Zinnov Zones for Robotic Automation Services
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Transcript of Zinnov Zones for Robotic Automation Services
2017
This report is solely for the use of Zinnov Client and Zinnov Personnel. No Part of it may be quoted, circulated or reproduced for distribution outside the client
organization without prior written approval from Zinnov.
Zinnov Zones for Robotic Automation Services- 2017
2
Agenda
1 About Zinnov
2 Robotic Automation (RA) Landscape
3Enterprise Engagements with RA
Services Providers
4 Zinnov Zones for RA Services
3
About Zinnov: A leading Digital Transformation & Globalization focused management consulting company
Zinnov
Enterprise Digital Transformation
Global Engineering Excellence
GEIP – Global Engineering Insights
Platform
Innovation
Enablement
Zinnov Zones
Ratings
Telecom & Networking
Consumer Electronics &
SemiconductorBFSI Retail
14 Years 200 Customers 160 Consultants 6 Offices
Offerings
Government and Industry bodies• Centre for Scientific and
Industrial Research• National Institute of
Smart Government• Ministry of Small and
Medium Enterprise• Department of Science and
Technology• NASSCOM
Tech Platforms & Internet
SolutionsIndustrial
Service Providers| Vendors
4
Zinnov’s framework based approach empowers large enterprises in making strategic decisions towards Robotic Automation (RA) investments
1. Robotics Automation Opportunity Prioritization Basis Insights from Fortune 500 Enterprises
2. Zinnov Framework for Automation Maturity-assessment of Enterprises (Z-FAME)
3. Assessment of Robotics Automation Service Providers 4. Assessment of Robotics Automation Platform Providers
Zinnov tracks the digital deals including Robotics
automation of Fortune 500 enterprises, prioritizing use
cases by verticals and in terms of intensity of
implementation
Zinnov publishes its annualRobotics Automation ZinnovZones rating of leading globalservice providers in terms oftheir RA prowess andscalability
Zinnov offers Z-FAME, a four stagedframework enabling enterprises to -1.Identify RA use-cases by verticals2.RA assets (tools used, type of
bots, etc.)3.Service Provider Competencies
(service provider relationships,consulting/ advisoryrequirements)
4.Internal Capability & Governance(COE)
Zinnov has alsoevaluated technologyplatforms, prowess,and features of leadingRA tool vendors likeAutomation Anywhere,Blueprism, etc
Zinnov Proprietary Confidential
5
Agenda
1 About Zinnov
2Robotic Automation (RA)
Landscape
3Enterprise Engagements with RA
Services Providers
4 Zinnov Zones for RA Services
6
Robotic Automation (Cognitive)
Robotic Automation (Rule Based)
Traditional Automation(Script based)
Robotic Automation (RA) involves use of software bots for automation of Business & IT processes
Source: Zinnov Research and Analysis, Deloitte
Evolution of Robotic Automation
Platform specific/ runs on data layer
Manual exception handling
Coding skills required
Platform agnostic and runs on UI layer
Manual exception handling
Coding skills typically not required
Platform agnostic and runs on UI layers
Learns to handle exceptions over time; intelligent decision making
enabled by ML algorithm
Coding skills typically not required
Quality & Compliance ScalabilityLower Cost of
OperationsEfficiency Gains
1 2 3 4
Deployment of robots reducesthe total cost of operations
Robots typically work 2x-3xfaster than humans; robots alsowork round the clock
Robots work at a significantlyhigher accuracy levels comparedto humans (~100%) and ensurecompliance
Scalable deployments acrossfunctions, business units andgeographies
Drivers for Growth in Robotic Automation Adoption
Redeployment of people from mundane processes
5
Implementation of RA leads toup-levelling of workforce todecision-making roles
Structured
Semi-structured
Unstructured
Data Type
Structured
Semi-structured
Unstructured
Data Type
Structured
Semi-structured
Unstructured
Data Type
7
Enterprises currently spend over $1.5 Bn in RA; both business & IT processes present significant investment potential
Source: NASSCOM, Gartner, Forrester, Zinnov Analysis
USD1,305Bn ~USD 41Bn
Total IT-BPM Services Spend
RA Addressable Opportunity
USD 1.5-1.8Bn USD 6.5Bn
Current RA Spend includes POC, design, development, integration, maintenance and support of RA
implementation as well as resources, infrastructure & tools leveraged for
research & training purposes
Estimated 2020 RA Spend at 60% CAGR
Total Addressable and Realized Market for Robotic Automation (FY2017)
Segmentation of Addressable Robotic Automation Market
>USD 19Bn
Business Processes
>USD 11 Bn >USD 11 Bn
Infrastructure Mgmt Processes ADM/SI Processes
By Type of Enterprise Process
8
Insurance
BFS, Insurance, Telecom and Retail verticals top the chart on adoption of Robotic Automation
Notes: *Others include Healthcare, Media & Entertainment, Public Sector, Professional Services, etc.; RA Addressable Opportunity based on vertical market size, penetration of BPO-IT services in the vertical, conduciveness of processes to robotic automationSource: Zinnov Analysis, Company websites, case studies, news articles, press releasesFNOL- First Notice of Loss, EMR- Electronic Medical Records
Banking & Finance
Retail Manufacturing Others*
Segmentation of Robotic Automation Market Based on Industry Verticals With Use Cases and Case Studies
Telecom
Illustrative Use Cases Illustrative Use Cases Illustrative Use Cases Illustrative Use Cases Illustrative Use Cases Illustrative Use Cases
E-form extraction & making system entries
Tax reporting
Compliance and credit checks
FNOL submission handling
Customer onboarding Password reset
Loyalty program management
Payments processing
Order management Incident management
Payroll administration Vendor management
Customer Onboarding
Managing applications for loan applications and
automation of account opening
Actuarial Operations
Process automation in the actuarial modelling
operations
Customer Management
Front and back office automation for better
customer experience and reduced operational costs
Invoice Handling
Workflows related to invoice handling including
creating entries in the ERP system
Procurement & SCM
Automation of processes in General Motors Global
Procurement & SCM process using Xerox
Automated Intelligence
EMR Integration
Integration of data from various applications into
one common EMR application
9
Enterprises across verticals have a potential to adopt RA across a spectrum of IT & Business processes
Zinnov Analysis
Workload Category
Trade Processing
Reconciliation
Internal Accounting
KYC/AML
Data Management
Collections & Recoveries
Corporate Reporting
Lending Operations
Workload Category
Finance & Accounting
IT Support
Claims Processing
Corporate Reporting
Transaction Processing
Product Management
Underwriting System
Customer Engagement
Workload Category
Finance & Accounting
Corporate Reporting
Procurement
IT Support
Sales Management
Corporate Planning
Logistics & Distribution
Inventory Management
Workload Category
Server Management
Operations Support
Network Management
Database Management
Data Centre Management
End User Services
Security Management
Virtualization
Middleware
Cloud Support
Workload Category
Post Implementation Support
Application Testing
Deployment/ Release Management
Application Integration
Application Migration
Data Migration
Performance Testing
Banking & Capital Markets
Insurance Retail
Workload Category
Order Management
Billing
Assurance
Customer onboarding
Order fallouts
Data consolation and reporting
Complaints resolution
Password reset
Telecom
Priority Use-cases
Decreasing focus of enterprises on use cases
10
RA use case priorities are based on the value they generate and relative ease of their deployment
Source: Primary Interactions with Industry Experts, Zinnov Analysis
Value Generated (1-5)[Cost Savings | Efficiency | Quality & Compliance]
Ease
of
De
plo
yme
nt
(1-5
)[S
cala
bili
ty|
Ease
of
Wo
rkfo
rce
Red
eplo
ymen
t]
Assessment of Top RA Use-cases: Benefits to Enterprise & Ease of Deployment
Trade Processing (Banking & Capital Markets)
Reconciliation(Banking & Capital Markets)
Internal Accounting(Banking & Capital Markets)
Finance & Accounting (Insurance, Retail)
IT Support(Insurance)
Claims Processing(Insurance)
Order Management (Telecom)
Billing(Telecom)
Assurance(Telecom)
Corporate Reporting(Retail)
Procurement(Retail)
Server Management
Operations Support
Network Management
Post Implementation Support
Application Testing
Deployment/ Release Management
2
2.5
3
3.5
4
4.5
2 2.5 3 3.5 4 4.5 5
BPO IMS ADM
FOR ILLUSTRATIVE
PURPOSE ONLY
11
New age automation platforms are enabling rapid adoption of RA technology within enterprises
Other RATool Vendors
Source: Company websites, Zinnov Analysis
Offerings
Global Platform Talent Base
Focus Verticals
Cognitive Capability
CompanyInformation
Illustrative Clients
800-900
Banking, Insurance, Energy, IT, Healthcare,
Manufacturing
Medium
Founded: 2003HQ: San Jose, USA
350-450
Banking, Insurance, BPO, Telecom, IT, Retail
Low
Founded: 2012HQ: Bucharest, Romania
Blue Prism Virtual Workforce Platform
1100-1300
BPO, Telecom, Utilities, Energy, Healthcare, Banking, Insurance
Low
Founded: 2001HQ: London, UK
200-300
Banking, Insurance, Healthcare,
Manufacturing, Media
High
Founded: 2010HQ: New York, USA
WorkFusion Smart Process Automation Platform
WorkFusionRPA Express
WorkFusionChatbots
3300-3800
Banking, Insurance, Retail, Healthcare,
Utilities
High
Founded: 1998HQ: New York, USA
12
Further, the advent of intelligent automation along with business model transformations is driving the growth momentum
5. Demand concentrationNorth America accounts for more than half of the RA market and Europe for another one-third. Also, large
enterprises constitute more than 70 % of the market
3. Free tools?
RA market may follow the “Free Basic” Route, with the minimum enabling tool being available for free
e.g. WorkFusion made their basis RA offering free for enterprises
Technology vendors such as IPsoft have white-labelled their products (IPcenter) allowing SPs like IBM, Cisco, etc.
to create their respective automation offerings
6. Whitelabeling of products
1. Intelligent automationIntelligent Robots is the next frontier of RA. Companies already deploying robots with cognitive and AI abilities (ML, NLP, NLG) for complex workloadse.g. UBS using AI to identify behavioural information from unstructured data sets to show relevant wealth management products to customers
Enabled by APIs, robots are expected to come inbuilt to automate relevant most common deterministic workloade.g. Pega acquired OpenSpan - Combination brings robotics and analytics capabilities to their core - case management
2. Robots pre-built in enterprise software
4. Centralized control and monitoring
Bot Farms being created which help scale up or scale down bots as per demand
e.g. BotsInsight from Automation Anywhere for real time analytics; WorkFusion offers controls to make
changes and deployment
Key Trends in RA Market
13
Agenda
1 About Zinnov
2 Robotic Automation (RA) Landscape
3Enterprise Engagements with RA
Services Providers
4 Zinnov Zones for RA Services
14
Enterprises spent over $160 Mn in FY 2017 with external service providers around their RA deployments
Source: Zinnov Research and Analysis
End to end streamlining of RA strategy• Defining RA governance and operating model• Complete outsourcing vs CoE setup• Process discovery and re-engineering• Tool vendor selection
Design and Consulting
Customization, Development, System Integration and Deployment• Defining the right architecture frameworks • Scripting of automation processes• Testing & deployment of software robots
System Integration and development
Managed Services, Support and Maintenance• Ensuring working of software• Updating software, if required• Create any new automations/ scale previous
automations• Maintain database and provide insights
Managed servicesEnterprise
Spend on RA(FY2017 E)
RA Services Sourced by Enterprises
(FY2017 E)
USD 1.5-1.8Bn USD 160-180Mn
$ 20-25 Mn
$110-115 Mn
$35-40 Mn
15
RA services investments by enterprises are largely limited to the top 20 RA service providers
Source: Zinnov Analysis
% S
har
e o
f O
uts
ou
rce
d m
arke
t
Number of SPs in decreasing order of RA revenues
10 3020 40 100
Top 10 –65%
Next 10–20%
Rest– 15%
50 60 70 80 900%
10%
20%
Market Share of SPs in Outsourced Robotic Automation
16
Large deals on RA engagements between customers & services providers are beginning to happen
Source: Zinnov Analysis
>55%
>35%
>10%
<USD 500K USD 501K-2Mn USD 2Mn+
• Large tier companies are focusing on expansion of RA practice by leveraging their huge customer portfolio, in addition to pure play automationdeals.
• Small and mid-tier service providers are giving more emphasis to end-to-end execution and implementation of RA engagements across allservice lines.
Segmentation of RA deals by category of service provider
84%
16%
USD 501K - USD 2 Mn
84%
16%
USD 2Mn+
Legend:
Large tier Service Providers
Small & mid tier Service Providers
81%
19%
<USD 500K
By Volume - Overall
% Split of Customer Deals by Average RA Deal Size (Overall)
82%
18%
Large tier SPs
Small & Mid tier SPs
17
BFSI, insurance, telecom and retail customers show more affinity towards RA service providers
Source: Zinnov Analysis
38%
15%
17%
8%
7%
2%
9%
% Split of RA revenue
30%
21%11%
6%
6%
5%
21%
% split of RA customers
Banking and Financial Services
Insurance Telecom Retail ManufacturingMedia and Entertainment
Others
Service Provider RA Business – Segmentation by Verticals
Average Revenue Contribution by RA Customers
Industry VerticalAverage Revenue per
Customer ($ Mn)
Telecom 1.1
BFS 0.9
Retail 0.8
Manufacturing 0.8
Insurance 0.5
Media & Entertainment 0.3
Others 0.3
18
Outcome based engagement models are gaining tremendous traction as enterprises look to maximise their RA investments with service providers
Source: Zinnov Analysis
55% of robotic automation deals were outcome based as compared to 1% of overall digital
Types of Engagement Models
Drivers for Adoption of Outcome Based Models in RA
FTE based pricing less relevant with RA
Safeguarding against technology upgrades
Ease of defining outcomes for RA relevant processes
Gain Share Model- Gains above the baseline level would be shared between the client and theservice provider for a period of time.
Risk Reward Model- Joint innovation for solutions between client and vendor attenuates the riskand the reward is shared according to pre-defined terms.
Transaction Based Model- Vendor fee is defined based on the number of transactions throughthe process.
Outcome Based Models
Traditional Models- include FTE based pricing, fixed price models and T&M based pricing. Otherinnovative input based models including core/flex models are also used for RA engagements.
Traditional Models
Overall Digital Robotic Automation
99%
45%
1%
55%
Percentage Split of Customer Deals based on Type of Engagement Model
Traditional Models Outcome based models
19
Drivers for these platforms
• Bridging gaps in commercially available proprietary platforms
Vertical specific Ease of configuration Focus on front office use cases
• Increasing wallet share with license revenue
3. Partnerships with Start-ups
Service Providers are starting to make investments towards increasing their RA capabilities
Source: Zinnov Research and Analysis
Partnerships Intellectual Properties (IPs)Digital Labs & Centers of
Excellence
SPs are partnering with RA tools andtechnology vendors as well as startups
SPs are investing in building in-houseautomation platforms and cognitive solutionsas well
SPs also building CoEs for delivery excellenceand Digital Labs for development of new RAtechnologies
1. Tool Vendors
2. Partners for Cognitive Technologies
87%SPs partnering with one of the following tool vendors to leverage their RA platforms.
67%SPs preferring IBM Watson for cognitive automation
SPs partnering with startups for niche technologies like OCR, chatbots, handwriting recognition etc.
Multiple SPs have built / are building their own automation platforms.
Illustrative list
Wipro leveraging Avaamo for its business chatbots
SPs are focusing on building three types of CoEs
Design & Conceptualisation
Certification & Training
Support & Sustenance
SPs are building R&D Labs focused on emerging technologies like AI, ML, IoT, etc.
Artificial Intelligence (AI) focused R&D lab in Dublin, Ireland
9000 Approximate global strength of employees in RA CoEs
Infosys Automation Platform
Decreasing popularity amongst SPs
1.RA delivery- with governance, assessment and implementation teams
2.Collaboration with vendors- Dedicated centres for collaboration with vendors such as Openspan, IPSoft, etc.
3.RA CoE as a service offering- setting up RA CoE for customers
20
Building strong RA talent base is a key focus area for service providers
Knowledge of vertical business processes
Enterprise architecture frameworks- Zachman,
TOGAF, etc.
Automation tools (Blue Prism, etc.) and scripting
languages75%
11%
14%
Ability to identify processes to be
automated; six sigma certifications
Experience in programming (VB, C#, .Net, C++, etc.)
Programming, basic Java or .Net)
OCR and DMS tools knowledge (Kofax, EMC,
Documentum)
Experience with information solutions and
products
Sources: Zinnov AnalysisNotes: ML- Machine Learning, NLP- Natural Language Processing, GETs- Graduate Engineer Trainees, SPs- Service Providers
Creation of process design documents, technical
design documents
• SPs are building talent in-house, by identifying core capability teams and/ or hiring GETs
• SPs are training them in scripting and in ML, NLP, etc. through boot camps and induction programs, generally lasting 3-6 months
• SPs also partner with tool vendors such as Blue Prism, Thoughtonomy, etc. for their training/ accreditation programs with certifications for RA talent. Eg- Blue Prism Accreditation
Initiatives for Robotic Automation Talent Building
Segmentation of Existing RA Talent
Key SkillsMarket Talent
AvailabilityService Provider Focus on Skill Development
Types of Roles
Domain Experts/ Process Analysts
Solution Architects
Developers/ Testers
21
Agenda
1 About Zinnov
2 Robotic Automation (RA) Landscape
3Enterprise Engagements with RA
Services Providers
4 Zinnov Zones for RA Services
22
Future Outlook
Scalability of RA Business
Positioning reflects the scores in Prowess and Scalability
Scale of Business
RA Clientele
RA Capabilities
Innovation Ecosystem
Value Added BusinessModels
RA Prowess
RA Talent
Zinnov Zones for RA Services 2017: Framework
RA Prowess RA Scalability2Zinnov evaluated participating service providers on two key areas basis which they
were plotted on a 2-dimensional graph
The cumulative score of enterprises based on RA Prowess (x value) and Scalability in RA business (y value) was used to classify service providers in Zinnov Zones framework
1
23
RA Prowess Parameters
RA Capabilities
Innovation Ecosystem
Value Added
Business Models
Degree of utilization of partnerships with start-ups, technology platforms, academic universities and research institutes | Strength of digital innovation including set up of RA specific digital labs and Centres of Excellence
Ability to deliver across business models: T&M, Fixed Price and Outcome based models | Innovation in Engagement Models
Leveraging RA IPs, tools, frameworks across various verticals| Effectiveness and maturity of RA IPs in driving value to customers | Capacity of delivering RA services across service lines | Abundance and mix of RA talent | Average experience of talent
Value Addition to business by cost and time savings | Improvements in accuracy of processes
Cumulative Score on the RA Prowess parameters defines the horizontal position of Service Providers in Zinnov Zones framework
Prowess is estimated considering six key parameters:
Future Outlook Focus on new logo acquisition and strategic partnerships | Measures to expand in new geography | Innovation in new talent hiring/ development practices | Future R&D focus
24
Scalability Parameters
Scalability has been broken down into three key parameters-
Scale of RA Business
RA Clientele
Total Revenue across RA business across the verticals | Breadth of processes automated and software robots deployed
Width of RA client portfolio | Spread of marquee clients and large value accounts within the RA clientele
Cumulative Score on the Scalability parameters defines the vertical position of Service Providers in Zinnov Zonesframework
RA Talent RA talent abundance
25
EPAM
EXL
HCL
Hexaware
L&T Infotech
Mphasis
Syntel
TCS
Tech Mahindra
VirtusaPolaris
Wipro
WNS
Zensar
Genpact
Intelenet
Xoriant
Atos
Tieto
IBMAccenture
Capgemini
Source: Data shared by participant companies, Zinnov Research
Zinnov Zones for RA Services
Nurture Zone Breakout Zone Execution Zone Leadership Zone
Scal
abili
ty (
Clie
nts
, Tal
ent,
Fin
anci
als)
Overall Ratings
High
Low HighRA Prowess (Offerings, Innovation Ecosystem, Value Added, Business Models, Future Outlook)
Full Participation by Service Providers
Partial/No Participation by Service Providers
26Source: Data shared by participant companies, Zinnov Research
Zinnov Zones for RA Services
Nurture Zone Breakout Zone Execution Zone Leadership Zone
Scal
abili
ty (
Clie
nts
, Tal
ent,
Fin
anci
als)
BFS Ratings
High
Low HighRA Prowess (Offerings, Composition of Clients, Talent)
EPAM
EXL
HCL
Intelenet
L&T Infotech
Mphasis
Syntel
TCS
Tech Mahindra
VirtusaPolaris
Wipro
ZensarXoriant
Atos
Tieto
Genpact Accenture
IBM
Capgemini
Full Participation by Service Providers
Partial/No Participation by Service Providers
27Source: Data shared by participant companies, Zinnov Research
Zinnov Zones for RA Services
Nurture Zone Breakout Zone Execution Zone Leadership Zone
Scal
abili
ty (
Clie
nts
, Tal
ent,
Fin
anci
als)
Insurance Ratings
High
Low High
EXL
HCL
Intelenet
L&T InfotechMphasis
SyntelTCS
Tech Mahindra
VirtusaPolaris
Wipro
WNS
Zensar
Atos
Genpact
AccentureIBM
Capgemini
RA Prowess (Offerings, Composition of Clients, Talent)
Full Participation by Service Providers
Partial/No Participation by Service Providers
28Source: Data shared by participant companies, Zinnov Research
Zinnov Zones for RA Services
Nurture Zone Breakout Zone Execution Zone Leadership Zone
Scal
abili
ty (
Clie
nts
, Tal
ent,
Fin
anci
als)
Retail Ratings
High
Low HighRA Prowess (Offerings, Composition of Clients, Talent)
HCL
Intelenet
L&T Infotech
TCS
Tech Mahindra
VirtusaPolaris
Wipro
Zensar
Accenture
IBM
Capgemini
Genpact
Atos
Full Participation by Service Providers
Partial/No Participation by Service Providers
29Source: Data shared by participant companies, Zinnov Research
Zinnov Zones for RA Services
Nurture Zone Breakout Zone Execution Zone Leadership Zone
Scal
abili
ty (
Clie
nts
, Tal
ent,
Fin
anci
als)
Telecom Ratings
High
Low High
Full Participation by Service Providers
Partial/No Participation by Service Providers
RA Prowess (Offerings, Composition of Clients, Talent)
HCL
IntelenetL&T Infotech
TCS
Tech Mahindra
VirtusaPolaris
Wipro
Atos
Genpact
Accenture
IBM
Capgemini
30
Disclaimer
Zinnov Proprietary Confidential
In the context of Zinnov Zones for RA, we reached out to a limited set of service providers that could be potential leaders inthis space. Our set of inclusion criteria enables us to shortlist, effectively based on which service providers are invited toparticipate. While we normally see significant interest in participation, sometimes a service provider may request to beexcluded from the Zinnov Zones activity if the timing of the research or circumstances within the service providerorganization makes participation difficult. If a service provider declines to participate at the beginning of a Zinnov Zonesprocess, it is important to know the following policies:
Some non-participating service providers are still included in our evaluationo As we invite only leading service providers and emerging players to participate in Zinnov Zones, if a service
provider decides not to participate, we have still included them in the final report if we think it is necessaryo Our reasoning is that Zinnov Zones without a leading service provider would project a partial picture of the market
and make it less pertinent for our clients
The Zinnov Zones report clearly differentiates service providers that did not undergo the same rigorous evaluation as its peerso While our analysts have evaluated the service providers that declined to participate, the service provider’s place in
the ratings is denoted by a differentiating symbol indicating non-participation in the research processo Their assessment is based on different inputs than those used for evaluating its peers
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