Презентация ppt_watson_final.pdf

December 2014 The Strategy of enabling IBM Watson for public sector in Russia IBM Watson & GSOM Consulting Project ANTINORI Leonardo DE GAVRE Guillaume HONKAMAA Susanna LEPEKHINA Kristina REPP Sergej

2 Project Overview Literature review Potential of Cognitive Computing in the Public Sector Stages of development of E-government in Russia Market Analysis Pestle Analysis for Russian Public Sector Russian IT Market current situation and future trends Competitors Analysis SWOT/TOWS Resource-based View Strategic Discussion Recommendations Fields of Implementation Potential Partners Agenda

3 Quick project overview We were assigned to this project on September 19 th , 11 weeks ago Regular communication round with Mikhail Lobotskiy (2 -week intervals) Valuable insights provided by our Academic Advisor / Course Coordinator / Career Center etc. Meanwhile, we led 11 interviews With 7 IBMers and with 4 external IT program managers Preparing customized questionnaires in English and in Russian Literature review and market research Around 100 academic papers, reports, IBM presentations or conference minutes, books More than 50 companies analyzed as potential competitors or partners. . . A few difficulties faced Resignation of 1 of our team members Difficulties with access to our school resources Academic deadlines not always in line with the course of our project Limits of our research Difficulties to find interviewees for a second round Diversity of Watson portfolio; limited availability of use-cases due to breakthrough technologies Difficulty to be coherent between unavailability of ”Ask Watson” in Russian and our recommendations

4 Literature review

5 Cognitive computing market trend Source: (Marketsand. Markets 2013) Natural Processing Language market size and growth 0%5%10%15%20%25%30% 0123456789102013 2014 2015 2016 2017 2018 Revenue ($) Year-on-year growth (%) US$bn CAGR=21, 1%

6 Cognitive computing market trend Natural Processing Language market size and growth by user Source: (Marketsand. Markets 2013) 00, 5 11, 5 22, 5 3 2014 2015 2016 2017 2018 Healthcare Defense Education US$bn CAGR=20, 1%CAGR=23, 7% CAGR=14, 0%

7 Catalogue Transaction Vertical integration Horizontal integration Four stage model of development in E-government Technologicalandorganizationalcom plexity. C om plex Sim ple Integration. Sparse Complete Source: (Layne&Lee 2001)

8 Market analysis

9 PESTL Analysis: the Russian Public Sector Dimension Issue Impact on Business Political • Public sector is driving the innovation • Lack of transparency in decision making process. • Increasing interest in E-government processes. • Network/Strong long-term partnerships required. Economic • Dependence of economy on natural resources. • Lower government expenditure due to oil price and exchange rate. Social/Cultural • Citizens awareness, changing expectations. • More efficient and clear decision-making process, less bureaucracy. Technological • High demand in the Russian IT market • Increasing of revenue, quality of service, productivity and efficiency Legal • Changes to privacy law; • Every corporation that has already collected personal data about Russian consumers, employees or third-party partner, should move its IT technology infrastructure to a data center located on the territory of the Federation. • Data location requirement is going to adversely affect the collection, provision, exchange and efficient use of up-to-date information; • Corporations should immediately start facing the issue and evaluating options in order to meet new legal requirements and restrictions.

10 Russian IT market current situation

11 Breakthrough technological trends Artifi cial intelligence and cognitive technologies; Human-machine interface; Big data and supercomputers; Computer vision; Information security; Bio-informatics. Market niches for IT products and services Cloud computing; Big data; The Internet of Things; Digital manufacturing; Mobility; Cyber security. Russian IT market expected evolution

12 Russian and international IT companies with Russian origins based on promising technological and market trends Company name Strategy Breakthrough R&D + a systemic approach to developing new markets Innovative developments + the strategy of building a very profitable billion-dollar business Game as a Business + Business as a Game with Constantly Changing Rules Industry competencies + innovative developments A “convenient” product + technological innovations Key business direction: • Software for Optical Character Recognition (Fine. Reader) and the software development kits (SDK) • Solutions for automated document capture • Products and services within the sphere of translation and linguistics (Lingvo, ABBYY, Language Services) • Solutions based on a technology for the comprehension, analysis and translation of texts in natural languages (ABBYY Compreno – technological platform for solutions in intellectual search, documents classification, translation, and e. Discovery etc. ) • Developing solutions for data backup, emergency recovery and protection • Developing solutions for data management for mobile devices • Developing and publishing games for the mass audience of users (casual and mid-core games) for mobile platforms, game consoles and PCs • Game distribution through its own and partner sites • Creation and development of new brands within the game industry • Custom software development • Software product integration • Software testing and audit • Software support and technical maintenance • Dedicated software development centers • Technological and business consulting • IT personnel recruiting and outstaffing • Engineering software development: computer aided design system (CAD system), geometric kernel of 3 D- modeling, systems for engineering data and product life-cycle management (PLM), project design work management systems, and production planning and management systems • Complex automation for pre- production and production management in the engineering industry • Complex automation for design operations in industrial and civil construction

13 Russian and international IT companies with Russian origins based on promising technological and market trends Company name Strategy Outsourcing + industry markets with high growth potential Forming the new technological niche + global partnership Venture investments + (physical + digital) New markets + a systemic approach to their development Consumer segmentation + international markets expansion Key business direction: • Software development • Software support • IT solutions re-engineering, migration and porting • Software integration • Independent software testing • Technological research and software consulting • Instruments for developing an interactive 3 D/2 D catalog of parts, repairs and maintenance guides, and training courses — Rapid. Author • Integrating instruments for creating 3 D/2 D documents with Teamcenter, a product life cycle management system • Professional editor of 2 D images in the CGM format — the Cortona 2 D Editor Pro • Interactive browsers for viewing 2 D/3 D data in different platforms — the Cortona 3 D Viewers • Venture investments in the field of personal robotics, including: wearable and connected devices, and Io. T (Internet of things), etc. • Developing and implementing ERP systems for restaurant business automation (iiko. RMS, and iiko. Chain) • Complex services for restaurant automation and restaurant networks (installing and tuning up equipment; educating and certifying users) • Solutions for delivery automation (iiko. Delivery) • Creating and implementing a platform for organizing mobile social loyalty programs (iiko. net) • Special solutions (controlling current orders, and analyzing operational indicators, etc. ) • Software development for client service optimization

14 Company name Strategy Corporate venture investment + competence synergy Industry segmentation + expansion into international markets In-house innovations + success replication Industry expertise + turnkey integration Universal proposal + network scaling New markets + doing business at industry junctions Key business direction: • Venture investment s in the high tech sector. Target market segments — IT and telecommu nications • Customized software development • The Company’s own product solutions • IT solutions and engineering • Built-in systems development • Independent testing • Technological consulting • IT personnel recruiting and IT training • Management consulting, IT consulting • Business processes automation systems • IT systems infrastructure • Information security systems • Technical safety systems • IT outsourcing and technical maintenance • IT personnel and business processes outsourcing Corporate software for lease • Smart city solutions • IT and management education programs • Software development and adaptation • CAD systems, GIS systems and PLM systems development and implementation • IT standards and concepts development, consulting • Creation of information models and spherical panoramas of industrial objects • IT engineering of design works • Engineering services — equipment design, development, production, installation, commissioning and start up • Payment receipt via terminals and kiosks • Services based on the virtual prepaid card • Advertising • Payment processing via kiosks, points of payment receipt and electronic wallets • Retail sales of software through the Company’s own online supermarket • Software distribution via the Internet • Affiliate program (Softkey catalog placement on partner websites) • Order processing (service for developers —sales on the Softkey trade site) • Software distribution in household appliances and electronics networks via terminals • Online software supermarket for mobile device users (Softkey, and Mobi) • A communications site and online expertise center for consumers, developers, experts and sellers (IT 4 all. ru) • Specialized resource for Saa. S promotion (Point 4 all. ru) Russian and international IT companies with Russian origins based on promising technological and market trends

15 Company name Strategy Universal Solutions + Entering the Global Market Strong position in Russia’s IT industry + creating instruments for the global market Russian innovation + market niche in competitive environment Key business direction: • Development and licensing of software (engines) for voice and video transmission via IP networks • Creation of software for HD multi-point Internet video conferences • A provider of cloud services for exchanging electronic documents with contractors, governmental and regulatory organizations. One of Russia’s largest certification authorities • Development and manufacturing of high-tech telecommunications LTE- equipment: • Yota. Phone — the first in the world smartphone with two screens, one of which is always on • Yota. Ruby — portable Wi. Fi router • Yota. Amber — portable Wi. Fi LTE access point • Yota. Phone Idea Camp –international project for applications’ development for the second “always- on” display, bringing together end- users, designers and developers Russian and international IT companies with Russian origins based on promising technological and market trends

16 Overview of competitors Function Deal with complexity Probabilistics decision making Passive learning Understanding unconventional data Autonomy Active learning Natural language generator Properties Well-scoped framework Watson Search and Q&A tools Siri Interacting & Assisting tools Amelia Interpreting technologies Project Adam Google. Brain Ashamovandpartners Aging Analytics Database constituion

17 Overview of competitors Function Deal with complexity Probabilistics decision making Passive learning Understanding unconventional data Autonomy Active learning Artificial Intelligence M achine Learning Properties Well-scoped framework Watson Kensho. Madbits(Twitter) Salesforce Scaled. Inference Infer. Net Azur. ML

18 Potential challenges to IBM Watson from IT giants Google Microsoft Google Brain : recognizes language of expression even if not specified Quantum Artificial Intelligence Lab and other Artificial Intelligence / Machine Learning projects Natural language processing and human-computer visualization / interaction Investments in healthcare startups through Google Ventures Project Adam Infer. Net as a writing software Azur Machine Learning in the field of Artificial Intelligence 1 2 HP Development of one umbrella platform : HAVEn Supporting Hadoop distributions Increasing the number of sources to feed Autonomy Enabling real-time analytics through Vertica or secure real-time data collection through Enterprise Security

19 Analysis

20 Limited availability of quantifiable data bases and sources Quantitative research suggest large sample size of experts & clients Hard to reach Limited project time-frame Risk of insignificant n/respondents Risk of ‘fuzzy’ results Strategic recommendations require wide under- standing of market & technology Methodology Research Barriers Qualitative in-depth analysis Direct method semi-structured expert interviews Targeted standardized questionnaires Large amount of relevant information Transcripts allow extensive data analysis Three expert groups / Two target questionnaires Data analysis concepts SWOT/TOWS RBV Research Approach Limitations Validity restrictions (n for 2 groups too small) Risk of interviewers` bias & subjectivity Questionnaire Version IBM Experts Pot. Clients Business Partners English 7 1 Russian 1 2 n=

21 Strategic Lead Questions What capabilities do we have/need? What is the organisational environment in Russia? Is this potentially worth it for future investments? Analysis SWOT Lists internal + external strategic capabilities Based on project‘s research and review Simple to understand / easy to communicate TOWS Foster strengths to maximize opportunities Overcome weaknesses by taking advantage of opportunities Avoid threats by the use of strengths Reduce weaknesses; avoid threats 1 4 3 2 Inadoptiontoframeworkof. Homburg&Krohmer(2008, p. 480)and. Johnsonetal. (2008, p. 384)

22 Analysis: Watson Portfolio — SWOT STRENGHTS Core Solutions multiple use-cases abroad Patents + intense technological knowledge in semantic analytics Mature level of cognitive computing knowledge in China Business partnerships & high perceived reputation in Russia First mover advantage Innovative company culture World leader corporation in terms of technology, sales, profitability WEAKNESSES Early stage developing technology No Russian language anthology (Watson Cognitive) Lack of use-cases in Russia/Public sector worldwide On-premise solutions require vast amount of energy + cost Lack of clear agenda for support from Watson NY Focus too strong on technical solutions; not practical value Focus on efficiency in respect of orders and targets (economic plans issued by the government; i. e. health system & education) Centralized administration & social system Demand for tools to organize unstructured big data as Russia is moving from paper administration to electronic records Partnerships w/ research institutes Few local direct competitors Plan for Russian national cloud (Rostelecom) Educated specialist workforce US-based company; current geopolitical situation (sanctions etc. ) Legal limits foreign corporations in the public sector Lack of transparency in decision-making Structured market with limitations and own standards with regards to import regulations Restrictions foreign cloud solutions Difference in typologies/treatments/processes (e. g. healthcare Local competitors copying services OPPORTUNITIES THREATS Conversion Strategies Neutralization Strategies Matching Strategies

23 Analysis: Watson Portfolio — TOWS High Technological Entry Barriers Centralised Administration and Paper-based Systems Language Localization in Russia (Core Solutions) Cognitive Semantic Systems New-to-the-Market Best Practices in Healthcare Sector Russian Partnerships IBM’s Recognition & Reputation Smarter City Projects in Russia Watson Cognitive Solution Localisation in Russia Watson Value Preposition in Russia Lack of Russian Knowledge Base in Health Care Lack of Pilots/Use-Cases in Russian Public Sector Authorities’ Understanding of IT vs Russia’s expertise in Cognitive Computing Cloud Restrictions vs Watson Cloud Solution Platform for Developers (Non-Personal Information) High On-Premise Costs & Requirements Regulatory and Legal Restrictions Cultural Mentality: Innovation and Knowledge-Sharing Restrictions to Foreign Cloud Solutions Long-term Planning Horizon on State Level STRENGHTS WEAKNESSES O PPO RTU N ITIES TH REATS Overcome Foster Reduce Avoid Considered into recommendations

24 RBV suggests: Resources & capabilities are drivers and foundation of a firm’s strategy Analyses the significance of resources and capabilities of a firm to create a sustainable competitive advantage Analysis: Resource-Based View (RBV) Three conditions to identify a sustainable competitive advantage in a resource Valuable for Strategy ? Rare amongst Competition ? Difficult to copy/sub- stitue? 1) Valuable Capability 2) Resource Heterogeneity 3) Resource (Im-)mobility Sustainable Competitive Advantage RBV used to justify/turn down future investment decisions into Watson Competitive Strategy

25 Analysis: RBV Watson Assessment Short-Term Competitive Advantages Sustainable Competitive Advantages IS-infrastructure/IBM network Platform Content Analytics Semantic/Cognitive Analytics Patents Technical skills IS development Watson IT-Resources RBV Group Asset Valuable Rarity Appropriability Imitability Substitutability Mobility Tangible IS-infrastructure/IBM network 1 2 1 2 Platform Content Analytics 1 2 2 3 2 2 Semantic/Cognitive Analytics 2 1 2 2 3 3 Watson cloud solution platform 2 3 2 1 1 1 Intangible Patents 1 1 2 3 2 2 IT-business partnerships (B 2 G) 2 3 1 1 3 2 Top-Mgmt. -sponsorship/Planning 2 3 1 1 2 2 Human Assets Technical skills 1 2 2 1 IS development 2 2 1 2 2 3 Market responsivness 1 3 1 1 2 2 Overall Assessment 1 2 1 3 2 2 Advantage Creation Advantage Sustainability RBV Assessment : Future investment recommended to sustain and foster competitive capabilities! Inaccordancetoframeworkby. Wade, M. &Hulland, J. , 2004. The Resource-Based View and Information System Research. MISQuarterly, 28(1), pp.

26 Discussion: Current Watson Position in Product-Life Cycle For Technologies in Government *Research Assessment of Current Status; Goal is to Reach Enlightenment Slope in 2 Years Innovation trigger Through of Disillusionment Slope of Enlightenment Plateau of Productivity Systemsfor Government Surveillance Bringyourowndevice Peak of Inflated Expectations Application Portfolio Management Cloud. Computingin. Government Tabletsingovernment Open. Government Data Government Shared. Services Useof. Social Mediain Government Source: Di. Maio, Andrea. 2014. Top Ten Strategic Technology Trends for Smart Government. Gartner. Advanced. Analyticsfor. Government Business. Intelligencefor. Performance. Management. Citizendevelopers Citizen. Data Vaults Morethan 10 years 2 to 5 years 5 to 10 years Lessthan 2 years. Plateau will be reached in: WATSON Cognitive* Strategic. Goal. Industry Trends

27 Based on Research High perceived value of IBM solutions Customer loyalty & public sector partnership Sustainable Competitive Advantages in Watson portfolio & Research capabilities Discussion: Recommended Competitive Strategy Perceived product value High Low High Price Differentiation Low Price Risky, high margins Loss of market share 1 2 3 8 4 5 6 7 Differentiation Strategy Aim low/mid-price to seek greater initial market share Identification of strategic customers; knowing what they value Create ‘Center of Excellence’ in Russian Public Sector The Strategy Clock Recommendation: Apply mid-price/high-value Differentiation Strategy to gain market share in B 2 G Inadoptiontoframework: Kaulkner, F. &Bowman, C. , 1995. The Essence of Competitive Strategy , Prentice. Hall,

28 Recommendations

29 Recommended Schedule Core Personal data Cognitive English Cognitive Russian Core No personal data P o rtfo lio Training + Sales Material Launch Pilot Projects Establishing Russian Cloud (Partnership/Technological) Monitor the Market in English, Training Build partnerships; localize Russian language function Starting to Reap Core Launch Pilot projects Launch Solution in Russian Instant Short Mid Long Jan. – Jun. 2014 Jun. 14 – Jun. 15 – Jun. 18 ->

30 Core: Straight to the market Practical pilot team training ~ 2, 5 HC International cooperation Business-oriented marketing material Dealing with non-personal data Low cost for the customer Potential topics: • Explorer: Health info • Research/teaching support • Law content analysis (Sp. BU) Needs of other solution categories Only Core needed first Partners Yandex, Rostelecom Preparations Ready to launch in Russia Pilots Practical benefits demonstrated Russian cloud establishment Possibility to deal with personal data Potential topics: • Corruption investigating • Diagnosis support

31 Following the situation Timely decisions Projects in English Experience Translating Full service in Russia Cognitive: See and go Technology under development, use cases coming Competitors not an immediate threat Recommended partnerships Skolkovo, RAEC Experience and insight to evaluate the market Gaining publicity Potential topics: • International research (WDA) • Studyadviser SPb. U (WEA) Demand in Russian In Russia, outside Russia International situation Language priorities, financial resources Partners ABBYY et al. , SPb. U

32 Short- to Mid-Term Recommendations Recommendation practical, business orientation in training light structure: 2, 5 head counts: Business, technical, ½ manager international cooperation — f 2 f when needed Specification Building expert pilot team for Core Marketing focus on benefits practical examples in materials, Russian pilots when available round tables with experts and possible clients to establish contacts and publicity establishing phase: 2 -3 months clear criteria project: 6 months low price, but large enough to commit the customer possible topics: law content search (with SPb. U), health info search to support self-motivated healthy living habits when the sales require (Core can also be provided on-premise) potential partners: Rostelecom, Yandex Pilot projects with Core Russian cloud

33 Long-Term Recommendations Recommendation when sales require including sales, technical, research worldwide cooperation possible partners in research: Russian Association of Electronic Communications (RAEC), Skolkovo Innovation Centre Specification Watson Unit Implementing Cognitive in English to gain experience and revenue from Cognitive possible topic: Study. Advisor to SPb. U (WEA) possible topic: Helping to enhance international academic research (WDA) in timing consider demand on Russian market and customers from other markets needing Russian sources in timing consider status of other translating projects and financial resources of Watson Group SPb. U possible partner e. g. in area of medical or law research Possible partners: ABBYY, Arria, NLG, Yseop, Ashamov and partners (also competitors) in launching phase: idea about show to medical doctors possibility to “update” Core customers to Cognitive Translating Cognitive into Russia Selling Russian Cognitive

34 Attractiveness of fields for IBM Watson in Russia Barrierstoentry. Technologym aturity Healthcare HIGH LOW HIGH Education Citizen Contacts Policy-Decision Making Public Security LOW Forboth presentations Foster Converse Avoid Build

35 Use cases Diagnosis support with information search Diagnose suggestion to MD Procurement management Preventive Health – citizen info bank H e a lth c a re WEA Opportunity Solution Existing cases Personal data Use in Russian Chronical diseases care application Diagnosis support with cognitive information search Diagnose suggestion to MD in oncology Preventive Health – citizen advisor WEX WEA WEX W? A WPA WDA NA Weltok’s CaféWell @Point of Care Modernizing Medicine Well. Point Care Guide & Reviewer Memorial Sloan-Kettering Bumrungrad International MD Buyline YES YES Probably YES YES YES

36 Use cases Research support WEx WDA Information finding Public security W? A Opportunity Solution Existing cases Personal data Use in Russian Information finding for students or teachers Individual study advising & plans “Study. Advisor” WEX WDA W? A Brazil Ministry of Justice National Library of Medicine Bayor College of Medicine Johnson & Johnson Probably Wex WDA Probably YES E d u c a tio n & R e s e a rc h Probably

37 Use cases Monitoring citizen atmosphere to support decision-making “listening citizens” Automatized citizen advising Applications review Law discovery for individuals, businesses or courts C itize n co n tacts, p o licy an d d e cisio n m akin g WEx Opportunity Solution Existing cases Personal data Use in Russian Public documents search Information finding from public databases Help to call centers Law search for individuals, businesses or courts WDA WPA WEx WDA WEA WPA IBM Call Center YES YES Probably YES Probably

38 Finding Partners Key Factors Yandex Strong expertise regarding personal data law Yandex is facing an increasing volume of data and could be interested by Watson … … whereas Yandex databases could « feed » Watson 1 Rostelecom Could provide support in terms of Big Data infrastructures, softwares and services Has a large volume of data at its disposal Appointed by Russian government to develop the national cloud platform 2 Russian Association of Electronic Communications (RAEC) Gathers main market players, key corporate and administration executives Creates norms for Russian IT sectors, represents the interests of the industry (lobby) Could provide valuable update about legal issues to IBM 3 Natural Language Generators ABBY has experience with Russian government agencies Arria NLG developed databases with specific fields ‘s corporate languages Ashamov and Partners claim an expertise on Russian semantic 5 Skolkovo Innovation Center Different start-ups can take an advantage of Watson « intelligence » Skolkovo hosts different promising projects for IBM

39 Thank you for your attention! We appreciate your feedback & thank you for this project opportunity!

Q&

41 Back-up slides

42 IT Market Dynamics Versus Oil Price 0510152025301994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 020406080100120 ITMarket Oil. Price. Russian. ITMarket(US$Billion) US$/Barrel. Brent. Crude 35%decline 30%growth 30%decline 38%growth Source: (IDCBlack. Book, Energy. Information. Administration)

43 Watson value assessment for public sector in Russian Federation Expectedvaluefor. Russianfederation. E ffortneeded Personalopinionby. Mr. Pavel. Shkljudov, IBMCEEIndustry. Leaderfor. Government Cancertreatment. Transportation management platform. Faremanagement. Socialpolicy Publicsafetyplatform Emergencyoperationsplatform Education/talentmanagement Socialandtaxfraud Unifiedidentity. Sustainabilitymanagementplatform Defense. Platform Transportationmanagement Governmentcloud Cybersecurity. HIG H LO W M ED IU M HIGH LOW MEDIUM Wave 1 Wave 2 Wave

44 Six stages of data processing growth Growth process Stage I Initiation Stage II Contagion Stage IV Integration Stage VI Maturity Stage V Data administration Stage III Control Data Processing organization Specialization for technological learning User- oriented programmers Middle Management Establish computer utility and user account teams Data administration Data resource management Data processing and control La x More la x Formalized planning and control Tailored planning and control systems Functional cost reduction applications Data resource strategic planning User awareness « Hands off » Superficially enthusiastic Arbitrarily held accountable Accountabilit y learning Effectively accountable Acceptance of joint user and data processing accountability Applications portfolio Functional cost reduction applications Proliferation Upgrade documentation and restructuring of existing applications Retrofitting existing applications using data- base technology Application integration « mirroring » information flows Organization Integration of application Source: (Nolan, 1979)

45 Proposed schedule for Watson in Russia during next years Instant Jan. 2014 – Jun. 2014 Short Jun. 2014 – Jun. 2015 Long Further Mid Jun. 2015 – Jun. 2018 Data Processing organization Data processing and control User awareness Applications portfolio M a rk e t Term A: Preparing for the launch B: First projects C: Establishing Russian cloud E: Mapping the possibilities for Cognitive in English G: Bringing Russian speaking Cognitive D: Starting to reap Core F: First experience from Cognitive H: starting Cognitive sales Russian