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
@pfershtWeb: hfsresearch.comBlog: horsesforsources.com
Phil Fersht, Chair FORA Council & CEO HfS Research
© 2017 HfS Research Ltd.
© 2017 HfS Research Ltd.
www.HfSResearch.com
© 2017 HfS Research Ltd.
The Six Value Levers Driving the Digital Operations Industry
© 2017 HfS Research Ltd.
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
© 2017 HfS Research Ltd.
Double-digit days of “traditional” outsourcing growth are long-
gone
Source: HfS Research, September 2017
© 2017 HfS Research Ltd.
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 (
$B
)
IT Professional Services Other IT Services
IT Infrastructure Management Application Development & Management
Industry Specific BPO HRO
F&A BPO Customer Care BPO
3.3%
5.6%
5.0%
3.3%
5.7%
-2.3%
4.9%
0.2%
-5% 0% 5% 10%
CRM BPO
F&A BPO
HR BPO
Industry SpecificBPO
ADM
IT Infrastructure
ProfessionalServices
Other ITServices
CAGR 2017 - 2021
Source: HfS Research, September 2017
© 2017 HfS Research Ltd.
Automation Opportunity Vast & Untapped
© 2017 HfS Research Ltd.
Automation and AI Business Operations Spend 2016-2021
0.3 0.4 0.6 0.8 1 1.2
4.86.2
7.58.9
10.211.5
0.7
1.1
1.6
2.0
2.42.7
0%
5%
10%
15%
20%
25%
30%
35%
0
5
10
15
20
2016 2017 2018 2019 2020 2021
Y-o
YG
row
th (
%)
Exp
end
itu
re (
US$
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.
© 2017 HfS Research Ltd.
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
© 2017 HfS Research Ltd.
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
© 2017 HfS Research Ltd.
The Future of Operations in the Robotic Age The OneOfficeTM Organization
© 2017 HfS Research Ltd.
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.
© 2017 HfS Research Ltd.
Can you estimate the proportion of structured v unstructured data in your organization?
Unstructured data is pervasive!
Source: HfS Research, September 2017
Sample: Enterprise Buyers = 460
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
© 2017 HfS Research Ltd.
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
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123
xyz
© 2017 HfS Research Ltd.
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”
Sample: Enterprise Buyers = 400
© 2017 HfS Research Ltd.
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
Source: “State of Automation 2017”
Sample: Global 2000 Enterprise Buyers = 400
© 2017 HfS Research Ltd.
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
Source: “State of Automation 2017”
Sample: Enterprise Buyers = 400
© 2017 HfS Research Ltd.
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
Source: “State of Automation 2017”
Sample: Enterprise Buyers = 400
© 2017 HfS Research Ltd.
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
Source: “State of Automation 2017”
Sample: Enterprise Buyers = 400
© 2017 HfS Research Ltd.
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
Source: “State of Automation 2017”
Sample: Enterprise Buyers = 400
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
© 2017 HfS Research Ltd.
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.