work the way you live deloitte shared services conference 2019 · - business objectives - technical...

Work the way you liveDeloitte Shared Services Conference 2019

Robotic and Intelligent Automation 101Dave Wright, Dupe Witherick, Nadia Shamsad, Deloitte

Robotic and intelligent automation 101Copyright © 2019 Deloitte MCS Ltd. All rights reserved.

Facilitators

Dave Wright Nadia ShamsadDupe Witherick


Objectives for today

Introductions

Overview of intelligent automation

Market trends

Identifying opportunities

Building an automation portfolio

Takeaways


Introductions

Question 1: Where are you from?

Question 2: Where are you on the automation journey?

Copyright © 2019 Deloitte MCS Ltd. All rights reserved. Robotic and intelligent automation 101

Overview of intelligent automation


What is R&IA?

1 – Robotic Process AutomationRPA is automation of business processes in which software performs tasks that can be codified by computers. It is often referred to as 'robotics' or 'robots' and is defined as the automation of rules-based processes with software that utilises the user interface and which can run on any software, including web-based applications, ERP systems and mainframe systems.

Screen scraping data collection

Rule based business process management

Tactical toolset to automate repetitive tasks

Cheaper and faster step towards process efficiency

3 – Artificial IntelligenceAI technologies perform tasks that previously required human intelligence, such as extracting meaning from images, text or speech, detecting patterns and anomalies, and making recommendations, predictions or decisions. They include machine learning, deep learning, natural language processing and generation.

Natural language recognition and processing

Dealing with unstructured super data sets

Hypothesis based predictive analysis

Self-learning rules continuously rewritten to improve performance

2 – Intelligent AutomationThe combination of Robotic Process Automation (RPA), artificial intelligence (AI) and other related automation technologies.

Data input and output in any format

Pattern recognition within unstructured data

Replication of judgment based tasks

Basic learning capabilities for continuous improvement to quality and speed


Our perspective on Artificial Intelligence

With each data point, interaction and outcome, develop and sharpen expertise

1

Apply context, understand imagery, speech and other unstructured data like humans do

5

Interact

Perceive

Understand

Reason

LearnNatural Language

Generation

Robotics

Image Recognition

Speech Recognition

Machine Learning

Natural Language

Processing

Advanced Analytics

Deep Learning

Talk and interact with humans in a natural way

4

Use hearing and sight to gather information from the surrounding world

3

Grasp underlying concepts, form hypothesis, apply rules and infer and extract ideas

2


Market trends


Year-on-year trends in Robotic Process Automation

2015

• 0% implementing RPA

• 55% anticipate an increase in use of RPA by 2017

2016

• 22% starting their RPA journey

• 74% planning to investigate RPA technology soon

2017

• 53% started their RPA journey

• 78% of those expecting to significantly increase investment over the next 3 years

“RPA could achieve near-universal

adoption within the next 5 years"

2018

• 68% started their RPA journey

• 4% of those have achieved scale and are now operating more than 50 robots

Sample sizes: N=20 (2015), N=143 (2016), N=424 (2017), N=478 (2018)


Automation with Intelligence: Re-imagining the organization in the ‘Age of With’


Identifying opportunities


The 8 steps along a typical client journey

First wave into production

Setup the centre of

excellence

Manage production processes

Scale deployment through the organisation

Scale deployment through the

business unit

Select processes

for automation

Define the RPA vision

Select RPA technology

1. Assist the client in setting the RPA vision for implementation:- Vision- Scope- Business objectives- Technical objectives- Success factors

4. Set up the foundations at the client to support their RPA journey:- Define CoE model to achieve core objectives- Set the standards, structures and methods for

delivery and ongoing management- Mobilise CoE to support ongoing efforts

3. Help client to select processes which help to achieve their objectives:- Define prioritisation criteria- Review processes for suitability- Build business case and roadmap

5. Deliver the first high value automations into production (~10 automations):- Select automations with most benefit to gain buy

in, in a focused area- Demonstrate delivery process- Demonstrate benefits realisation

6. Manage automations in the production environment:- Manage incidents in a

controlled way- Run a well-governed

change control process- Monitor capacity,

performance and business MI

- Run robot assurance process

7. Build on the solid foundation, implement at scale in a focused area:- Build automations end to

end across focused process areas

- Manage organisational change

8. Scale through the organisation to achieve a virtual workforce:- Realise significant benefits- Manage organisational change and

cultural shifts2. Help the client to choose an RPA technology provider, which allows them to achieve their objectives:- Help define client

selection criteria- Honest comparison of

technology providers- Proof of concept

comparison- Infrastructure setup

support


Full lifecycle to delivery

Development

User

Acceptance

Tests (UAT)Go Live Hypercare

Discover Design Deliver Deploy

Process Design

Process Analysis


A five week project identifying 152 opportunities for process automation, to potentially save 75,000+ hrs/year

Typical “Discover” process

-

5,000

10,000

15,000

20,000

25,000

30,000

35,000

CD Finance R&D HR CMI Marketing UFS

Tim

e S

av

ing

, h

rs/y

ea

r

Time Saving, per function, by proposed solution

RPA - Immediate Qualification RPA - Future Investigation IT/I&A Solution I&A Solution

152 50

34

51

170

20

40

60

80

100

120

140

160

# opportunitied

identified

I&A Solution IT/I&A Solution RPA - Future

Investigation

RPA - Immediate

Qualification#

of

op

po

rtu

nit

ies

Hopper Summary

170validated

opportunity cards

221-1

sessions

152validated,

consolidated opportunities

✔

7opportunity

identification workshops

204Processes for investigation

9RPA

awareness sessions

7functional lead

review meetings

84tagged as

reporting & IT use cases

68Remaining RPA opportunities

RPAHopper

(76k hrs/yr)

(9k hrs/yr)

(29k hrs/yr)

(18k hrs/yr)

(20k hrs/yr)

Reportingsolution

ITsolution

Other


Advantageous process characteristics

Process predictability

Rules based exceptions

Fewer systems

Each system used by the robot will require

configuration specific to

that system, may require credentials

High frequency

Daily, weekly and monthly

processes make the

most efficient use of your

digital workforce

Prone toavoidable errors

This gives the robot a real advantage over the human

workers and helps with the

change journey

Process needs to be defined in terms of a

set of unambiguous business rules

Simpler processes with few

exceptions in delivery

Repetitive

Highly repetitive

processes are unpopular

with people but robots love them

Structured data can be

read and used much more easily than

unstructured

Type of input e.g. voice, OCR will impact

complexity of automation

Structured vs unstructured

Inputs


Identify 2-3 candidate processes you wish to automate. For each process consider if the process…

Exercise

Is predictable?

Has rules based exceptions?

Uses a few number of systems?

Has high frequency?

Is repetitive?

Is prone to avoidable errors?

Uses structured data?

Has digital inputs?

Strongly disagree Strongly agree









“Discover” enablers

Accelerators Tools

4 | Copyright © 2018 Deloitte Development LLC. All rights reserved.

Our lab experiences are a powerful

selling tool that spark sales

opportunities at each stage of the

automation journey.

Further details of each lab and

typical projects told through client

impact stories can be found in the

Appendix

Scaling LabAn immersive, full day collaboration session that explores the ‘art of the possible’, engages with key scaling capabilities, and ignites momentum behind automation

Re-imagination LabA session to shift Executives mindsetenabling them to re-imagine an E2E

process unlocking the potential of Automation technologies

Activation LabA half day Lab to kick start a client’s

Automation journey, prioritise use cases for execution and aide them to avoid common

pitfalls made by others

01

02

03

Achieving

Automation Project

Lab

4 | Copyright © 2018 Deloitte Development LLC. All rights reserved.

Our lab experiences are a powerful

selling tool that spark sales

opportunities at each stage of the

automation journey.

Further details of each lab and

typical projects told through client

impact stories can be found in the

Appendix

Scaling LabAn immersive, full day collaboration session that explores the ‘art of the possible’, engages with key scaling capabilities, and ignites momentum behind automation

Re-imagination LabA session to shift Executives mindsetenabling them to re-imagine an E2E

process unlocking the potential of Automation technologies

Activation LabA half day Lab to kick start a client’s

Automation journey, prioritise use cases for execution and aide them to avoid common

pitfalls made by others

01

02

03

Achieving

Automation Project

Lab

Deloitte Discovery and Delivery methodology

Deloitte ecosystems


Development

User

Acceptance

Tests (UAT)Go Live Hypercare

Discover Design Deliver Deploy

Process Design

Process Analysis

Full lifecycle to delivery


“Process Analysis” considerations

Changes that may be required to the current process

Reporting requirements

Likely exception paths

Scenarios that would need to be tested

Change management

Go live strategy


Building an automation portfolio


Potential benefits


Typically there are six barriers that stand in the way of successful automation scaling

Overcoming Barriers to Scale


Vision and journey towards your future workforce

Workforce

• What is your business strategy?

• What is your automation strategy?

• Are leadership aligned on the vision?

• What are your strategic drivers / competitive differentiators e.g. cost, productivity, efficiency, customer centricity?

• What (new) activities / services are you planning to deliver?

• What new / augmented skills & capabilities do you want to possess?

• What is the mind-set & culture of your organization?

Strategy & Context

Imagining your

future workforce

• The convergence of technology and talent models has opened new

opportunities for workforce planning and the composition of work. How

does the organisation plan to (re)define work, workforce and workplace?

• Have you considered holistically what your future organisation design will

look like and considered the implications of embedding a digital workforce?

• Have you identified what future skills & capabilities are required in order

to achieve your vision & business case benefits?

Shaping your

future workforce

• How will the organisation leverage uniquely human skills to enhance

machine-human collaboration, drawing out the best of both?

• How will the organisation design account for headcount impacts, and/or

the augmentation of roles & teams? How will you re-design roles to realise

improvements in productivity and efficiency?

• How will governance enable control whilst allowing the flexibility required

for ongoing change and improvement? Are roles & accountabilities well-

defined?

Transitioning to

your future

workforce

• Is leadership sponsorship strong enough to ensure understanding of and

investment in the cultivation of a digital culture?

• Is there a talent strategy in place to define tailored approaches to

capability development?

• Has performance management of both the human and digital workforce

been considered?

Transforming your

future workforce

• What is the mind-set in your organisation and how will that shape the

change journey?

• Have you determined the most appropriate mechanisms and timings for

communicating the changes?

• How the workforce be incentivised to embrace automation and agility?


Automation should simply be viewed as one step in operational excellence process optimisation

Process

Employing this approach will help overcome process fragmentation and support the ability to scale automation across your organisation

EliminateIdentify sources of effort and eliminate them at their roots

StandardiseStandardise operational processes within an organisation or team

Simplify Reduce time spent carrying out the process

Automate Deploy technology to automate the process

DefineEstablish an agreed understanding of the current state processes


Key considerations for scaling

Technology

Core Infrastructure

• Cloud Vs On premise• Distributed architecture• High Availability/Disaster Recovery• Backups

• Load balancing• Clustering• File storage• Firewalls

Control Room Architecture

• Control Room strategy• Role based access• Version control

• Environments – DEV/UAT/Prod• Credentials management• Password management integration

OperatingEnvironment Strategy

• Centralised Vs Federated• Physical Vs Virtual Machines• Attended Vs Unattended

• 2FA e.g. smart cards• Application environment strategy• Business Continuity

Workstation Provisioning

• Provisioning workstations across environments e.g. DEV/UAT/Prod

• Packaged desktop build for Robotics e.g. Group policy exceptions

• Plug-ins and connectors (Java, drivers)

• Software patching cycle

Cyber Security & Access Policies

• Robot accounts (user Vs service)• Segregation of Duties, least privilege

principle• Data policy and procedures e.g.

storage, archiving, retention complies with industry standards e.g. (PHI)

• SSO for application access• Data quality & integrity e.g.

anonymized Vs Prod• Auditing e.g. operational,

administrative and transactional Robot logs

Development & Deployment Process

• Reusable components• Wiki – knowledge base• Best practices e.g. coding standards,

code reviews

• Testing strategy• RDLC artefacts• Change Management

Procurement & Licensing

• Procurement of licenses• Direct or through re-seller• Licence models e.g. concurrency,

minimum purchase, duration, etc.

• Developer license allocation shared Vs individual

• Runtime license optimization –dependency on operating model


Data

Data GovernanceThe operational structures put in place to manage and make

decisions about data with clearly defined ownership and

responsibilities.

Data Quality

The degree to which the organisation can trust the accuracy, consistency and completeness of data.

Data AnalysisThe rigour with which data can be used for analysis to enable

business decision-making.

Checklist

Data Governance Framework documented

Data owners and stewards assigned

Common data dictionary is in place that is understood, used and referred to enterprise wide

Data governance policies updatedData governance processes and controls implemented

Data quality and master data management process in place

Data cleansing performed at the source and is a priority

Processes are in place to resolve data quality issues

Metadata and reference data for unstructured data are defined and captured

Unstructured data formats are standardised where possible

Data is reliable and can be used to generate meaningful insight and inform decision-making, with any caveats clearly defined and communicated

Data quality is actively measured and reported

Data Security

The protection of data from unauthorised access and data corruption throughout its lifecycle.

Data AccessibilityThe right people have access to the right data from the right channel in a consistent and automated way.

Data StandardisationThe extent to which standardised data models and definitions are

used and commonly understood.


Takeaways


Takeaways

The way we live and work will be transformed through automation1

2 Although most companies are automating, very few have yet scaled

3 Enterprise-wide automation will become the norm quickly


Appendix


Enterprise Automation FrameworkThe Automation Framework underpins the core content of the R&IA scaling lab and addresses the most commonly experienced barriers to scale

A bold yet plausible vision and ambition

that key people buy in to

New ways of organising and working to adopt and collaborate with

new digital co-workers

Vision Operating Model

Knowing how and where value will be

captured and how to prioritise investments

Value Capture

Having the skills and capacity to

automate at scale, and supporting

people whose roles will change

Daisy-chaining technologies in a stable, resilient

and secure environment, in a fast and agile way

Workforce Technology

Enabling adaptive value streams,

driving differentiated

business performance

Process

Policies, standards, governance, ways of working and roles and responsibilitiesto support controlled adoption across the enterprise

Centre of Enablement Standards and Control Framework

Proactive governance and

quality management of structured and

unstructured data

Data

Enterprise-wide RPA

EnterpriseAutomationFramework

V1.4


AI SeekerAI Seeker is a crowdsourcing tool that gives people across the business the chance to provide potential opportunities, effectively outsourcing the initial search. BAs can then prioritise and progress ideas with substance. While this targets task based opportunities, it can be a helpful way of engaging with stakeholders and building awareness

Cognitive Engagement

Cognitive Automation

Cognitive Insights

Natural Language Processing

Similarity system

Advanced scoring engine

Guided conversation to collect ideas

Access via the intranet

Augment interactive Workshop

Stakeholder management

Pipeline of cognitive opportunities

Ideas review

Disparate activities can lead to duplication

and inconsistent use of technologies

Problem statement

Automation opportunities exist across the organisation but are not easy to identify

v

Initiatives need to be captured and prioritised to allow for effective scaling

Differing levels of understanding of the potential of automation

Benefit

Our solution

Automation opportunities identified across the organisation and scored automatically

v

Workforce has enhanced understanding of automation and AI and identifies more opportunities

Coordinated roadmap, technology platform increases ROI of automation projects

Bring to our clients

Adapt to client and industry needs

Cloud hosted with minimal integration effort


Digital PipelineCurrently the opportunity list, high level cost / benefit, process and technical documents and business case realisation are stored in separate repositories and require manual effort to manage. Shibumi is a cloud based solution which can hold all necessary information in a single area, making pipeline management for simplifications and automations easier

Automated prioritisation & qualification

A global methodology configuration

Slicing and dicing data

Client proven approach

Engage stakeholders through platform

Fully auditable

Structured approach to qualification

Bulk import feature - simple to upgrade

Fast configuration

Advanced benefits tracking features

Exportable to MS Excel

Numerous reporting views

Up to 50% of a process analyst’s time can be spent on low value activities such as assimilating disaggregated data to present in slides

Problem statement

Existing methods of pipeline management are disaggregated, typically relying on spreadsheets, often managed in isolation

v

Laborious sign off processes and business engagement often slows the rate of progression

Poor visibility of opportunities and the associated data within the pipeline, results in poor awareness and business engagement

Benefit

Our solution

Systematic opportunity prioritisation and qualification, reduces the time spent creating PQD documentation

All documentation stored per opportunity, enabling aggregation of data to a holistic level for reporting and cross business insights

Dynamic prescription of actions per opportunity lifecycle phase including customisable alerts to key stakeholders

Bring to our clients

Adapt to client and industry needs

Automation “in a box” – the Deloitte method productised


Digital DiscoveryUnderstanding the ‘As-Is’ landscape of a process end-to-end is highly manual and normally missing the intricacies of an overall process. Our digital discovery tool aims to combine data mining with desktop recording information to integrate the data and provide a true representation of the process, so simplification and automation can be fact based and more impactful

Deploy

Build

Analyse

Processes are scattered and not well understood even where robust process documentation exists

Problem statement

Automation opportunities exist but organisations have struggled to scale

v

Initial view of automation opportunities and business case is based on assumptions

Discovery of automation opportunities is manual and time-consuming

Benefit

Our solution

Candidates for R&IA can be identified in around 6 weeks and are based on actual client data

Fact based analysis will tell us with confidence where the highest value opportunities are

Bring to our clientsThe Digital Discovery tool is industry agnostic and relevant to all clients pursuing an automation programme

Digital discovery will enable us to move up the value curve to access end-to-end opportunities

The ‘Deloitte Process Mining Framework’ uses data science to integrate the front and back end system data

Celonis Process Mining uses system event logs to visually reconstruct how processes perform

NICE Automation Finder records front-end employee actions to capture processes in real-time

Pipeline of robotic and cognitive opportunitiesdriven by data

Swiftly move onto discussions around transformation and delivering value

The framework will provide an end-to-end view of processes highlighting process complexities and variants to expose opportunities for automation

Expedite benefits realisation by reducing the leakage between opportunities identified and implemented

Digital Discovery captures front and back-end system data to provide an end-to-end view of processes

This publication has been written in general terms and we recommend that you obtain professional advice before acting or refraining from action on any of the contents of this

publication. Deloitte MCS Limited accepts no liability for any loss occasioned to any person acting or refraining from action as a result of any material in this publication.

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