NASSCOM BPM Strategy Summit 2017 - The Future of Operations in the Robotic Age By Phil Fersht, CEO & Chief Analyst, HfS Research

The Services Research Company

Phil Fersht

CEO and Chief Analyst, HfS [email protected]

The Real Impact of Automation, and AI on Enterprise Operations

© 2017 HfS Research Ltd.

Overview:

• Industry analyst, author, speaker, strategist, entrepreneur and blogger

• 20 years’ in the global IT and business process outsourcing and shared services industry spanning analyst and consulting roles

• Coined the As-a-Service Economy in 2014

• Coined The Digital OneOfficeTM in 2017

• Advised and on 100’s of global IT services, BPO and shared services engagements

• Overseas the largest global network of enterprise services and operations professionals

Career Experience:

• Founded HfS Research in 2010, overseeing an unprecedented growth story in the analyst industry

• Practice Lead, Global IT Services & BPO Research, Gartner, Inc

• Global BPO Marketplace Leader, Deloitte Consulting

• Consulting Practice Head, IDC Asia/Pacific

• European IT Markets Practice Lead, IDC Europe

Education:

• BSc. Honors in Business & Technology, Coventry University, UK

• Diplôme Universitaire de Technologie in Business & Technology, University of Grenoble, France

[email protected]

@pfershtWeb: hfsresearch.comBlog: horsesforsources.com

Phil Fersht, Chair FORA Council & CEO HfS Research



www.HfSResearch.com


The Six Value Levers Driving the Digital Operations Industry


Which of the following business drivers will have a major impact on your business?

It really is all about data now…

0% 5% 10% 15% 20% 25% 30%

Scarcity of creative talent that can see the possibilitiesfor innovation and growth via new technologies

Adapting legacy work culture to be more real time anddigital

Driving out costs through process automation

Building relationships with external ecosystem andindustry partners to drive innovation and growth

Micro targeting customers / hyper personalization andcustomization of products to customer requirements

Combating the threat of potentially disruptive digitalcompetitors

Making more predictive decisions based on rapidlyaccessible real-time data

The shift toward digital/online/virtual experiences andaway from physical/face-face engagements

Rank 1 Rank 2

Source: HfS Research, September 2017

Sample: Enterprise Buyers = 460


Double-digit days of “traditional” outsourcing growth are long-

gone



Global BPM and IT Services Market, 2017–2021 ($B)

$0

$250

$500

$750

$1,000

$1,250

2016 2017 2018 2019 2020 2021

An

nu

al E

xpe

nd

itu

re (

$B

)

IT Professional Services Other IT Services

IT Infrastructure Management Application Development & Management

Industry Specific BPO HRO

F&A BPO Customer Care BPO

3.3%

5.6%

5.0%

3.3%

5.7%

-2.3%

4.9%

0.2%

-5% 0% 5% 10%

CRM BPO

F&A BPO

HR BPO

Industry SpecificBPO

ADM

IT Infrastructure

ProfessionalServices

Other ITServices

CAGR 2017 - 2021



Automation Opportunity Vast & Untapped


Automation and AI Business Operations Spend 2016-2021

0.3 0.4 0.6 0.8 1 1.2

4.86.2

7.58.9

10.211.5

0.7

1.1

1.6

2.0

2.42.7

0%

5%

10%

15%

20%

25%

30%

35%

0

5

10

15

20

2016 2017 2018 2019 2020 2021

Y-o

YG

row

th (

%)

Exp

end

itu

re (

US$

Bill

ion

s)

RPA Intelligent Process Automation AI Business Operations Spend Growth (YoY)

$5.8 Bn

$7.7 Bn

$9.7 Bn

$11.7 Bn

$13.6 Bn

$15.4 Bn

Source: HfS Research 2017

AI refers to the simulation of human thought processes across enterprise operations, where the system makesautonomous decisions, using high-level policies, constantly monitoring and optimizing its performance andautomatically adapting itself to changing conditions and evolving business rules and dynamics. It involves self-learningsystems that use data mining, pattern recognition and natural language processing to mimic the way the human brainworks, without continuous manual intervention.


C-Suite directives focused on less cost and more OneOffice automation, machine learning and real-time data How critical are the following C-Suite directives to your operations strategy? (SVPs and above)

20%

22%

26%

30%

31%

31%

42%

48%

46%

55%

45%

48%

48%

43%

19%

19%

13%

20%

15%

15%

8%

12%

12%

5%

5%

6%

6%

7%

Invest in cognitive techn and machine learning to reduce reliance on

mid/high skilled labor

Invest in process automation and robotics to reduce reliance on low-

skilled labor

Improve the quality of operations talent

Accelerate speed to market with new products

Create real-time data that supports predictive, not reactive decisions

Align middle/back office operations to improve customer

experiences

Drive down operating costs

Mission Critical Increasingly Important Emerging Not a Directive

Source: HfS Research in Conjunction with KPMG, “State of Operations and Outsourcing 2017”

Sample: n=454 Enterprise Buyers


HfS Sees Intelligent Automation as a Continuum Today

trigger based

Characteristic of process

rules baseddynamic language

rules basedstandardized language

Structured

Characteristic of data/information

Unstructured without patternsUnstructured patterned

Data CenterAutomation:

RunbookScriptingSchedulingJob controlWorkloadautomationProcessorchestration

SOAVirtualizationCloud services

RPACognitive

ComputingArtificial

Intelligence

BPMWorkflow

ERP


The Future of Operations in the Robotic Age The OneOfficeTM Organization


AI building blocks

Technology: Nuance, Cortana, Alexa

Use cases: voice recognition, conversational services

Technology: Google DeepMind, Tensorflow, Loop AI, Microsoft Cognitive Services

Use cases: integration of data on an industrial scale, pattern recognition without

ontology or knowledge base, analysis of dark or IoT data

Technology: IPcenter, HIRO, ignio, HOLMES

Use cases: password reset in IT help desk, self-healing IT environment

Technology: IBM Watson, Amelia, LivingActor, Accenture myWizard

Use cases: substitute of IT and business agent, virtual data scientist, virtual scrum

master, mortgage broker advisor

Technology: HIRO, ignio, HOLMES

Use cases: discovery in accounting, KYC, batch management

Technology: AntWorks, AlchemyAPI, Clarifai

Use cases: pattern recognition in images, integration of handwriting

NLP

Machine/Deep

Learning

Neural Networks

Virtual Agents

Autonomics

Computer Vision

Without understanding what’s happened in the past, AI

cannot provide an optimal customer service experience

• People who buy those cars may have a basic understanding of how thetechnologies work, but most tend to focus on the benefits that come with aninvestment in the technology, notably spending less on gas while also helping tosave the environment

• It’s not necessarily the technology itself that’s most important, but rather theimpact that the technology has on the experience of their users.

• IBM’s Watson utilizes the information it has available to answer questions andmake decisions, based on probabilities, but it doesn’t have the capabilities toremember and apply an understanding of what may have happened in the past.

• Deep learning AI systems are all about storing what has been learned in the past,takes note of how variables and results have changed under different scenariosand then make decisions based on that.

• A chatbot that knows what the product inventory looks like, how to calculateshipping information and complete the sale — with no human needed. But,without a deeper learning, it cannot make recommendations about otherproducts that a specific shopper might like based on previous visits.


Can you estimate the proportion of structured v unstructured data in your organization?

Unstructured data is pervasive!



0%

9%

40%

29%

20%

2%

0% / 100% 10% / 90% 25% / 75% 50% / 50% 75% / 25% 100% / 0%

Only 22% of organizations have more

than half their data structured


User journey from unstructured request to execution

Customerrequests

Virtual AgentStandard

transactionsSelf-service

formsDynamic Case

Flow Mgt.

• Unstructured

forms of

requests

• Different media

• Conversation

• Knowledge

infusion

• Natural

language

processing

• Analytics

• Transactions

that comply

with standard

operating

procedure

• Knowledge

base

• Interactive

forms

• Service

catalogue

• Governance

• Orchestration

of interactions

and workflows

Bots

Chat

Knowledgedatabase

NLP

• Extraction of

data

• Execution of

requests

• Scheduling

abc 123 xyz

123

xyz

abc123 abc

xxx123

xyz789

789

xyzabc

123

xyz789

abc

xxx 123

123abc xxx

xyz

xxx 789

123

789

xxx

123123

abc

123

xxx123

789 abc

789abcxxx123 789

abc

123xxx

xyz

xyz789

xxx123

abc

abc xxx789

abc

abc123

789

123

xyz


When, if ever, do you believe AI automation to be applicable for you within the following processes?

All AI Techniques & Solutions Are Getting Evaluated

37%

42%

37%

41%

45%

19%

18%

21%

23%

21%

23%

21%

24%

19%

22%

NEURAL NETWORKS

NATURAL LANGUAGE PROCESSING (NLP)

COMPUTER VISION

VIRTUAL AGENTS

MACHINE LEARNING (ML)

Piloted / implemented Evaluating In next 2 years

Source: “State of Automation 2017”



How would you describe your organizations current Automation strategy?

Almost a third of enterprises are already integrating automation

into their service delivery

31%

20%18% 17%

13%

2%

We are integrating in

our service delivery

We are in the process

of formulating a

strategy

We have built/are

building a Center of

Excellence

Project use/case

focused

We are mandating this

as a requirement for

our service provider

We don’t have one


Sample: Global 2000 Enterprise Buyers = 400


How is the decision-making process for automation capabilities organized within your enterprise?

Decision Making For Automation: Broad Set of

Stakeholders, Narrow Set of Decision Makers

18%

21%

22%

24%

24%

27%

28%

29%

35%

57%

54%

15%

48%

42%

51%

48%

44%

47%

49%

44%

51%

32%

31%

43%

13%

11%

18%

21%

11%

19%

20%

21%

11%

10%

15%

39%

21%

27%

10%

8%

21%

7%

4%

7%

4%

1%

1%

3%

EXTERNAL CONSULTANTS

CHANNEL PARTNER

DATA CENTER MANAGER

PURCHASING MANAGER

INTERNAL PANEL OF EXPERTS/BUSINESS LEADERS

PROCUREMENT DEPARTMENT

FINANCE DEPARTMENT

LINE OF BUSINESS DIRECTOR

CFO/FINANCE DIRECTOR

CIO / IT DIRECTOR

CEO

MANAGEMENT BOARD

Decision Maker Influencer Stakeholder No role

The C-suite plays a critical role in setting

the automation strategy




Which of the following benefits do you think automation could deliver to your operations?

Automation Benefits Seem To Reflect Long-Term Thinking…

12%

21%

25%

31%

37%

38%

45%

46%

48%

49%

52%

FTE reduction

Guaranteed short term cost reduction

Overcoming process bottlenecks and enabling processes to flow end-to-end

Relieves management time to focus on customers

Improves employee motivation by relieving them of rudimentary tasks

Better visibility, auditability and compliance

More actionable data for customer insights

More actionable data for operational insights

Superior data accuracy

More workforce agility – giving operations the ability to scale

Better quality of operations




What is preventing or slowing the adoption of Automation within your organization?

The Automation Catch-22: The Biggest Adoption Barrier Still

Seems To Be Short-Term Cost Benefits

20%

23%

25%

27%

28%

28%

28%

35%

Not sure where to start

IT does not have the time to implement

Lack of understanding of technology buildingblocks

Bad experience with technology-driven processchange

Lack of internal talent to evaluate and implement

Underlying platform is sufficient, don’t think automation lower cost

IT budgets exhausted from technologydeployments

Immediate cost savings not attractive enough




What is stopping you from considering the application of RPA technology within your organization?

RPA is struggling to provide the business case for non-adopters



8%

8%

10%

17%

23%

23%

24%

30%

41%

The disruption to the business is too great

We are unconvinced of the service provider capabilities in this area

We don’t know who should be responsible

We don’t have the appropriate talent

Have adopted technology-driven process change before and have had bad

experiences

We don’t believe the cost savings would offset the disruption

We don’t see the business value to our organization

It will be built into enterprise software platforms in the next 5 years; we’ll

wait

Lack of clarity on the business case

© 2017 HfS Research Ltd.Source: Bureau of Labor Statistics, HfS Research Analysis (data to 2015)

Recessions destroy jobs, not robots…

-4.0%

-3.0%

-2.0%

-1.0%

0.0%

1.0%

2.0%

3.0%

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Annual Job Growth US


Six Steps to be Successful in the Robotic Age

I. Be smart about your career. If you can’t automate and digitize your rudimentary processes, you will quickly run out or value to any organization. Being smart about data is no longer geeky, its career-critical.

II. Begin with quick wins. Get stakeholders onside by demonstrating meaningful, impactful outcomes without major investments. Find a broken process you can quickly fix with RPA or a SaaS/mobile app, or simply by converging data. Then find another…

III. Focus on integrating data with real urgency. Every siloed dataset restricts the analytics insight that makes you a strategic contributor to the business. You can’t create value or transform a business operation without converged, real-time data!

IV. Focus on speed and urgency with short-terms plans to realize your long-term vision. Really look to deliver results in weeks not months and keep delivering robust outcomes as you go to enhance your credibility . Think of each individual project as a milestone achieved on a longer journey.

V. Practice inclusive leadership. Engage people and value their input to win hearts and minds – realize the vision of the transformation together.

VI. Be brave! You have to venture outside of your comfort zone and take your colleagues and partners with you. You have to believe in what you’re doing and make smart, pragmatic – and sometimes bold decisions along the way.