March 2015, IDC #254209

WHITE PAPER

The Critical Role of the IT Group in Self-Service Analytics

Sponsored by: Tableau Software

Brian McDonough Dan Vesset

March 2015

IDC OPINION

Agile decision making, aided by self-service analytics software, is improving organizational

performance at leading organizations around the world. Organizations that have learned how to

provide business users with self-service information access analytics capabilities while maintaining

control of data assets in line with IT and corporate policies and practices are realizing benefits across a

wide range of business processes. It is not always an easy task, but the business benefits, both

quantitative and qualitative, are worth the effort to give users more control over their own analytic fate.

Some view self-service analytics as nothing more than another attempt to circumvent the IT group and

enterprise policies for a localized benefit. Nothing could be further from the truth. In today's era of more

and faster-moving data, organizations have no choice but to ensure effective collaboration and

appropriate division of labor among IT, line-of-business (LOB), and business intelligence (BI) groups in

enabling self-service analytics. IT groups should take a leadership role because by supporting

self-service analytics, IT can become an essential partner in personal and organizational success.

Customers, big and small, are telling us that self-service analytics is a "must-have" capability that can

maximize its benefits when it is supported by a robust IT infrastructure and adherence to corporate

data governance and security policies while providing end users with the flexibility to tackle real

business issues with real benefits. Customers interviewed about their experience with self–service

analytics cite important lessons:

At Arby's Restaurant Group Inc., the IT department took a leadership role in deploying a new

self-service analytics solution that could access multiple enterprise data sources. Creative

problem solving through ad hoc analysis spread quickly and in one specific case is being used

to manage a project involving a large capital expenditure over several years that is key to

Arby's strategy and future growth.

At the U.S. division of a global bank, an agile self-service analytics environment enabled the BI

team, in collaboration with the IT group, to meet a much greater demand for information

access and analysis from business users. The new self-service analytics solution has led to

the identification of potential new clients and new revenue opportunities.

At World Wide Technology (WWT), spreadsheet-based analysis has been steadily replaced by

purpose-built self-service analytics software as users experience the benefits of a more visual

and engaging analytics solution and share their experience with peers. The new solution

provides greater visibility into data quality issues and improved data governance compared

with the previous method of spreadsheet-based analysis. This has resulted in more consistent

and trusted interpretation of analysis.

©2015 IDC #254209 2

Whether business users, a business intelligence competency center, or the IT group first brings the

tool into the organization, IT leadership is necessary to ensuring the successful implementation and

adoption of a new generation of BI and analytics solutions.

IN THIS WHITE PAPER

This white paper discusses the benefits and challenges of deploying self-service analytics solutions

and the new roles that IT, line-of-business, and business intelligence or analytics groups need to

embrace to ensure pervasive adoption of this technology. This white paper discusses lessons learned

from organizations that have experienced benefits following the deployment of self-service analytics

and effective collaboration among IT, BI, and LOB groups. This white paper further provides

recommendations and lessons learned for IT managers to take an active role in supporting the ad hoc

analysis and data discovery needs of business users.

SITUATION OVERVIEW

The reality of changing software purchasing trends and budgets (e.g., IDC research shows 60% of IT

spending now is funded or very strongly influenced by business groups) is having an impact on the

relationship between LOB and IT around data and software. Many LOB, BI, and analytics groups pride

themselves on their ability to bypass IT to fulfill their own needs for data access and analysis. But there is a

fine line between data and analytics democracy and anarchy. While there are clear benefits to self-service,

this approach also exposes the organization to new risk in the form of inconsistency in data definitions or

key performance indicators (KPIs), incomplete or siloed data, or misinterpretation of results of analysis.

Too many in IT still equate self-service analytics only with increased risk and lack of governance, while

too many on the business side view IT only as a roadblock on the way to faster and more flexible

access and analysis of data. Business end users do complain about slow IT support. According to IDC

research, only 8% of business users today cite that they are completely satisfied with the speed of IT's

response to their needs and requirements. At the same time, IT complains about ill-defined and

constantly changing user requirements.

The tide is turning. A growing number of IT, business, and BI groups are recognizing the need to

collaborate and to recognize and leverage each other's core competencies. Several customers that

went through the growing pains of this process shared their experiences and lessons learned.

Widespread Use of Self-Service at Arby's Restaurant Group Highlighted by the Financial Planning and Analysis Group

Saddled with an in-house-developed enterprise data warehouse (EDW), a BI toolset, and outdated

enterprise applications, Arby's Restaurant Group Inc. had an opportunity to change things after a split with

restaurant chain Wendy's in 2011. After completing the implementation of new enterprise applications, the

company began searching for a better BI solution in 2013. Arby's hadn't yet updated its EDW, so it needed

a BI solution that could access multiple data sources and relate and aggregate this information while a

new EDW was being built. Arby's IT department turned to Tableau Software for its visual analytics and

©2015 IDC #254209 3

self-service analytics capabilities. "Behavior changed almost immediately as business and even members

of my department began asking new questions of our data," said John Lukas, CIO at Arby's Restaurant

Group Inc.

Arby's Financial Planning and Analysis (FP&A) group supports financial decision making for the

company and was just one of the many groups that began asking new questions of their data. Faced

with a strategic initiative to remodel company-owned restaurants with maximum return, FP&A built a

dashboard on Tableau to replace a legacy spreadsheet-based analysis solution that was manually

intensive to maintain, slow to calculate analysis, and limited in the analysis it could perform.

The goal of the spreadsheet solution was to compare sales before and after a restaurant was remodeled.

The spreadsheet took 8 hours to manually prep every week and took 7 hours to calculate the sales

change. FP&A wanted to conduct more analysis to better understand the variables that impacted success

so best practices could be implemented as other sites are remodeled in the future.

FP&A constructed a dashboard on Tableau that removed the 8 hours a week of data preparation

previously required by connecting directly to the data source. It also calculated the before and after

outcomes in seconds rather than hours. But more importantly, it let the FP&A team see how restaurants

near a remodeled site are impacted, how time of year impacts a remodel, what factors determine whether

a site is a good candidate for remodeling, and more. This is important insight that has led the FP&A team

to calculate the ROI and begin to make the case to franchisees who own 71% of all restaurant sites that a

remodeling effort is worth the capital expenditure. With Tableau, the FP&A team can spend more time

conducting analysis rather than preparing data. It is already assigning, as a project, each of its team

members to create a Tableau dashboard and show the company something it hasn't seen before.

This is just one example of an organization that recently started using new ad hoc analysis of granular

data to discover new metrics and key performance indicators that can help it better manage its

business. The flexibility of the self-service solution and the speed of deployment by the IT group

enabled the organization to pose a new question concerning a current promotion and conduct analysis

of its performance that immediately yielded benefits. This type of capability is not common, and at

Arby's, it hinged on the effective collaboration between IT and business as well as the recognition that

BI and analytics do not represent a single use pattern or a homogeneous workload.

"We enabled marketing to pose and answer their own questions, finance to do live what-if analysis

during budgeting meetings, our buying organization to drive greater efficiencies across its operations

and more, all without the user coming back to us with a request to build new analyses or provide

access to new data sources," said Lukas.

BI and Analytics Use Cases

There are three major BI and analytics use cases, each requiring a dedicated approach and

appropriate technology support. The three use cases are:

Performance management, which is focused on planning and analysis of a fixed set of KPIs to

assess historical performance. Solutions in this area are typically deployed to support

executives and managers. This may include dashboards and reports and alerting technology

to notify managers of trends and anomalies in the data. The key factor of this use case is a

well-known set of preset requirements.

©2015 IDC #254209 4

Operational intelligence, which is focused on sense-and-response functions and may include

delivery of real-time information to frontline employees or other systems. Typically, these

systems rely on rules that are periodically reviewed and adjusted as needed.

Exploration and discovery, which focuses on ad hoc analysis. BI technology and techniques are

not new, yet the previous practices that relied on static reports or even interactive dashboards

that answered predefined questions no longer meet the expectations of information-hungry

decision makers at all levels of the organization. A new generation of technology is putting

design questions and the ability to answer those questions in the hands of business users. This

is fundamentally changing how organizations interact with data, how they develop new

hypothesis and scenarios, and how they react to changes in their operations or the market.

There are gray areas between these use cases, but they nevertheless help highlight the breadth of what

BI and analytics can mean to any given company. At Arby's, the case of quickly developing a hypothesis

and testing it by using rapid development techniques and a flexible ad hoc analysis process highlights the

company's ability to recognize the specific use case (Exploration and Discovery) and execute it in a

manner that differs from something requiring a more highly controlled production environment like

enterprise reporting. The difference in the output of the two use cases is clear (see Figure 1). Such

interfaces solicit excitement from LOB users — a rare feat in the enterprise software market.

FIGURE 1

Visualizations Engage Analytics Users

Source: Tableau Software, 2015

©2015 IDC #254209 5

Although a picture is worth a thousand words, in this case, it does not do full justice to the interactivity

provided by such an analytics tool or the new data preparation, access, analysis, presentation, and

sharing processes that it enables.

To provide LOB users with this type of self-service solution, IT has the opportunity to play a critical role

in deploying the software and underlying infrastructure, provision the source data sets, and ensure the

environment is maintained to provide the desired performance.

Self-Service Analytics for All at the U.S. Division of a Global Bank

A few years ago, following the deployment of new operational applications, the U.S. division of a global

bank (the company) began to look for new BI software to address its overreliance on disconnected

spreadsheets for analysis. Using disconnected spreadsheets had resulted in data quality problems

from manual data entry, version control issues with various analyses, and lack of sufficient data

governance. The previous data analysis practices also limited collaboration and knowledge sharing

because the analyses were often kept on local hard drives for largely personal use.

The effort was led by the four–person BI group rather than the central IT group. After the selection and

initial deployment of new self-service analytics software from Tableau Software, the company

experienced a rapid growth in the number of self-service analytics users. Three years after the initial

deployment in 2010, there were 2,000 users, and today, five years later, the company has 5,000 users

and 600 active users.

The company's VP of Internal Channels and Intelligence said, "We don't believe in the concept of the

power user; our philosophy was to make good tools available to all users."

Part of what drove the rapid adoption of the self-service analytics software from Tableau Software

were the specific features and functionality of the tool. Figure 2 displays another sample of a

self-service analytics dashboard (note that this is only a sample and does not reflect the specific

deployment at the company).

©2015 IDC #254209 6

FIGURE 2

Painting a Picture of Performance

Source: Tableau Software, 2015

Just as importantly, what drove such strong demand for and rapid adoption of Tableau Software's

self-service analytics software at the company was the effective collaboration between the BI group

and the IT group. At the company, the BI function is separate from the IT function. IT manages the

central data warehouse and production reporting software; it also manages the hardware infrastructure

and security for the company. But like in many companies, the IT group was not staffed to address the

constantly changing data discovery and analysis needs of all the various internal business groups.

Seeing the gap in internal BI capabilities, the BI group decided to take a lead in filling the business

need. It started small and incrementally approached individual business groups, promising to rapidly

develop an initial set of analytic dashboards without any cost to the business group. The BI group did

internal marketing of successful deployments and even hired a videographer to create "how to" videos,

which became extremely effective in increasing awareness and demand for the new self-service

analytics solution. As demand for the solution grew rapidly across the organization, 50 volunteers with

knowledge of specific business domains emerged across departments to champion the unique

analytics needs of the groups they support and to work closely with the BI team to meet these needs.

©2015 IDC #254209 7

While the IT group was initially not involved in the introduction and early success of the Tableau Software

deployment, it did become involved as soon as the BI group needed to expand to the Tableau Server

product, which allows people to share their dashboards and data sources with colleagues in a secure

fashion. The VP of Internal Channels and Intelligence put it plainly, "I didn't want to run a server under my

desk. IT allocated virtual machines to our deployment and took over security management." IT also

provides the BI group with enterprise data, which has already been cleansed, thus requiring minimal, if any,

data quality reviews by the BI group. The BI group manages the metadata, and the 50 BI developers in the

business group have full freedom to build dashboards or reports as needed by their local constituents.

One example is the set of tools for wealth management advisors that allows the company to identify

net-new assets of its clients — assets under management elsewhere that could potentially be moved

under the company's management. In addition, there are performance management reports for

managers as well as risk check reports that flag such events as unusual trades.

Another key benefit of using Tableau has been the ability to rapidly produce new reports and

dashboards on an as-needed basis. In the past, the BI group focused on 40 core reports, while today it

is able to create hundreds of views, dashboards, or reports. Also, in the past, the BI group was able to

support only 100 users, while today, with the same human resources, it is supporting 5,000 users,

including financial advisors and staff in finance, HR, banking, and insurance areas of the company.

The company has adopted an agile approach to development and handles about 30 ad hoc user

requests per month, which can range from simple requests to change the color on a report to more

complex requests. "Before, building a report was like deciding to get married," said the VP of Internal

Channels and Intelligence. "Today, some changes are instant, and none of the new reports or changes

take more than two weeks to deploy."

As the company adds more users and dashboards, it is steadily replacing a previously implemented

cloud-based BI tool with Tableau to speed time to insight and reduce costs of ownership. The

replacement will reduce the cost of its analytics solution by over 80%.

Productivity Gain and Rapid Increase in Self-Service Analytics Usage at World Wide Technology

At World Wide Technology (WWT), a systems integrator and global supply chain solutions provider,

individual business users had begun to use their own copies of Tableau Desktop. The centralized BI group

saw the opportunity to expand the use of Tableau and began facilitating discussions with the IT group.

Initially, IT was concerned about letting the new self-service environment into the organization. Some

members of the IT group were concerned about data security, but others in IT recognized the benefits and

the potential efficiency gains for their own group and for the company and moved forward with an

implementation of Tableau Server.

The status quo when it came to fulfilling BI needs of business users at WWT was very much like that at

many other companies. Change requests from business were communicated to IT. One group from IT

collected requirements; another team would develop the solution and then pass it back to business.

These processes introduced unnecessary delays and inefficiencies. IT was responsible for the entire

cycle of information access and analysis, including extracting data, organizing data, performing analysis,

and delivering reports. The business users took the reports and continued to do their own analysis in

spreadsheets because they wanted to add their own data and manipulate it in new ways. In effect, the

©2015 IDC #254209 8

whole information access and analysis process was duplicated by business users. Both groups

recognized that this process, which resulted in overreliance on spreadsheets, was far from ideal.

WWT's IT group recognized the need for a more flexible analytic environment that could enhance and

extend its centralized BI reporting environment. After outlining roles and responsibilities, the IT and

business groups were able to form a successful partnership and make significant progress toward

removing the dependency on spreadsheets for ad hoc analysis. The proliferation of independently

designed and distributed analysis previously done in spreadsheets was brought under better control

through the Tableau self-service analytics solution.

The use of the new visual discovery tool provided not only a new level of flexible, on-demand access

to data but also insights into data quality issues as well as a means for the BI group to govern data.

WWT approaches data governance as a continuous process of refinement rather than a process that

must be finalized before analysis can be conducted. This allows business users to benefit from more

immediate insights while incremental gains in KPI and data standardization are incorporated over time.

As Rob Villareal, Lead of the WWT BI Competency, said, "We changed to a process of sharing

information first versus sharing it only when it's perfect. The latter is really impractical."

WWT's BI team learned another valuable lesson during the deployment of Tableau to the broader

internal audience. Initially, the team decided to seek internal power users and offer them Tableau

Desktop licenses and training. The power users loved the new tool, but they weren't using it. It turned

out that because of their deep expertise with spreadsheets, they were happy to continue using them.

"You can't give people licenses and just expect them to go and start using the software," said Villareal.

"It's important to understand people need to see the benefits of switching before they will."

Instead, WWT created a new centralized BI Competency Center (BICC) staffed with some existing

employees and some new employees. The BICC is made up of 12 people, 7 on the IT side and 5 on the

business side. The core BICC is supported by a total of 16 full-time data analysts in the lines of business

and 30 IT staff focused on the data infrastructure. IT staff working with the BICC are responsible for

making relevant data sources available, maintaining and improving the data warehouse, managing access

permissions, and ensuring data quality.

Analytics teams were created to align with lines of business, and team members worked closely with

their business function and were trained to use Tableau. The departmental analytics teams are

responsible for accessing data through Tableau and building visual dashboards for the lines of

business they support. "It's a division of labor that works. We don't want a Wild West environment,"

said Villareal. With this shift, IT is able to spend more time building up scalable data sources and a

more responsive information architecture rather than churning out reports. As a result, within the past

six months, the company has seen a fourfold increase in the use of the Tableau solution, with users

accessing Tableau through mobile devices and on laptops. In the past, IT just handed over reports to

LOBs without knowing how they were used. Today, with a corporatewide Tableau license funded by

IT, the company is able to keep track of detailed technology utilization metrics, such as most active

users, top-viewed dashboards, and data sources used most often.

There are no shortcuts when it comes to facilitating effective collaboration. At WWT, the BICC leadership

spent time convincing and cajoling both IT and LOB leadership to gain trust and support for the self-

service analytics solutions and processes. The benefit of this effort is that there is now broad adoption,

©2015 IDC #254209 9

including at the highest levels of the company. Both the president and the CEO of WWT use executive

dashboards developed in Tableau, and some top executives start each day by looking at Tableau-based

information. And yet the company has only scratched the surface of the potential use of self-service

analytics — "We have passed infancy and are now into awkward adolescence," said Villareal.

The Role of IT in Enabling Self-Service Analytics

Improved collaboration among IT, business, and BI groups can help mitigate risks and drive more

pervasive adoption of self-service analytics tools. One of the key factors to enable the success of

such a strategy is for IT to recognize that self-service is an unstoppable movement (similar to BYOD)

that necessitates giving up the "command and control" mentality of many IT organizations. A big part

of more effective collaboration is the recognition of the role and core competency of each of the

internal stakeholder groups. This can help overcome existing biases and entrenched views about

IT-business interactions.

In too many companies, the IT group is involved in the full life cycle of the data preparation, management,

and analysis processes of any given BI solution. This is what leads to end-user dissatisfaction, siloed

shadow IT projects, and therefore unnecessary risks for the company. It doesn't have to be this way.

In the case of the U.S. division of a global bank, IT has conceded dashboard development to a

distributed team of business users while maintaining control over the quality and sources of data.

Although there are still, and maybe always will be, some lingering organizational challenges to this

alliance, the new approach has resulted in improved insight and satisfaction among business users.

Business users' analysis requirements are met faster than ever before. At the same time, IT is able to

fulfill its mission of supporting enterprise data management and governance goals.

IDC believes that IT should focus on:

Providing the right infrastructure to support today's generation of self-service analytics

software (This can include ensuring appropriate performance from on-premise server and

storage hardware, optimized software implementation, and/or identification and management

of cloud services contracts.)

Making all relevant enterprise data and external data sources available and ready for use by

business users

Ensuring that data can be trusted by leading ongoing data quality and governance processes

Leading a cross-functional team to train and educate users on the software and share best

practices for self-service development

Management of data access rights, including those on mobile devices, and otherwise ensuring

security of the data

By focusing on its core competency, IT can ensure its resources are optimally deployed and don't

cause critical delays for end users looking for self-service analytics. More importantly, by becoming

more involved in information management, rather than focusing on operational IT support, the CIO and

other IT leaders will be seen as strategic leaders and partners to the business.

©2015 IDC #254209 10

CHALLENGES AND OPPORTUNITIES FOR TABLEAU SOFTWARE

Tableau Software is one of the leading providers of self-service analytics tools. Founded in 2003,

Tableau has been one of the key vendors at the forefront of developing visual data discovery tools that

enable self-service analytics. The company's products are available for use on an individual desktop or

for the whole enterprise and deployable on-premise or in the cloud. The company even offers a free

version of its software, Tableau Public.

Tableau Software doesn't operate without competitors. The continued demand for self-service visual

discovery has caught the attention of many technology vendors. In this environment, Tableau must

continue to innovate and provide the type of customer service that its users have come to expect. As

the company's footprint in large companies and for enterprisewide deployments expands, Tableau

must continue to ensure balanced support for both business and IT needs.

At the same time, the opportunities are vast. The self-service analytics trend has not yet reached the

majority of organizations — certainly not in the broad global market for BI technology.

New Expectations for Business Intelligence and Analytics

In 2014, organizations of all sizes across industries invested about $11 billion on software for querying,

multi-dimensional analysis, reporting, and visual discovery. This overall BI software market is expected

to continue to grow at a healthy average annual growth rate of 8% over the next five years. However,

one market segment — self-service visual discovery — stands out. It is growing 2.5 times faster than the

rest of the BI market. What is happening in the market is a broad-based resetting of expectations about

information access and analysis. These expectations are driven in the enterprise by:

Experiences of employees in their personal lives with continuously improving search engines

and navigation capabilities of online retailers.

Belief that it is possible to outcompute to gain better insight and to outcompete on better

insight. In this case, outcompute doesn't necessarily refer to greater technology infrastructure

performance; rather, it refers to a full spectrum of features and functionality to deal with more

data in shorter decision cycles by empowering more users — not just the so-called data

scientists and power users — within the organization.

Frustration with existing BI and analytics solutions. Only 31% of organizations cite that their

business analysts' technology needs are being met. That rate is even lower (26%) for

operational and customer-facing employees (see Figure 3). Furthermore, close to 60% of

organizations report that their BI and analytics initiatives are hindered by the lack of BI

technology development skills to build dashboards, reports, and analytic applications.

©2015 IDC #254209 11

FIGURE 3

Percentage of Organizations with Business Analytics Solutions That Meet

User Requirements

Source: IDC, 2015

LESSONS LEARNED

Fighting the trend of self-service analytics adoption will only lead to further separation between

business and IT. Both groups must be willing to make some compromises and collaborate to ensure

mutual success in line with the strategic and operational goals of the organization. Organizations that

have gone through a successful implementation of self-service analytics often cite similar lessons

learned. These lessons fall into categories of analytic processes, cultural change, technology benefits

and limitations, and data management and control issues.

One of the key lessons we heard repeatedly across organizations is that establishing data

governance policies takes longer than expected. It can be politically challenging, and it is often

an iterative process in which perfection is not a reasonable expectation. Both IT and LOB

users need to be aware of this fact of self-service analytics deployment and avoid a drawn-out

political battle for enterprisewide agreement on all elements of the data, metrics, and analytics

before users are able to benefit from new insights.

Responding to the demand for self-service analytics tools will necessitate a reassessment of

current centralized IT practices. Acceptance that agility must be fostered at the expense of

some control will help shift established policies to better suit the requirements for data

discovery and ad hoc analysis. It is important to establish the roles and responsibilities of

business users and IT in support of any self-service analytics implementation.

Individual business groups that often acquire and support their own analytics technology are

often described as "shadow IT." These groups can cause issues with the security and control

of IT solutions and data, but today, a growing number of leading IT organizations see them as

extensions of IT focused on data analysis, interpretation, and distribution. Best practice

approaches are now centered on these two groups working as a collaborative team to improve

user satisfaction and organizational success within established IT practices and policies.

0 5 10 15 20 25 30 35

LOB employees

Data scientists

Business analysts

LOB managers

(%)

©2015 IDC #254209 12

IT should become a clearinghouse to share and disseminate best practices. These could be in

the form of training on how to interpret and analyze the data and KPIs accessed within the

self-service analytics solution. IT can also champion the adoption of self-service analytics by

sharing best practices adopted by one department to inspire other departments to ask new

questions of their data. By focusing on best practices for analyzing and interpreting data, the

IT department becomes more consultative and less administrative.

IT should help business users tell better success stories. IT organizations should not only help

LOB and analytics staff measure and assess outcomes but also work to quantify the value of

analytics projects and impacts those projects have had on the business. An enterprise-

friendly, self-service analytics solution can help in facilitating this process. A server-based

technology, managed by IT, enables IT to view relevant metrics and share them with users

across lines of business instead of having to chase usability and success metrics from

distributed spreadsheet projects or individual desktop tools.

Self-service analytics presents the opportunity for IT to be seen as a relevant, credible, and useful

partner to lines of business. By implementing IT solutions that enhance user experience and

effectiveness, such as self-service analytics, these solutions are more likely to become widely adopted

and bring new success to organizations and individual contributors alike. Through this shared success,

IT can dispel the perception that IT is a bottleneck to business agility and gain recognition as a

valuable and crucial partner to the business user.

As with any new technology initiative, there will be hurdles when implementing self-service analytics.

Most will be organizational challenges that will require compromise and collaboration. The adoption of

self-service analytics is expected to continue at rapid rates. Organizations that embrace the trend with

appropriate division of labor, internal sharing of best practices, and appropriate technology will

experience project success and drive business benefits for their organizations.

About IDC

International Data Corporation (IDC) is the premier global provider of market intelligence, advisory

services, and events for the information technology, telecommunications and consumer technology

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