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Zinnov Zones for Robotic Automation Services

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Zinnov Zones for Robotic Automation Services

  1. 1. 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. 2. 2 Agenda 1 About Zinnov 2 Robotic Automation (RA) Landscape 3 Enterprise Engagements with RA Services Providers 4 Zinnov Zones for RA Services
  3. 3. 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 & Semiconductor BFSI Retail 14Years 200 Customers 160Consultants 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 Solutions Industrial Service Providers| Vendors
  4. 4. 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 annual Robotics Automation Zinnov Zones rating of leading global service providers in terms of their RA prowess and scalability Zinnov offers Z-FAME, a four staged framework enabling enterprises to - 1.Identify RA use-cases by verticals 2.RA assets (tools used, type of bots, etc.) 3.Service Provider Competencies (service provider relationships, consulting/ advisory requirements) 4.Internal Capability & Governance (COE) Zinnov has also evaluated technology platforms, prowess, and features of leading RA tool vendors like Automation Anywhere, Blueprism, etc Zinnov Proprietary Confidential
  5. 5. 5 Agenda 1 About Zinnov 2 Robotic Automation (RA) Landscape 3 Enterprise Engagements with RA Services Providers 4 Zinnov Zones for RA Services
  6. 6. 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 Scalability Lower Cost of Operations Efficiency Gains 1 2 3 4 Deployment of robots reduces the total cost of operations Robots typically work 2x-3x faster than humans; robots also work round the clock Robots work at a significantly higher accuracy levels compared to humans (~100%) and ensure compliance Scalable deployments across functions, business units and geographies Drivers for Growth in Robotic Automation Adoption Redeployment of people from mundane processes 5 Implementation of RA leads to up-levelling of workforce to decision-making roles Structured Semi-structured Unstructured Data Type Structured Semi-structured Unstructured Data Type Structured Semi-structured Unstructured Data Type
  7. 7. 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. 8. 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 automation Source: Zinnov Analysis, Company websites, case studies, news articles, press releases FNOL- 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. 9. 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. 10. 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] EaseofDeployment(1-5) [Scalability|EaseofWorkforceRedeployment] 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. 11. 11 New age automation platforms are enabling rapid adoption of RA technology within enterprises Other RA Tool Vendors Source: Company websites, Zinnov Analysis Offerings Global Platform Talent Base Focus Verticals Cognitive Capability Company Information Illustrative Clients 800-900 Banking, Insurance, Energy, IT, Healthcare, Manufacturing Medium Founded: 2003 HQ: San Jose, USA 350-450 Banking, Insurance, BPO, Telecom, IT, Retail Low Founded: 2012 HQ: Bucharest, Romania Blue Prism Virtual Workforce Platform 1100-1300 BPO, Telecom, Utilities, Energy, Healthcare, Banking, Insurance Low Founded: 2001 HQ: London, UK 200-300 Banking, Insurance, Healthcare, Manufacturing, Media High Founded: 2010 HQ: New York, USA WorkFusion Smart Process Automation Platform WorkFusion RPA Express WorkFusion Chatbots 3300-3800 Banking, Insurance, Retail, Healthcare, Utilities High Founded: 1998 HQ: New York, USA
  12. 12. 12 Further, the advent of intelligent automation along with business model transformations is driving the growth momentum 5. Demand concentration North 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 automation Intelligent Robots is the next frontier of RA. Companies already deploying robots with cognitive and AI abilities (ML, NLP, NLG) for complex workloads e.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 workload e.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. 13. 13 Agenda 1 About Zinnov 2 Robotic Automation (RA) Landscape 3 Enterprise Engagements with RA Services Providers 4 Zinnov Zones for RA Services
  14. 14. 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 services Enterprise 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 $35-40 Mn
  15. 15. 15 RA services investments by enterprises are largely limited to the top 20 RA service providers Source: Zinnov Analysis %ShareofOutsourcedmarket Number of SPs in decreasing order of RA revenues 10 3020 40 100 Top 10 – 65% Next 10– 20% Rest– 15% 50 60 70 80 90 0% 10% 20% Market Share of SPs in Outsourced Robotic Automation
  16. 16. 16 Large deals on RA engagements between customers & services providers are beginning to happen Source: Zinnov Analysis >55% >35% >10% <USD 500K USD 501K-2Mn USD 2Mn+ • Large tier companies are focusing on expansion of RA practice by leveraging their huge customer portfolio, in addition to pure play automation deals. • Small and mid-tier service providers are giving more emphasis to end-to-end execution and implementation of RA engagements across all service lines. Segmentation of RA deals by category of service provider 84% 16% USD 501K - USD 2 Mn 84% 16% USD 2Mn+ Legend: Large tier Service Providers Small & mid tier Service Providers 81% 19% <USD 500K By Volume - Overall % Split of Customer Deals by Average RA Deal Size (Overall) 82% 18% Large tier SPs Small & Mid tier SPs
  17. 17. 17 BFSI, insurance, telecom and retail customers show more affinity towards RA service providers Source: Zinnov Analysis 38% 15% 17% 8% 7% 2% 9% % Split of RA revenue 30% 21% 11% 6% 6% 5% 21% % split of RA customers Banking and Financial Services Insurance Telecom Retail Manufacturing Media and Entertainment Others Service Provider RA Business – Segmentation by Verticals Average Revenue Contribution by RA Customers Industry Vertical Average Revenue per Customer ($ Mn) Telecom 1.1 BFS 0.9 Retail 0.8 Manufacturing 0.8 Insurance 0.5 Media & Entertainment 0.3 Others 0.3
  18. 18. 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 the service provider for a period of time. Risk Reward Model- Joint innovation for solutions between client and vendor attenuates the risk and the reward is shared according to pre-defined terms. Transaction Based Model- Vendor fee is defined based on the number of transactions through the process. Outcome Based Models Traditional Models- include FTE based pricing, fixed price models and T&M based pricing. Other innovative 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. 19. 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 and technology vendors as well as startups SPs are investing in building in-house automation platforms and cognitive solutions as well SPs also building CoEs for delivery excellence and Digital Labs for development of new RA technologies 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. 20. 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 languages 75% 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 Analysis Notes: 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 Skills Market Talent Availability Service Provider Focus on Skill Development Types of Roles Domain Experts/ Process Analysts Solution Architects Developers/ Testers
  21. 21. 21 Agenda 1 About Zinnov 2 Robotic Automation (RA) Landscape 3 Enterprise Engagements with RA Services Providers 4 Zinnov Zones for RA Services
  22. 22. 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  Business Models RA Prowess  RA Talent Zinnov Zones for RA Services 2017: Framework RA Prowess RA Scalability2 Zinnov 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. 23. 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. 24. 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 Zones framework  RA Talent RA talent abundance
  25. 25. 25 EPAM EXL HCL Hexaware L&T Infotech Mphasis Syntel TCS Tech Mahindra VirtusaPolaris Wipro WNS Zensar Genpact Intelenet Xoriant Atos Tieto IBM Accenture Capgemini Source: Data shared by participant companies, Zinnov Research Zinnov Zones for RA Services Nurture Zone Breakout Zone Execution Zone Leadership Zone Scalability(Clients,Talent,Financials) Overall Ratings High Low High RA Prowess (Offerings, Innovation Ecosystem, Value Added, Business Models, Future Outlook) Full Participation by Service Providers Partial/No Participation by Service Providers
  26. 26. 26Source: Data shared by participant companies, Zinnov Research Zinnov Zones for RA Services Nurture Zone Breakout Zone Execution Zone Leadership Zone Scalability(Clients,Talent,Financials) BFS Ratings High Low High RA 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
  27. 27. 27Source: Data shared by participant companies, Zinnov Research Zinnov Zones for RA Services Nurture Zone Breakout Zone Execution Zone Leadership Zone Scalability(Clients,Talent,Financials) Insurance Ratings High Low High EXL HCL Intelenet L&T InfotechMphasis Syntel TCS 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
  28. 28. 28Source: Data shared by participant companies, Zinnov Research Zinnov Zones for RA Services Nurture Zone Breakout Zone Execution Zone Leadership Zone Scalability(Clients,Talent,Financials) Retail Ratings High Low High RA 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
  29. 29. 29Source: Data shared by participant companies, Zinnov Research Zinnov Zones for RA Services Nurture Zone Breakout Zone Execution Zone Leadership Zone Scalability(Clients,Talent,Financials) Telecom Ratings High Low High Full Participation by Service Providers Partial/No Participation by Service Providers RA Prowess (Offerings, Composition of Clients, Talent) HCL Intelenet L&T Infotech TCS Tech Mahindra VirtusaPolaris Wipro Atos Genpact Accenture IBM Capgemini
  30. 30. 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 in this space. Our set of inclusion criteria enables us to shortlist, effectively based on which service providers are invited to participate. While we normally see significant interest in participation, sometimes a service provider may request to be excluded from the Zinnov Zones activity if the timing of the research or circumstances within the service provider organization makes participation difficult. If a service provider declines to participate at the beginning of a Zinnov Zones process, it is important to know the following policies:  Some non-participating service providers are still included in our evaluation o 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 necessary o 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 peers o 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 process o Their assessment is based on different inputs than those used for evaluating its peers
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