

Explaining it this way, you may wonder "Why is Fujitsu releasing AI-related APIs now? If there are already services offered from overseas, why not use those?" These are reasonable questions. First of all, since we hope to responsibly put AI to practical use, it is necessary for Fujitsu to handle everything from the hardware foundation to the software itself. Secondly, learning requires the use of large amounts of data held by companies, and at the same time, there are many people awaiting Fujitsu's solution with regards to data rights and handling. We at Fujitsu believe that AI technology plays an important role for each part of digital businesses, and we are working to accelerate our efforts in AI companywide.


Solutions & Technologies I o T ( I n t e r n e t o f T h i n g s )

PART 3-5

Fig.1: IoT Usage Sectors/Classifications

Fig.2: Four Stages of IoT

Takaaki Suga　Deputy Head (Product and IoT businesses), Network Services Business Unit

From Sensors to IoT Platforms,Fujitsu's IoT Endeavors

How are companies today using the IoT? Fig.1 shows the classifications of the new projects Fujitsu has implemented since January 2016 where it was a factor. The information-gathering stage (where information is gathered as to how IoT might be used) now remains at 10%. Considering that in 2015 the same classification was at over 50%, it seems apparent that company efforts are moving along at a rapid pace.

However, there is still a long way to go. The digital journey as it concerns the IoT can be broken down into the four stages shown in Fig.2. As you can tell from looking at Fig. 1, many companies presently remain at Stage 1. There seem to be three main reasons for this. ①The return on investment is unclear, ② it is difficult to see how to proceed from Stage 2 onward, and ③ many companies are unfamiliar with how to utilize know-how gained from prior work to advance new knowledge through the use of digital technology. In many cases, another likely reason is that the business division in charge of products and the IT division in charge of IT do not have a close, cooperative relationship.

Through Fujitsu's service system intended for joint development, we can support companies as they proceed from stage to stage. To that end, I would like to describe here a part of the knowledge and

know-how accumulated by Fujitsu pertaining to the IoT.

Structure of IoT Systems

Let's begin with an overview of the IoT system as a whole (Fig.3). Its components cover an extremely broad range. Just the major components include sensor devices, networks, and clouds. It tends to be overlooked, but based on our experience, connections to and cooperation with existing and core systems are exceptionally important. For instance, when creating an application to

Information Gathering Stage 10%

Manufacturing Innovations11%

Operation Monitoring/Maintenance 15%

Worker Management26%

Consumer Services 14%

Vehicle/Goods Management 9%

Data Analysis Services9%

Maintenance WorkOptimization 5%

Other 2%

● In order to win out against competition, progressing to a higher stage is necessary● We need to prepare for the rapid onset of industry-changing innovation

Optimization ofexisting business

Stage1Product line visualization

of worker safetymanagement, etc.

New products,services

Stage2Sale of Product Services

Holds more data

Open-close strategy

Businessplatform

Stage3Open the data utilization

infrastructure, and make itthe de facto standard Create something

not yet thought ofwith an entirelynew businessperspective

Stage4？

Industry-changingInnovation



PART 3-5

I o T ( I n t e r n e t o f T h i n g s )

Cloud

Network

IoT Platform

SensorDevices

Gateway

Short-range Wireless/Wi-Fi/Cable LAN

Applications

Mobile/Internet/Dedicated Line

LPWA

Existing & core systems for inventory, human resources, customer management, etc.

Sensors EmbeddedDevices Smart Devices

manage someone's working conditions through a wearable device that detects a person's vitals and amount of physical work, the service cannot be established without a link to data in the personnel management system. In the following, we will focus on the three fields of sensor devices, networks, and IoT platforms (data utilization infrastructures).

Sensor Devices

In tackling the IoT, one of the first things to be examined is sensor devices used for collecting data. At present, there are a wide variety of these items, and moreover, rapid advancements are being made in the area (Table 1). There are also many things that need to be considered such as size, power consumption, and durability, though it can be difficult to recognize trends; however, at Fujitsu our research places an emphasis on categorizing sensors, and continues to focus on specifications, principles, and possible applications.

While the measurement subject, accuracy, format, price, environmental conditions, and lifespan are important when considering what technology to adopt, they are not all that is taken into consideration. How the sensors are to be installed and the way each sensor is connected are also important. Seldom can sufficient information be obtained using the data from only one sensor, and usually circumstances cannot be determined without combined data from multiple sensors.

An algorithm to convert sensor data into a form that makes it easy to process is also required. An example of when you might collect data on a person’s movements could be to judge whether or not a person had intentionally lied down. Using data from multiple sensors it can be determined whether an accident happened, and it can be detected if the person collapsed as a result. Since this type of algorithm takes more time and effort than one might expect, Fujitsu has put its

sensor data analysis know-how into an algorithm that comprehensively analyzes what is already available built into mobile phones and smart devices, called FUJITSU IoT Solution UBIQUITOUSWARE.

Device Networks

In the IoT, the connection between devices is also important. While there are also wired connections, let us focus on wireless technology here. More often than cases where devices and the data center are directly connected, in reality there are many other forms by which the communication of devices comes together and is enabled by a parent device; thus, here a device connection to a parent device is assumed. First, with gateways such as factory equipment monitoring or on-board devices for cars or construction machinery, etc., communication from what are known as rich devices is bidirectional and large in volume, and is generally compatible with LTE/3G mobile phone networks.

However, if the device installation conditions have to be strictly trimmed, LTE/3G is excessive both in terms of power consumption and cost. These strict conditions are one of the central battlefields in IoT technology, and various wireless technologies are arising in response. Of particular note is the new communication technology tailored to the IoT known as LPWA (Low Power, Wide Area). As the name implies, power consumption is low, while the range of communication remains broad.

Fig.3: Elements of the IoT System



PART 3-5

Device Type Application Example

Installation Environment/Usage

Principle Power Use, Size, Cost

Wireless Module & IF

Environment Sensor (Temperature, Humidity)

A/C control at factory & visualization (power reduction), incl. data center

Install inside where measurements are wanted

Temperature change of band gap voltage, detection of capacitance from humidity changes

・ μWs・ mm2

・ 100s of yen

I2C*1, SPI*2

Pressure Sensor Production management for agriculture (used with temperature, humidity), TPMS*3

Environmental data measurement in facilities, on farm work sites; mounted on tire valve

Pressure changes detected by electric resistance change due to piezoresistive effect*4

・ 10μW・ mm2・ 100s of yen

I2C, SPI

Water Level Sensor Watching the water level of a water-purification tank, river

In a manhole, on a river, in a purification tank

Water pressure detected using piezoresistive gauge, and detecting reflection time from water's surface with ultrasound, etc.

・ 10s of MW~1W・ cms×10s of cms・ ~10,000s of yen

Analog Voltage

Dust/Dirt Sensor Visualization of air pollution

Set up in a living room or office

Amount of light scattered by pollutants

・100mW measurement・cm2

・1000s of yen

Analog Voltage

Air Volume/Flow Rate Sensor

Energy saving data center, etc. by sensing air flow, factory process management

Installed in a place where there is a flow of gas and/or liquid

Temperature distribution around heater changes with the flow of air detected as electromotive force difference of thermopile*5, or by measuring the rotation speed of the propeller

・ 10s~100s of mW・ cms×10s of cm・ for flowmeter, 10,000s of yen

I2C, Analog Voltage

Inertial Force Sensor (gyro, acceleration, angle, vibration)

Smartphone, robot control

Adjusting screen orientation, angle & vibration of game controller, camera shake correction, posture detection

Detects angular velocity from Coriolis force acting on vibrating object

(Acceleration) ・100s of μW, 2mm2

(Gyro) ・mWs, mm2

・ 100s of yen

I2C, SPI, Analog Voltage

Impact Sensor Sporting goods (Reebok headgear)

Built into helmet/headgear for football, etc. to measure extent of effects on the head

Using charge generated in proportion to acceleration due to bombardment of Piezoelectric ceramics

・ 1cm2

・ 100s of yenAnalog Voltage

Pulse Sensor Understanding a person’s condition

Wrist-watch type Using the fact that the amount of absorbed reflected light changes with the volume of blood vessels

・ 100s of μW・ 3mm2

・ 100s of yen

I2C

Light Sensor (illumination, infrared, RGB, proximity)

Smartphone, automatic doors, lighting equipment

Adjust according to brightness, open/close door based on infrared changes

Using photodiodes to detect amount of light, radiation of extracted light

・ 100s of μW・ (light) 2mm2, 100s of

yen, (infrared) 10mm2, 1000s of yen

I2C, Analog Voltage

*1: I2C (Inter-Integrated Circuit): Philips' system of serial communication with offered peripheral devices*2: SPI (Serial Peripheral Interface): bus to connect devices used inside a computer*3: TPMS: Tire Pressure Monitoring System*4: Piezoresistance Effect: phenomenon where electrical resistivity changes when mechanical strain is applied*5: Thermopile: electronic device for converting thermal energy into electrical energy

Although SIGFOX, a representative LPWA technology, has a notably low transfer speed of 100bps, the range is exceptionally broad at 50km with good visibility, and its power consumption is also low. For example, utility fee meters for water, gas, etc. without power supply facilities have trouble when connecting with a network. LPWA can handle this as its battery life is from several to over ten years.

So what do we choose from among the various LPWAs? Overall there are both positives and negatives, and

there is no de facto option such as Wi-Fi for wireless LAN. Therefore, for the moment the method needs to be selected to suit the application. Fujitsu also is constantly watching technology trends, and at sites where our technology is to be used, we conduct testing and verify the connection to the Fujitsu cloud service.

IoT Platforms

Next , I will discuss IoT platforms . Because the applications, users, processes, etc. with traditional

Table 1: Application by Sensor Type (in the table, items with a green background are mainly by the sensor, and blue background items are operations built-in on smart devices)



PART 3-5

I o T ( I n t e r n e t o f T h i n g s )

Fig. 4: Necessities of an IoT Platform

App

Dept. A

App

Dept. B

API

API

IoT Platform

IoT App/Analysis Infrastructure

IoT Data Utilization Infrastructure

IoT Device Management

systems are clearly defined, requirements for the platform are easily determined. In contrast, with IoT systems, since it is difficult to set requirements in order to digitize conditions such as people, things, environment, etc., the ability to make requirement changes is instead a prerequisite.

Changes in data type and the amount of data also need to be considered. Initially, let's assume that an IoT system has been built for the purposes of alive monitoring equipment remotely. Typical data normally only needs to be acquired at intervals, but when signs of failure start to appear, data needs to be acquired in a way that allows the system to monitor conditions more closely. Since the types of devices and sensors to be monitored change daily, the types of devices, data size, and data type, as well as the tools for its analysis, will also change. In the future, IoT data will not be analyzed simply by one department or company, but it is expected that multiple departments and supply chains constituting multiple companies will share data. Appropriate data management, including security, is necessary. These are the reasons that IoT platforms are required (Fig.4).

Typical functions include the following three categories: ① IoT device management, ② IoT data utilization infrastructure, ③ IoT application/analysis infrastructure. For ① , many things depend on sensors and IoT devices, and ③ is not limited to IoT-data analysis and visualization tools useful for a wide-range of applications are commercialized. For ① and ③, the best method is to select the most optimal items to suit requirements.

On the other hand, the IoT data utilization infrastructure of ② is desirable for use as a common platform. This is because even if requirements change, the functionality of the data utilization infrastructure is universal. As for the actual IoT data utilization infrastructure, from around 2015, IBM, Amazon, and Microsoft started offering cloud-based services, and Fujitsu also released its FUJITSU Cloud Service K5 IoT Platform in 2015.

Functionality that is expected of an IoT data utilization infrastructure includes ① support for the standard IoT

protocols HTTP (REST)/S & MQTT/S, ② NoSQL-DB functionality for data storage, ③ binary data storage and reference functions, and ④ providing of a service portal/management API that has settings for using data.

To elaborate a little, for ① it is important to be able to use a common data models independent of protocols. For example, data from a sensor device is received using MQTT, and then accessed from an application using REST. With ②, No-SQL is suitable because information from various sensors can be added/changed later according to project developments, and it can also read JSON format messages and support query and event processing. For ③ , binary data such as sensor data, image data, etc. is accumulated, and it is indispensable in responding to reference needs.

K5 IoT Platform

The K5 IoT Platform, in addition to the four standard functions mentioned already, comes available with several additional functions. One is that for each resource used for storing data, access control is possible. This allows for secure data sharing between multiple organizations and companies. Furthermore, multiple rules can be set for one resource, increasing flexibility. For instance, for a resource that stores data from a certain device, through certain departments abilities to read and write, the rules related to things like reading



PART 3-5

the data can be set for different departments.

Here I would l ike to touch on the activit ies of organizations innovating in manufacturing in the IVI (Industrial Value Chain Initiative) consisting mainly of those in various manufacturing industries and IT vendors. Fujitsu is participating in a demonstration project of inter-company cooperation as an IVI working group activity, where the product information of the companies making up the supply chain is shared, constructing a system that can respond to sudden changes in plan or any trouble in a timely manner. Currently, smooth data sharing has been achieved via data access control.

The second additional function is the DRC (Dynamic Resource Controller) that allows for the dynamic balancing of the data load between the edge and the cloud for processing. While it is normal to send all the data to the cloud for processing, this requires a great deal of network and cloud resources, and Fujitsu does not find it to be cost effective. However, if an abnormality is detected, all data is sent to the cloud for detailed analysis. Depending on the situation (according to the settings), data processing is best when dynamically allocated.

In this case, since data is distributed to the edge and the cloud, management of data storage locations is also important. By having the data management functionality of the DRC, the data storage location information for both the edge and the cloud are registered, and as necessary, in response to a query from an application on the edge or cloud side, the data storage location is transmitted, and it is possible to gather the necessary data. A test bed for a large-scale IoT system with DRC was chosen for a grant from the National Institute of Information and Communications Technology (NICT) for IoT test bed projects and regional data center projects, and distributed computing management and distributed data management functionality were offered free of charge in across a large area. Presently, we are proceeding with an automotive-related demonstration in cooperation with The University of Tokyo and Hokkaido University.

Activities at the Industrial Internet Consortium

Needless to say, Fujitsu works in cooperation with corporations and other IT vendors, while also emphasizing the formation of an ecosystem. One instance of this was in March 2014 at the IIC (Industrial Internet Consortium) established by GE, Intel, Cisco, IBM, AT&T, etc. Fujitsu participated from the time the group was organized, and became a member of the steering committee (Fujitsu was the only Japanese company in this role).

The IIC stated as a goal the creation of real-world standards rather than universal standardization. Based on open technology, The Industrial Internet Reference Architecture (IIRA) was formulated, and a test bed was co-developed to demonstrate it, gaining approval from the IIC. As of January 2017, with the IIC consisting of more than 270 member companies, the approved test bed is growing close to defining real-world standards.

Taking a look at Fujitsu's efforts, we served as co-leader of the security working group and were responsible for writing related documents. Additionally, at the Yamanashi Plant of Fujitsu I-Network Systems, we planned a project that tackles visualization of product lines and applied it in a test bed in collaboration with Cisco. It received approval in 2015. In the IIRA, the IoT systems are divided into three tiers: Edge, Platform, and Enterprise. In each tier there are preferable functions, and there are interface functions shown between tiers. Fujitsu examined the system used for manufacturing sites, and adopted it at the Yamanashi Plant.

Earlier in this section, each of the technologies in the IoT data utilization infrastructure, IoT stages, sensor devices, and networks were described, along with participation in the IIC. In order for companies to press ahead in the harsh business environment, transitioning to more advanced IoT stages is a key point. In order to provide support for taking the necessary steps, Fujitsu is furthering and strengthening its R&D related to the IoT.


Solutions & Technologies A R / V R / M R

PART 3-6

Hideki Hara　Head of Digitalware Development Division, Middleware Business Unit

Significance & Impact of AR/VR/MR as Powerful Tools to Enhance

the Customer Experience

What do you think of when you hear AR (augmented reality) or VR (virtual reality)? General comments tend to be along the lines of "VR can be used for games and for simulating travel experiences," and "I think AR used to be popular but I've not heard the term lately." When compared with the applications for things like the IoT, AI, etc. in ICTs directly connected to business, for consumers there is no doubt a stronger impression of these in relation to entertainment purposes. And when compared with the VR headset devices we are seeing more of, does AR not seem unworthy of our attention these days?

Really, it is. One important part of digital business is improving the value of the customer experience, and customer engagement can be strengthened through these, as AR/VR excel in appealing to the five senses. Although this may seem a little exaggerated, I think that this concept should not be ignored in progressing on the digital journey, and rather it is an element of IT that should be aggressively incorporated. So when planning was done for the document you are reading now, I requested that we "definitely have pages explaining AR/VR." The fruits of my request are this article, and I hope you will accompany me as I delve deeper into this topic.

Notable Improvements in Recognition Accuracy & Realism

What sort of applications does AR have? One is sightseeing. With the 2020 Olympics to be held in Tokyo, there is no doubt that having tourist information

available in several languages such as English, Chinese, Korean, etc. will provide greater service to visitors. However, physical media with multiple languages require enormous expense to support, and with signs there is only so much available space. AR is useful in these sorts of cases.

A tourist can just hold a smartphone up to a guide sign, the camera can recognize the characters and images on the sign, and then the smartphone can translate it into the appropriate language based on its own settings. If you wear “smart glasses,” it can be even more convenient. Whatever the expenses for application development and distribution are, the stress felt by visitors to Japan can be greatly reduced, and even more importantly, people's impressions of Japan can be greatly improved (Fig.1).

What I hope you take from this example is that the situation is not as simple as "AR = augmented reality," and that it can also mean "complementary reality." Since it is an accessible example, I used sightseeing, but when thinking how to supplement or complement reality, there are various applications that can also be considered for workplaces. One such application that Fujitsu and many

？！

Fig.1: An example of AR. An English translation is displayed superimposed over a sign at Mt. Hakodate. photo by Hiro1775/Prykhodov/Getty Images



PART 3-6

A R / V R / M RA R / V R / M R

Table 1: Means of object and location/position recognition in AR

Image Recognition (using camera device)

Marker TypeBarcode, QR Code, AR Marker, etc.

Although recognition accuracy is high and the range is far, placement takes effort.

Markerless TypeObject Recognition, Character Recognition

Although easy to place, because of a strong dependence on the environment, such as changes in brightness, recognition accuracy is low and the range is short.

Location Information Recognition

GPS Type GPS Sensor, etc.There is no need to hold a smartphone over the target, but recognition accuracy is low over tens of meters.

Non-GPS Type (indoor location detection)

Wi-Fi Sensor, Bluetooth, etc.Although positioning can be detected indoors, in addition to the trouble of installing Wi-Fi equipment, recognition accuracy over several meters is low.

others are working on is facility maintenance. Looking at equipment through a head mounted display (HMD), or by pointing the camera on a tablet, the procedure for maintenance work can be understood, and it is also possible to have sensor information in an overlay. Experts can issue instructions from other locations as well, which leads to a reduction in errors.

Alternatively, companies can provide office guidance to new hires and foreigners; for example, teaching everyone one at a time how to use the copy machines is a waste of time and can be avoided. If AR support can be provided, then stress can be reduced, and learning can be sped up. Similarly, in retail stores and restaurants, it is easy to imagine ways that customer experiences could be improved using smart devices and AR as well.

Moreover, these were just a few instances I could think of. If you research broadly and study things like information gathering and idea formation as a part of the digital journey, there is a high probability that applications not previously considered will emerge. These can create value for the customer experience, which in turn will lead to a competitive advantage. That is why I want you to understand the backbone of the latest in AR and VR.

Expanding Applications of AR to Guiding, Education, etc.

Here I will discuss AR technology. With AR technology, as we take in real-world information through our senses such as vision, elements like audio and video processed by a computer are overlaid and displayed on top (a

superimposed display). The amount and quality of information typically obtained by humans is expanded through the superimposed display. Of course this is not new technology, and one of its original iterations was "computer vision" that developed over twenty years ago. In short, this technology extracted and recognized the outlines of objects in a camera's image, characteristic points, etc.

About twenty years ago, a high-end workstation was able to recognize the letters and numbers of a car's license plate, but what we are capable of now has changed completely. With today's smartphones , AR image processing can be done in real time at 20fps (frames per second), and AR games like Pokémon GO released in summer of 2016 are also cropping up.

Former diff iculties with accurate and real time recognition of objects are also improving rapidly. If connected to the cloud, the necessary resources for recognition can be accessed, and if using a machine learning model that has had learning, even smartphone processors can perform recognition in a short time with high accuracy. In addition to camera recognition, markers and location information can also be used (Table 1). For facility maintenance, etc. there are methods to put markers that can be read on equipment, and by using location information, the need to read with the camera can be eliminated. In this area, the point is that methods suited to each usage are becoming available. The remaining major challenge is reducing the size and weight of devices as well as addressing the matter of battery life. These technologies are evolving daily, and it is important to keep an eye on the situation.


Solutions & Technologies A R / V R / M R

PART 3-6

VR for Training Simulations

VR using an immersive head mounted display (HMD) can project realistic images of virtual spaces. HMDs have an acceleration sensor and gyro sensor, and detect the movement of the human head to move, rotate, scale, and draw the virtual space. When you turn your head to the right, the rotation alone will cause the virtual space to be drawn and displayed over the opposing left side. Even without this explanation, if you have experienced it, you were doubtlessly surprised by how real it felt. While you may not physically be able to go to many places, this technology can give you the feeling of venturing into space, to a tourist destination, or into a realm that exists solely in the imagination.

Hardware advances have greatly contributed to VR and AR. In the last two to three years, GPU rendering performance has evolved remarkably; for example, using NVIDIA's GTX1080, 4k+ resolutions can be displayed at a high framerate of over 40fps. As more things become possible, some companies are using VR for various practical applications. At the factory for a bottler of drinking water, a large number of part-timers are recruited during the summer when demand is particularly high. VR is used for their training. Disassembly, cleaning, and installation of lines is simulated, and the learning period for the job has reportedly been shortened from two months to two weeks. The use of this simulation training for workers on an assembly line is also used in automobile factories.

Can you imagine what this means? Though there are simulators for passenger aircraft that cost billions of yen,

one of the significant features of VR is that it is easy to use anywhere. It is by no means limited to entertainment applications, and depending on the ideas people come up with, it will spread out into many other areas.

Is MR the New Favorite?

Lastly we come to MR. MR stands for mixed reality and blends VR and AR together. Recently, Microsoft has released the HoloLens. The company describes it as a "self-contained, holographic computer, enabling you to engage with your digital content and interact with holograms in the world around you."

It may seem a bit confusing, but it is technology that displays something from the virtual world in the real world and is a device that looks like heavy glasses.

For example, as a service provided by furniture makers, the customer can be in his/her own living room when this is installed and see the furniture as if it were there. Using hand gestures the furniture holograms can be moved, but if one runs up against a wall or furniture already in the living room, it will not move any further. This may be a simplistic example, but it can still be said to have made something new possible.

In conclusion, I would like to once again emphasize that VR/AR/MR will be the next generation of human-machine interface connected directly to the customer experience. Considering that full-fledged application development has only just begun, I am convinced there will be no one not paying attention to and invested in this moving forward.



PART 3-7

S e c u r i t y

Risk-based Cybersecurity MeasuresDeveloping Technology for Mission Assurance and Business Continuity

The world 's f i r s t t h reat to computer security was discovered in 1945 when Grace Hopper of the US Navy found the first bug, a moth , in a computer. Over 40 years later in 1986, the first computer v irus "Bra in" was found. Since that time, over the last 30 years, the threats have continued to grow and the methods of incursion have steadily advanced. These threats have reached a level where they can affect the state of a nation.

Specific Measures Uncertain as Incidents Increase in Scale

Of course, security measures, tools, legislation, and guidelines have also been developed in response. However, attackers with a clear intention need to be responded to with advanced tactics. While there are some cases where the country will provide funding, security incidents are becoming larger in scale, and the reality is that they can deal a serious blow to a company. Security risks are decidedly business risks, and in fact, the world’s most highly valued private company Uber has been proactively hiring hackers since 2015 to work on eliminating the risk of automobile hacking.

However, for many companies , it is a lso hard to understand exactly how far to go and what countermeasures to put in place. Naturally, measures such as next-generation firewalls (FW) and intrusion detection systems (IDS/IPS) must be installed to combat external threats. Still, what products from which security companies to adopt is not easily determined.

First, a company must develop its own security policy, and then introduce measures accordingly in order to operate securely.

Even in so doing , the possibi l ity of a secur ity breach cannot be ruled out. No security measures guarantee 100% safety. In that sense, not only are perimeter defenses important, but internal network countermeasures need to be given attention in case outer walls are breached. These measures need to allow for quick notification and understanding of security breaches, minimization of damage, and speedy restoration of systems. Fujitsu offers integration services pertaining to security, and here we will focus particularly on solutions meant to minimize damage after an intrusion.

Mission Assurance and Business Continuity as a Framework for Security Measures

The thinking behind cybersecurity frameworks today is grounded in Mission Assurance (MA) and Business Continuity (BC). The "9/11 Commission Report" released by the U.S. Department of Defense (DOD) in 2012 discussed the realities of asymmetric threats.

A framework consists of four pillars that strengthen the

Framework Summary

Pillar 1 Identify and Prioritize Critical Missions, Functions, and Supporting Assets

Pillar 2 Develop and Implement a Comprehensive and Integrated Mission Assurance Risk Management Framework

Pillar 3 Use Risk-Informed Decision Making to Optimize Risk Management Solutions

Pillar 4 Partnering to Reduce Risk – A Shared Responsibility

Table1: Taken from "Mission Assurance Strategy" released April 2012 by the Deputy Secretary of Defense

Taisyu Ota　Evangelist, Cyber Security Business Strategy Unit

Sigehisa Ichikawa　 Manager, Cyber Security Business Strategy Unit



PART 3-7

S e c u r i t yS e c u r i t y

Table 2: Behavioral Phases of Attackers Fig.1: Conceptual diagram of "Attacker Behavioral Transition Model" focused on the process of actions taken by attackers

Number Behavioral Phase

P1Exploiting software vulnerabilities, attempting to download and install malware

P2Activities exploring the network environment, and conf irming g lobal IP addresses, searching for neighboring terminals, etc.

P3Infecting by copying malware to vulnerable terminals and executing it remotely

P4Downloading executable files and adding functionality through malware or tools

P5Searching for connectable C&C servers for remote operation

P6Remote operation through C&C communication, and confirming continued presence of infected terminals

P7Collecting and extracting confidential information from invaded organization, etc.

P8Participating in aggressive behavior acting as a bot for performing DDoS attacks, etc.

Intrusion Search Infection/Intrusion

DownloadExecutableFile

C&CSearch

C&CCommunication

UploadingExploitativeInformation

Attack/AggressiveActions

P1

P4

P8

P5

P6

P7

P2 P3

resilience of an enterprise’s key capabilities, assets, and processes (personnel, equipment, facilities, networks, information systems, infrastructure, and supply chains, etc.) even when unexpected things happen (Table 1).

Of these, readers will be familiar with "business continuity." However, I would like to emphasize that Business Continuity Management (BCM) / Business Continuity Planning (BCP) BCP/BCM should include security measures to for natural disasters and terrorism as well.

This framework is based on an OODA loop as well as a PDCA cycle. Since the OODA loop is discussed in 2-1, it will not be covered in detail here. However, the reason it is part of the foundation of this framework is because the "observe" aspect of the decision cycle for gathering information is essential for security.

For MA to carry out minimum necessary business operations no matter what happens, the following processes must be implemented:① Means for finding intrusions as early as possible

⇒ technology to detect cyber attacks② Stopping intruding malware quickly ⇒ technology to block intrusions③ Prompt clarification of the damage situation caused ⇒ expedient forensics

④ Taking appropriate actions in response to attacks and damage

⇒ Cyber Threat Intelligence (CTI)

Many existing security tools detect malware at the boundary between the Internet and the corporate network as well as at the end point (terminal), and place great emphasis on evaluation of the reputation of the site and countermeasures on the net. Of course, these are necessary measures to take, but malware can also come in the form of a compressed file with a password. And in a sandbox, advanced malware will alter its behavior, causing it to go undetected.

In order to address these issues, Fujitsu is developing four kinds of technology. Let me explain them in order.

Development of Technology for Post-intrusion Measures

For MA, in the earliest stages of an attack, questions like, "Are attacks noticed?", "Can the spread of damage be prevented?" and "Can the extent of impact be identified?" must be answered expediently. To that end, we analyze the behavior of attacks with the hopes of understanding their methods. Since attackers go through a series of steps to accomplish their purpose, we gain insight into their overall process.


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Fig.2: Product for internal countermeasures against a targeted cyber-attack (iNetSec Intra Wall)

Attacker

Infected via targetede-mail, etc.

AttackTarget

InfectedTerminal

Infection

Switch

Commandinformationtransmission

Spying

iNetSec Intra WallSensor

Monitoring

Monitoring

Monitoring

Monitoring

Detection

Monitoring behaviorbetween terminalsand terminals and server

In particular, there is a well-known framework called the Cyber Kill Chain. It consists of seven steps: Reconnaissance → Weaponization → Delivery → Exploitation → Installation → Command and Control → Actions on Objective. By breaking the attacker's kill chain before it can reach its target, business continuity for a company can proceed unhindered.

① Technology for Detecting Cyber AttacksBased on this thinking, Fujitsu is developing technology focused on the processes used by attackers. By first focusing on attackers' behavior when breaking into a corporate intranet, we detect intrusions based on behavior. At the core is a model of how the attacker's behavior transitions, and the actions taken are classified into phases P1 to P8 as shown in Table 2. The transition from one behavioral phase to the next is modeled in Fig.1.

Based on this information, communication from devices is monitored. By comparing the flow of attack behavior immediately following an intrusion to the attacker behavior transition model, new forms of detection have been developed by Fujitsu (patent pending). By employing these methods, internal attack actions can be detected early, and the probability of breaking the cyber kill chain at a stage before the attacker achieves his/her objective is increased.

② Technology for Blocking Invasive MalwareDetect ion technology a lone cannot ensure the organization's MA. Blocking infected devices is also necessary. Therefore, we are developing technology that automatically disconnects potentially infected devices from the network.

One characteristic common to communication patterns involved in various attack methods is known as a chokepoint. By focusing on and analyzing chokepoints for the type and context of communication flowing through them, the activity of latent malware can be detected. Since only the type of communication and the context are measured, a high detection rate is achieved, even if the information is encrypted (Fig.2).

Technology that detects and blocks certain actions is important in halting the spread of damage early on. To further strengthen mission assurance, this technology can be used in conjunction with external threat prevention products to automatically shut off communications between detected malware and C&C (command and control) servers and spreading/spying activities on internal networks.

③ High-speed Forensic Technology for Understanding Cyber Attacks at a Glance

When personal information leaks due to unauthorized


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S e c u r i t y

Method 1:Collection of Evidence

Method 2: Extracting Attack Progress

> Copy file1

> Cmd1 ...

Command operationevidence trail

・Inferred commands・Linked user information

Analyze operationcommands basedon attack characteristics

Attack PC Damaged PC

Acquiredcommunications

> Copy file1> Cmd1 ...

Cmd1

Cmd2

Cmd3

Cmd1Cmd1

#Login#File Copy#Execution


#Login#File Copy #Login

#File Copy

#Login#File Copy#実行



#Login

#LoginPC2（10.xx.xx.xx）

PC5（10.xx.xx.xx）









A Base B BaseCommand operation

evidence trail

access (as seen in the incidents involving the Japan Pension Service and JTB security), companies report the situation to victims and related organizations and are responsible for explaining the cause and means they are using to handle the situation. To convey this information accurately, it is important to understand the extent of the damage that has occurred once an attack is discovered.

The mainstream approach to this issue involves analyzing network and PC logs. But this method only renders fragmentary information. To grasp the full extent of damage, experts must take time and conduct analysis. This is why it can take weeks to put together the whole picture. Still, for all the communication data acquired, there are methods for analyzing it. But when the amount of data is enormous, the process becomes more expensive and time consuming.

Fujitsu has responded to this problem by developing technology that can quickly assess the level of damage caused by a targeted cyber-attack by automatically analyzing a large amount of network communication. This technology consists of evidence -collecting technology and technology for extracting the details of an attack’s progress.

The evidence collection technology gathers network communication and uses it to determine the operation commands executed on PCs. It then abstracts and accumulates information at the level of obtained operation commands. Through this method, only about 1/10,000th of all network communication data is extracted. In addition, it specifies who performed which operations by linking user information specified in communications data with operation command, collecting a trail of evidence about those executed commands (Fig. 3).

Another means for determining the progress of such attacks is to identify and analyze the communications of a business operating under normal conditions against those occurring when an attack seems highly probable. With this method, damage analysis that would normally take a long time and require the services of experts was possible in a short period of time without the experts. In situations where there are concerns about a lack of security personnel, I believe this will serve as an effective means to rely on. ④ Cyber Threat Intelligence for Assisting AnalystsThe technologies for detecting an intrusion, providing protection, cutting off/blocking an attack, and speeding up the analysis necessary for understanding the impact

Fig. 3:Overview of technology for collecting an evidence trail and extracting the progress of an attack


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of damage have been explained. These are used to minimize damage and ensure MA and BC. In parallel, an in-house CSIRT (Computer Security Incident Response Team) must execute measures to deal with the incident.

CSIRT analysts are essential for understanding the totality of the attack. Using an overall picture of the intrusion incident, the necessary points to protect are narrowed down in order to determine an effective countermeasure approach. This fourth item utilizes cyber threat intelligence (CTI) technology to form a complete picture of an attack. CTI is contextual information for getting an overview of attacks from the results of analysis of cyber-attacks conducted by high-level analysts (Fig.4).

To support this approach, Fujitsu has built a CTI sharing system in collaboration with a leader in the U.S. defense industry, BAE Systems. This system focuses on the five Ws and one H questions for contextual information on cyber-attacks (who: attacker, when: time, why: purpose, where: attack target, how: intrusion path/method, what: observed incident) and information

on countermeasure strategies, converting them into a format that can be processed by computers. In addition to functionality for creating and making use of advanced CTI, the system can securely and easily share CTI with other organizations and companies, enabling even inexperienced cyber-attack analysts to implement high-quality analysis and strong countermeasures expediently.

◇ ◇ ◇

I have explained the four technologies that Fujitsu is developing . Once aga in , these methods and technologies alone cannot guarantee 100% safety from security breaches. There is no established method for completely preventing DDoS attacks, and encryption and key management is also necessary for internal countermeasures related to controlling access and information leakage. Furthermore, processes areas such as physical security and employee awareness training are based the same security measures as before. The four technologies introduced here are focused on early detection after intrusion, understanding the impact of damage caused, and accelerating recovery.

Fig.4: CTI sharing system screen for analyzing the progress of targeted attacks



PART 3-8

A P I M a n a g e m e n t

Fig.1: Examples of Uber Technologies' API in use; business creation through connections (screens show each application)

Matching

Flight andUber reservationsall-in-one

Restaurant andUber reservations

all-in-one

Airports Hotels

RestaurantsStations Point A Point B

Drivers Passengers

Uber PlatformUber API

Call a car using Uber API from United/OpenTable applications⇒ Uber can gain passengers just by making its API publicly open

UNITED OpenTable

Launchpad for Digital BusinessUnderstanding API Management

In contrast to other closed business systems, systems and services in digital business are instead based on being open to the outside. Multiple companies linking their systems and services to each other allows for an approach that can increase the experience-based value for each client. To achieve this we have developed a Web API (Application Programming Interface).

Let's look at Uber Technologies, a car transportation service, as an example of a pioneering company in digital business (Fig.1). The company is open through its Uber API (Web API), and any number of companies can make use of it. One such company is United Airlines. Uber's transportation service can be called from their seat reservation site (application), enabling passengers to arrange for a car to pick them up at the airport when they book a seat. Similarly, OpenTable, a popular U.S. restaurant reservation service, uses the Uber API to

make it possible for users to reserve a car while making a restaurant reservation.

Users reserving a plane or a restaurant seat do not need to launch Uber's app to reserve a car. They can seamlessly arrange a series of appointments as if United Airlines or OpenTable were providing the transportation themselves . This arrangement benefits the three enterprises mentioned as well as their customers. The business conducted between Uber and peripheral companies via a Web API is often called the API Economy.

API Management for Accelerating the API Economy

From a programming standpoint , a Web API is a common subroutine that can be called by various

Hiroki Suzuki　Senior Director, Middleware Business Unit, Digital Transformation Business Group

Kota Kawai　 Director, Business Platform Service Division, Digital Business Platform Unit


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Fig. 2: Five principal functions for API management

AppDevelopers

AppDevelopers

APISpecifications

Release

Outer API

API UseAnalysis

Inner API

⑤ Developer Service ④ Analytics Service

API Gateway

API Management

①Security ② Traffic Control

③ Life Cycle Management

《API User Side》《API Provider Side》

programs. In the case of the Uber API, a subroutine is called for matching drivers and passengers for transportation by the United Airlines reservation program. United Airlines has further enhanced its service by using Web APIs published by various other companies. Even Uber's service allows for the use of other Web APIs, including Google Maps and Braintree (payment service).

Though we may a make a service available to the outside world , it is programmed like any simple subroutine. Restrictions must be put in place for security and external use. To do this, the tool (or service) known as API management is employed; and its main functions are as follows (Fig.2).

① SecuritySince Web APIs are published to the Internet , considerations such as access control and authentication are critical. Access control is a function that narrows down API users. An example of this is requiring an API key distributed in advance for external applications (services) to make requests.

Another level of authentication pertains to user convenience on external services. When a user of the United Airlines app logs in to the reservation system, it requires authentication. But when the user requests the car transportation service within the reservation system, a separate login for Uber also needs to be authenticated. Since users of the Uber API services are authenticated

when using the United reservation system, it is best to avoid having them re-authenticate their login to access Uber. This functionality is made possible using a response protocol called "OAuth."

② Traffic ControlBecause it is difficult to predict how frequently an open Web API will be used, it is virtually impossible to predefine the performance requirements for backend systems generating responses for such Web APIs. If there are too many incoming requests, a company's own service responses could be hampered causing problems with prioritization. In these cases, flow restriction can be effective.

For instance, accepting up to 10 requests per minute and applying a restriction that returns an error on any requests over that amount allows operations to continue within the limits of performance output capacity for backend systems. This method is also effective in dealing with DDoS attacks.

③ Life Cycle ManagementWeb APIs go through a development process similar to the development, testing, and operation of standard applications. In other words, strictly switching to an environment for developing and testing Web APIs and an environment for operating them (open Web APIs) leads to quality assurance. Additionally, by making the URL indicating the endpoint for each version of a Web API unique through version control when making



PART 3-8


Fig. 3: Position of Apigee among API management products (Gartner's "Magic Quadrant for Full Life Cycle API Management" 2016)

CA Technologies

IBMMuleSoft

TIBCO Software (Mashery)Apigee

Red Hat (3scale)Axway

WSO2Sensedia

Akana

Software AG

SAP

Dell Boomi

Torry Harris Business Solutions

Cloud ElementsOracleMashape

digitalML

Apiary

COMPLETENSS OF VISION

ABIL

ITY

TO E

XECU

TE

As of October 2016

NICHE PLAYERS VISIONARIES

CHALLENGERS LEADERS

revisions, application developers can be prevented from using the wrong API.

④ Analytics ServiceTo what extent is the Web API being used? What time of day is it being used? What applications are using it? In what region is it being used? To answer these questions, we use functionality that analyzes and produces visualizations of the history of a Web API's usage. Also, in a business that makes direct sales through Web APIs (e.g. a weather forecast API), the call history for a Web API can be used to track metering information as the basis for usage-based billing.

⑤ Developer ServiceOn the API provider side, a means for disseminating information to developers of applications that use their Web APIs-a "developer portal"-can encourage application developers to proceed with development autonomously.

For Developer Service, there is a template for building a developer portal that includes mechanisms for publishing Web API specifications, accepting petitions for use of the API, distributing API keys, and also supporting application developers through a community.

API Management “Apigee” Provided by Fujitsu

There are many companies that provide tools and services for API management (Fig.3). Fujitsu has partnered with Apigee, which has an exceptional track record in this field, and together they offer K5 API Management on the public cloud K5. Acquisition of ventures in this field by major ICT companies are progressing. For example, CA Technologies has purchased Layer 7, and Red Hat has bought 3scale, each of which was a leading venture. Apigee was also acquired by Google last year. However, they have a


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policy in place that ensures their partnership with Fujitsu remains unchanged, and we are continuing to release API management solutions through K5 to countries all over the world.

Major reasons for Fujitsu's involvement with Apigee is that it has the architecture to scale out and that it has the infrastructure to handle large numbers of API calls. In fact, many distribution businesses use Apigee. In addition to being able to handle more than one billion transactions per day, at its peak usage on Black Friday, Apigee processed 50,000 transactions per second without difficulties.

Moreover, in addition to providing services in a cloud environment based on Apigee's hybrid cloud strategies, such as Amazon Web Services and the Google Cloud Platform, software products with exactly the same architecture for on-premises use are also offered. Fujitsu’s ability to provide both cloud and on-premises services is another reason we chose Apigee.

The Value of Web APIs as System Modernization

We have covered what is indispensable in digital business for application development, but there is one more topic to explore: the modernization aspect of Web API for making existing systems callable from the outside. At Fujitsu we have a system for departments and personnel responsible for maintenance support for hardware and software delivered to clients. It that handles contract

management, equipment management, maintenance parts management, and incident management.

Although each of these involves individual data sets, the portion needed to be handled using office PCs is not much of a problem. However, referencing this on a tablet for customers can be inconvenient. Therefore, a Web API is provided for each siloed system, and it can be accessed from outside the system. At the same time, we developed a tablet app that captures necessary information from a client perspective.

In this simple manner we can set up Web APIs on existing systems. And by employing API management, we provide the invaluable feature of secure access from outside the company. Depending on the API management settings, access can be limited to specific tablets and apps only, and security can be ensured by monitoring calls for data from the Web API. This makes it possible to use the system from the outside without a VPN (virtual private network).

In the future, by publishing Web APIs corresponding to partners supporting Fujitsu's support business, we aim to build partner-specific support systems. We also plan on using Web APIs to enhance our partner ecosystem. Initially, it may be necessary to completely rebuild to manage data beginning with the client. This may be a provisional means, but we think that Web APIs that save both time and cost, as well as API management, have great utility value.


○General Manager Jun Taguchi

○Editor in Chief Junji Kawakami

○Art Director Atsuo Yamamoto

○Contributors Sigehisa Ichikawa (Fujitsu)

Taisyu Ota (Fujitsu)

Yutaka Osada (Fujitsu)

Kota Kawai (Fujitsu)

Shinichi Kawakami (Fujitsu)

Youichi Kurachi (Fujitsu)

Shozo Sakai (Fujitsu)

Tatsuhiko Shibasaki (Fujitsu)

Takaaki Suga (Fujitsu)

Hiroki Suzuki (Fujitsu)

Hidehiro Takeda (Fujitsu)

Kaoru Chujo (Fujitsu)

Masakazu Nakamura (Fujitsu)

Hideki Hara (Fujitsu)

Kouichi Hidaka (Fujitsu)

Takashi Hirano (Fujitsu)

Tomohiro Fukui (Fujitsu)

Kiminori Yoshida (Fujitsu)

Toshikuni Yoshida (Fujitsu)

Tetsuro Takahashi (Fujitsu Laboratories)

Akihiro Kuroki (Fujitsu Research Institute)

Yoshinobu Sawano (Fujitsu Laboratories of America)

○Organizer Yutaka Osada (Fujitsu)

Hidemi Okada (Fujitsu)

Shozo Sakai (Fujitsu)

Tatsuhiko Shibasaki (Fujitsu)

Shengyan Ding (Fujitsu)

Masatsugu Matsuo (Fujitsu)

Takeshi Miyagawa (Fujitsu)

Toshikuni Yoshida (Fujitsu)

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