the advent of r-bpo: is the future of bpo robotic?

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The Services Research Company The Advent of R-BPO: Is the Future of BPO Robotic? Webinar, July 15 th 2016 Phil Fersht Chief Analyst and CEO, HfS Research [email protected] @pfersht

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Page 1: The Advent of R-BPO: Is the Future of BPO Robotic?

The Services Research Company

The Advent of R-BPO: Is the Future of BPO Robotic?

Webinar, July 15th 2016

Phil FershtChief Analyst and CEO, HfS [email protected]@pfersht

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©2016HfSResearch

Overview:• 20 years’ business experience in the global IT and business process

outsourcing and shared services industry • Coined the “As-a-Service Economy” in 2014• Industry analyst, author, speaker, strategist and blogger• Advised and cogitated on 100’s of global IT services, BPO and

shared services engagements• Meddles with the largest global network of enterprise services and

operations professionals

Career Experience:• Practice Lead, IT Services & BPO Research, Gartner, Inc• Global BPO Marketplace Leader, Deloitte Consulting • Consulting Practice Lead, IDC Asia/Pacific• IT Markets Practice Lead, IDC Europe

Education:• BS with Honors in European Business & Technology, Coventry

University, United Kingdom • Diplôme Universitaire de Technologie in Business & Technology from

the University of Grenoble, France

[email protected]

Phil Fersht, CEO and Chief Analyst, HfS Research

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©2016HfSResearch

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©2016HfSResearch

HfS Research Has Been Writing About Intelligent Automation for 4+ Years

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©2016HfSResearch

The “Intelligent OneOffice” will emerge from Digital + Automation

The Digitally-Driven Front

OfficeMobile,

Social/Interactive, Real-time actionable data,

Design Thinking

Digital UnderbellyIntelligent Automation of manual processesDigitization of documentsIoT

Intelligent Digital Support FunctionFront office-aligned IT, Finance, HR, Procurement, Supply Chain

Intelligent Digital Processes Predictive & Operational Analytics, Cognitive.

TheCustomer-firstDigitalOrganization

TheEnablingIntelligentOneOffice

The Nervous System, incepting & Processing

all Inputs

The Neural System

The Circular System

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©2016HfSResearch

The Service Providers will bifurcate into two groupings

Back Office OutsourcersEfficiency, Automation, Labor Arbitrage and Scalability

OneOffice EnablersData Orchestration and Human Collaboration

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©2016HfSResearch

62%

49%

29%

29%

26%

24%

18%

13%

11%

33%

45%

40%

31%

48%

43%

30%

23%

25%

19%

22%

21%

24%

37%

29%

26%

12%

18%

5%

9%

16%

35%

38%

Drive down operating costs

Cost effective, flexible services

Better address risk and regulation

Accelerate speed to market with new products/services

End-to-end process optimization

Real-time data-driven insights

Improve the quality of operations talent

Restrict the recruitment of labor where possible

Invest in process automation and robotics to reduce reliance on labor

Mission Critical Increasingly Important Emerging Not a Directive

HowcriticalarethefollowingC-Suitepriorities/directives,intermsofshiftingfromaCostFocustoaValueFocuswithyouroperatingmodel?

C-Suite operations directives focused on “more from less”

Source:HfSResearchandKPMGLLP,2015Sample:168EnterpriseBuyerExecutivesfrom“AchievingValueBeyondCost”Study,2015

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©2016HfSResearch

RPA use focused on IT currently, with F&A in a high adoption swing

8%

8%

8%

9%

8%

8%

10%

6%

9%

10%

17%

17%

18%

17%

19%

21%

19%

23%

23%

23%

HumanResources

Procurement

Industry-specificProcess(i.e.…

Sales

SupplyChainandLogistics

CustomerService/SalesSupport

Marketing

FinanceandAccounting

ITapplicationmaintenance&…

ITandNetworkinfrastructure…

FullscaleRPA Implementing/usingRPAactively

Source: “Intelligent Operations" Study, HfS Research 2016Sample: Buyers = 371

ThinkingabouttheuseofRPAwithinthefollowingbusinessfunctions,whatstageofmaturityhaveyoureached?

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©2016HfSResearch

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How buyers would improve the quality and outcomes from their current service relationships…

28%

13%

9%

45%

4%

2%

Lettinggoandgivingupmorehigher-valueworktoourserviceprovider(s)

Threateningtoentertaincompetitivebid(s)toforceyourcurrentprovider(s)touptheirgame

Bringbackmoreworkin-houseandimproveitourselves

Rolloutanautomationstrategyintandemwithourprovider

Bringinaspecialistadvisortorecalibrateourrelationship(s)andgetusontherightcourseforAs-

a-Service

Notalot– wepaidfor“cheapandcheerful”andthat’swhatwe’restuckwith

Source:TheHfSWorkingSummitforServiceBuyers,December2015(Sample53enterpriseoutsourcingleads)

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©2016HfSResearch

RPA 1.0

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©2016HfSResearch

How HfS Defines Intelligent AutomationRobotic Process Automation describes a software development toolkit that allows non-engineers quickly to create software robots to automate rules-driven business processes. E.g. digitizing the process of collecting of unpaid invoices, that involves mimicking manual activities in the RPAsoftware, the integration of electronic documents and generation of automated emails to ensure the wholecollections, process is run digitally and can be repeated in a high-throughput, high intensity model.

Cognitive computing is the simulation of human thought processes in an Intelligent Automation process or set of processes. It involves self-learning systems that use data mining, pattern recognition and natural language processing to mimic the way the human brain works, without continuous manual intervention. E.g. an insurance adjudication system that assesses claims, based on scanned documents and available data from similar claims and evaluates payment awards.

Autonomics is referring to self-learning and self-remediating engines, where the system makes autonomousdecisions, using high-level policies, constantly monitoring and optimizing its performance and automaticallyadapting itself to changing conditions and evolving business rules and dynamics. Increasingly minimal humanintervention. E.g. a virtual support agent continuously learning to handle queries and creating new rules/exceptions as products evolves and queries change.

Artificial Intelligence is where intelligent automation systems go beyond routine business and IT process activity to make decisions and orchestrate processes. E.g. an AI system managing a fleet of self-driving cars or drones to deliver goods to clients, manage aftermarket warranties and continuously improve the supply chain.

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©2016HfSResearch

HfS Sees Intelligent Automation As-a-Continuum

trigger based

Characteristic of process

rules baseddynamic language

rules basedstandardized language

Structured

Characteristic of data/information

Unstructured without patternsUnstructured patterned

Data CenterAutomation:

RunbookScriptingSchedulingJob controlWorkloadautomationProcessorchestration

SOAVirtualization

Cloud services

RPA CognitiveComputing

ArtificialIntelligence

BPMWorkflow

ERP

Autonomics

Self-learning & Self-remediation

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©2016HfSResearch

Intelligent Automation Continuum Expanding Fast

trigger based

Characteristic of process

rules baseddynamic language

rules basedstandardized language

Structured

Characteristic of data/information

Unstructured without patternsUnstructured patterned

Data CenterAutomation:

RunbookScriptingSchedulingJob controlWorkloadautomationProcessorchestration

SOAVirtualization

Cloud services

RPA CognitiveComputing

ArtificialIntelligence

BPMWorkflow

ERP

Autonomics

Self-learning & Self-remediation

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©2016HfSResearch

Endgame: Vertically infused insights and data??!!Insights,Data

VerticalProcesses

Verticallyinfusedinsightsanddata

BPaaS,BPOas-a-stack,Industryplatforms.

Machinelearning,Neuralnetworks,Enterprisesearch,ArtificialintelligenceAnalytics

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©2016HfSResearch

So We Need To Transform What Knowledge Work Means

New JobsData Insight ManagerAugmentation IntegratorVisualization Interpretation"Bot" Employee OversightAutomation Overlord

Endangered JobsData EntryInvoicing / CollectionsAbstracting & IndexingData ReconciliationL1 Customer SupportMaster Data Management

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©2016HfSResearch

Automation Impact Scenarios on Services Professionals by 2021

Scenario1ModerateLowskilledjobsfallingby22%

Mediumskilledjobsincreasingby13%

Highskilledjobsincreasingby57%

Totaljobsfallingby2%

Scenario2Likely

Lowskilledjobsfallingby30%

Mediumskilledjobsincreasingby8%

Highskilledjobsincreasingby56%

Totaljobsfallingby9%

Scenario3Aggressive

Lowskilledjobsfallingby36%

Mediumskilledjobsincreasingby1%

Highskilledjobsincreasingby55%

Totaljobsfallingby14%

~300,000jobsatrisk ~1,400,000jobsatrisk ~2,200,000jobsatrisk

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©2016HfSResearch

1.7 2.7

4.85.2

8.8 6.1

0

4

8

12

16

2015 2021

ITServicesa

ndBPO

Employees

(Millions)

LowSkilledServicesJobs

MediumSkilledServicesJobs

HighSkilledServicesJobs

Impact of Automation on Services Jobs – Likely Scenario

Impact• Lowskilledjobsfallingby30%• Mediumskilledjobsincreasingby8%

• Highskilledjobsincreasingby56%• Totaljobsfallingby9%

Outlook• LowskilledjobsphasingouttoautomationthroughRPA/Autonomics

• Startingtoaffectmediumskillsascognitivecomputingaugmentstheseskills

• Increasingdemandforhighskilledpositionsinvolvingcreativeproblemsolving,analyticsandcriticalthinking

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©2016HfSResearch

Total Impact of Automation on IT/BPO Services Workers by Major Country (likely scenario, low-skilled workers)

0.73 0.74

2.28 2.34

0.670.54

1.641.57

-35%

-30%

-25%

-20%

-15%

-10%

-5%

0%0.0

0.5

1.0

1.5

2.0

2.5

Philippines UK India US

%DecreaseinW

orkforce

ServicesW

orkers(M

illions)

2015 2021 %Change

Research sources: 1477 industry stakeholder interviews 2015-16, NASSCOM, US National Bureau of Labor Statistics, UK ONS, Selected others, HfS Analyst judgment

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©2016HfSResearch

Total Impact of Automation on IT/BPO Services Workers by Major Country (likely scenario, mid-high skilled workers)

0.28

0.80

1.11

2.56

0.41

0.94

1.27

2.73

0%

10%

20%

30%

40%

50%

0.0

0.5

1.0

1.5

2.0

2.5

3.0

Philippines UK India US

%In

creaseinW

orkforce

ServicesW

orkers(M

illions)

2015 2021 %Change

Research sources: 1477 industry stakeholder interviews 2015-16, NASSCOM, US National Bureau of Labor Statistics, UK ONS, Selected others, HfS Analyst judgment

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©2016HfSResearch

Total Impact of Automation on IT/BPO Services Workers by Major Country (all skill-levels across all workers)

1.00

1.54

3.38

4.90

4.43

1.08

1.47

2.90

4.30 4.18

-20%

-15%

-10%

-5%

0%

5%

10%

0.0

1.0

2.0

3.0

4.0

5.0

6.0

Philippines UK India US Other

%Cha

ngeinW

orkforce

ServicesW

orkers(M

illions)

2015 2021 %Change

Research sources: 1477 industry stakeholder interviews 2015-16, NASSCOM, US National Bureau of Labor Statistics, UK ONS, Selected others, HfS Analyst judgment

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©2016HfSResearch

David PooleCo-founder and CEOSymphony Ventures

Ian BarkinCo-founder and Head of StrategySymphony Ventures

Johnny RamondinoSenior Director Product ManagementADP

The Panel

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23 Orchestrating the world’s work© 2016 Symphony Ventures – Confidential and Proprietary

This Game is Changing

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24 Orchestrating the world’s work© 2016 Symphony Ventures – Confidential and Proprietary

Our Observations Regarding RPA Take-Up

Robotic BPO Pure Players• Automation process specialists• Implementation experience and capability extending into operate and run• Extensive process model and object library• Human augmentation in exception handling and expert knowledge provision

Shared Services and GBS• Direct / implementation partners• Centers of excellence

BPO• Clients taking a multi-channel approach

- In-house / specialist firms vs BPO providers• Slow provider take-up and limited partnering strategy• Outcome-based providers win over FTE-based providers• Opportunity for digital innovation

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25 Orchestrating the world’s work© 2016 Symphony Ventures – Confidential and Proprietary

World-ClassProcess

Standardized &

ControlledProcess

World-ClassProcess

World-ClassProcess

“Process as a service” – standardized world class processes utilizing leading SaaS tools, enablers and accelerators. RPA provides the integrations between the tools and the interfaces to and from core legacy systems. Staff will handle the tasks requiringhuman intervention.

World-ClassProcess

UnstructuredCommonProcess

”As-a-Service” Processes

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The Changing Landscape Driving BPO (Business Process Outsourcing)

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27

ADP is transforming HCM

Copyright © 2016 ADP, LLC. Proprietary and Confidential.

Interconnecting Technology with Expertise

27

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28

Supporting our clients throughout their lifecycle

Service delivery evolution

• ACA cost and compliance analysis, scenario modeling

• HR, Pay and benefits regulations and best practices

• Sustain and improve quality of service & speed of execution

• Optimize scope of services to improve value proposition

• Speed up transition to stable state after major initiatives

• Business case support• Compensation planning, job/

position codes, salary banding• HCM integration and

process improvement• Wellness strategies• Workforce planning• Data driven decision support

• Rapid standup model• Combined technology stack and

service teams• Proven track record mitigating

risks• Controlled cost

• Supports all sizes of clients• Manages differences in

complexity needs when requirements change

• Large geographic footprint

• Strategy & personalized tools to educate employees andimprove engagement

• Change Management for organizational, process andtechnology changes

Intelligent Automation

Advisory Services

Communication & Change

Management

Acquisition & Carve out

Support

Compliance & Regulatory

Affairs

Scalable Service Model

Page 29: The Advent of R-BPO: Is the Future of BPO Robotic?

The Services Research Company

The Advent of R-BPO: Is the Future of BPO Robotic?

APPENDICES

Phil FershtChief Analyst and CEO, HfS [email protected]@pfersht

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©2016HfSResearch

How HfS Defines Intelligent AutomationRobotic Process Automation describes a software development toolkit that allows non-engineers quickly to create software robots to automate rules-driven business processes. E.g. digitizing the process of collecting of unpaid invoices, that involves mimicking manual activities in the RPAsoftware, the integration of electronic documents and generation of automated emails to ensure the wholecollections, process is run digitally and can be repeated in a high-throughput, high intensity model.

Cognitive computing is the simulation of human thought processes in an Intelligent Automation process or set of processes. It involves self-learning systems that use data mining, pattern recognition and natural language processing to mimic the way the human brain works, without continuous manual intervention. E.g. an insurance adjudication system that assesses claims, based on scanned documents and available data from similar claims and evaluates payment awards.

Autonomics is referring to self-learning and self-remediating engines, where the system makes autonomousdecisions, using high-level policies, constantly monitoring and optimizing its performance and automaticallyadapting itself to changing conditions and evolving business rules and dynamics. Increasingly minimal humanintervention. E.g. a virtual support agent continuously learning to handle queries and creating new rules/exceptions as products evolves and queries change.

Artificial Intelligence is where intelligent automation systems go beyond routine business and IT process activity to make decisions and orchestrate processes. E.g. an AI system managing a fleet of self-driving cars or drones to deliver goods to clients, manage aftermarket warranties and continuously improve the supply chain.

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©2016HfSResearch

HfS Automation Labor Impact Model –Key Assumptions & Methodology

This model predicts likely impact of the most recent wave of automation on the IT Services and BPOindustry. We estimate the current total IT Service and BPO employs c15 Million in 2015. With c3.5Million in India, c1 Million in Philippines, c5 Million in North America and c4 Million in Europe.

The workers within the industry have been divided into 3 categories: low skilled, medium skilled andhigh skilled. With low skilled workers conducting simple entry level, process driven tasks that requirelittle abstract thinking or autonomy. High level workers undertaking complicated tasks that requireexperience, expertise, abstract thinking and autonomy.

The model then applies underlying growth rates for each category linked to market growth. Eachscenario has a different set of parameters that will impact each level of worker setting out likely degreeof automation for each group and the probability that the job will be automated and in what timeframe this is likely to happen. There parameters are set out in full on the “Scenario Parameters” slide.The model then predicts the reduction in each level of the workforce based on the probability ofautomation within the scenario. This is taken from the underlying growth figure to produce a numberfor the work force at each level.

The underlying growth rates assume current market growth will continue and is varied between thelevels based on demand – so given the increasing demand for higher level workers the underlyinggrowth in this category is larger irrespective of increases in automation.

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Automation is in the eye of the beholder

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©2016HfSResearch

What is IASK?The Intelligent Automation Starter Kit is a specific workshop series for end-user organizations.

It provides a one-stop orientation for enterprise teams looking to understand Intelligent Automation technologies including the potential applications to their business

To get involved, email [email protected]

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©2016HfSResearch

About HfS ResearchHfS Research is the leading analyst authority and global network for IT and business services, with a specific focus onglobal business services, digital transformation, and outsourcing. HfS serves the research, governance, and servicesstrategy needs of business operations and IT leaders across finance, supply chain, human resources, marketing, and coreindustry functions. The firm provides insightful and meaningful analyst coverage of best business practices andinnovations that impact successful business outcomes, such as the digital transformation of operations, cloud-basedbusiness platforms, services talent development strategies, process automation and outsourcing, mobility, analytics, andsocial collaboration. HfS applies its acclaimed Blueprint Methodology to evaluate the performance of service andtechnology in terms of innovating and executing against those business outcomes.

HfS educates and facilitates discussions among the world's largest knowledge community of enterprise servicesprofessionals, currently comprising 150,000 subscribers and members. HfS Research facilitates the HfS Sourcing ExecutiveCouncil, the acclaimed elite group of sourcing practitioners from leading organizations that meets bi-annually to share thefuture direction of the global services industry and to discuss the future enterprise operations framework. HfS providessourcing executive council members with the HfS Governance Academy and Certification Program to help its clientsimprove the governance of their global business services and vendor relationships.

In 2010 and 2011, HfS Research's Founder and CEO, Phil Fersht, was named “Analyst of the Year” by the InternationalInstitute of Analyst Relations (IIAR), the premier body of analyst-facing professionals, and achieved the distinctive award ofbeing voted the research analyst industry's Most Innovative Analyst Firm in 2012.

In 2013, HfS was named first in rising influence among leading analyst firms, according to the 2013 Analyst Value Survey,and second out of the 44 leading industry analyst firms in the 2013 Analyst Value Index.

Now in its seventh year of publication, HfS Research’s acclaimed blog “Horses for Sources” is widely recognized as themost widely read and revered destination for unfettered collective insight, research, and open debate about sourcingindustry issues and developments. Horses for Sources today receives over a million web visits a year.

To learn more about HfS Research, please email [email protected].