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Towards open smart services platform

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Selected slides from my presentation in the "Smart Service System: Analytics, Cognition and Innovation" Minitrack at HICSS 2017.

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Towards open smart services platform

  1. 1. Hamid R. Motahari-Nezhad1, and Larisa Schwartz2 1 IBM Almaden Research Center 2 IBM TJ Watson Research Center Towards Open Smart Services Platform A Foundation for Cognitive Enterprise Services
  2. 2. © 2010 IBM Corporation Enterprise Services 2 A. Service Provider • Individual • Institution • Public or Private C. Service Target: The reality to be transformed or operated on by A, for the sake of B • Individuals or people, dimensions of • Institutions or business and societal organizations, organizational (role configuration) dimensions of • Infrastructure/Product/Technology/Environment, physical dimensions of • Information or Knowledge, symbolic dimensions B. Service Customer • Individual • Institution • Public or Private Forms of Ownership Relationship (B on C) Forms of Service Relationship (A & B co-create value) Forms of Responsibility Relationship (A on C) Forms of Service Interventions (A on C, B on C) Spohrer, J., Maglio, P. P., Bailey, J. & Gruhl, D. (2007). Steps toward a science of service systems. Computer, 40, 71-77. From… Gadrey (2002), Pine & Gilmore (1998), Hill (1977) A B C Vargo, S. L. & Lusch, R. F. (2004). Evolvingto a new dominant logic for marketing. Journal of Marketing, 68, 1 – 17. “Service is the application of competence for the benefit of another entity.” Major Types of Service (provider perspective): • Computational/technology services • Business/Enterprise services • People Services Service Offerings Definition & Design Service Sales Pursuit Transition and Transformation Service Delivery & Operation Lifecycle of Enterprise (IT) Services
  3. 3. © 2010 IBM Corporation Mega Trends in Enterprise Services Outsourcing deal sizes are shrinking! n In 2013, number of contracts climbed 2%, total contract value (TCV) declined 18.2% Deal shrinkage due to more service integration n “Hybrid Cloud and IT as Service Broker” became a top trend in 2014 Service integration guidelines for Multi-sourcing n UK govt. authored SIAM (service integration and management) n SIAM is a guideline for managing multiple suppliers by a given business (the consumer side)* Autonomic and cognitive computing impact on service management n Virtual knowledge engineers” absorb work previously carried out by human and shifting sales and delivery of IT services Old New Future! Source: Gartner Virtual Knowledge Engineers★ Jamie Erbes, Hamid R. Motahari Nezhad, Sven Graupner: The Future of Enterprise IT in the Cloud. IEEE Computer 45(5): 66-72 (2012)
  4. 4. © 2010 IBM Corporation Enterprise Workforce: The move towards OnDemand, and Digital! Enterprise workforce shift: online staffing n Enterprise crowdsourcing was named a major trend in Accenture Technology Vision 2014 n The revenue for Enterprise Crowdsourcing grew approximately 53% from 2009 to 2010 and accelerated to 75% from 2010 to 2011 On-demand workforce in IT outsourcing n IT service managers have started using crowdsourced staff (e.g. Axios) n The rise of specialized crowdsource-based IT service providers (e.g., onForce onsite IT services with warranty, and contingent classification) n Crowdsourced staff is used in training machine learning and AI algorithms, and agents (e.g., WorkFusion) Robots and Chatbots are the pioneers “Virtual (knowledge) engineers” n RPA (Robotic Process Automation): Abank deployed 85 bots for 13 processes, handling 1.5 million requests per year. It added capacity equivalent to more than 200 full-time employees at approximately 30 percent of their cost. n Chatbots have been developed in IT and in customer support and representatives in different industries n Nevertheless, cognitively enabled bots (chatbots) have been applied in limited (reps) roles n And, many companies, large and startups, are competing to provide the platform of chose for bots
  5. 5. © 2010 IBM Corporation The need for an open platform/marketplace for Enterprise IT Services Services Financial TechnologyOrganizational § Simplifying service contract and pricing: Using standard market services at all-inclusive unit pricing § Pay per use with flexibility to in- / decrease § Incentive to move to aaS model due to lower prices § Transparent financial model that establishes costs in business terms § Standardize platforms based on open standards with high automation § Continuous improvement based on analytics and cognitive technologies (just-in-time capabilities) § Use of Software Defined Environment across IT infrastructure (compute, storage and network) § Focusing on business outcome, rather than IT capabilities § Value-based choices through tiered standard offerings & service levels § LOBs manage consumption and service level choices §CMOs & LoB owners make sourcing decisions, often “business-driven” §Cultural shift of organization from procure/run to consumption of IT services §More consumable IT services offered by vendors
  6. 6. © 2010 IBM Corporation Open Services Management Platform: Conceptual Architecture Business-defined solution specs and restrictions, e.g., “full service,” “selected service,” or “multi-sourced” requirements Business-centric performance and risk predictions, alerts, traditional ITSM reporting Business Functions of Clients CRM HR Payroll Finance Collaboration… Vendor and Partner IT Service, and Enterprise Workforce Providers Client-Facing Components Hybrid services provider analytics Solution composition and service orchestration Governance and analytical substrate IT provider bid management ITServicesPlatformManagement Service Management Components Service Providers Management Components Client Business-Centric Self-service Portal Business-IT service/requirement mapping and translation Service composition and orchestration Business-IT risk/compliance/policy/SLAanalysis Hybrid services provider analytics Knowledge management and analytics) Services Offerings Management Provider Subscription Management Multi-vendor and Hybrid Service Governance Workforce management Travel
  7. 7. © 2010 IBM Corporation Select Technical Challenges of Open Services Platform 7 •Discovery of client business “functions” and dependencies on client's IT components and/or requirements •Automated decomposition of the functions to into multiple (independent) service providers, translation of business-to-IT requirements (e.g., SLAs) Business function outtasking •Business function risk assessment/prediction and IT incident resolution based on multiple (interdependent) service provider activities, with limited controls into providers’ infrastructures •How does the Service broker coordinate the activities of different service providers to provide platform- level guarantees? Multi-provider governance •Universal data models (ontologies) and configuration management supporting low-risk, low-delay service provider interchangeability (e.g., what if agents are used) Service integration abstractions, and models •Coordinating activities, and integrating the outputs from computational units (digital workforce) and crowd-sourced staff for outtasking Crowdsourced and Digital workforce management •Ability to offer advanced analytics to the service providers on opportunity selection, client requirement analysis •Ability for the service provider to put togethera solution over the capabilities of service providers. Service Analytics and Cognitive Support for service sales & operation
  8. 8. © 2010 IBM Corporation The Lifecycle of an Enterprise IT Services (Contract) 8 Prior Deals Service Offerings Guidelines, methodologies People Profiles Lessons Learned Service Delivery Data Opportunity Deal Deal Deal Checkpoints/ Contract T&T Steady-State Renewal Identification Validation Qualification Pursuit QA/Risk Analysis Delivery Engagement Transition & Transformation Renewal Steady-State Delivery Business Development Current Deals Pipeline Revenue & Finance Information Integrate and Make the Data Available Using Interfaces (APIs) Deal Information Management Enable Reusing Deal Artifacts and Sharing Knowledge Cognitive Business Requirements Understanding Analyzing RFPs to extract requirements, and author RFP Response Cognitive Solutioning Compose the set of service offerings that meets clients requirements Cognitive Process Automation Cognitive Robotic Automation
  9. 9. Cognitive Requirements Identification and Service Solution Draft Generation 9
  10. 10. © 2010 IBM Corporation Problem of Requirements Identification in RFPs § RFP turnaround times are challenging – Typically 3 to 6 weeks (have been shrinking over time) § RFP documents contains 10s of document, each 100s of pages describing various aspects of the requirements § Initial RFP Reading and Understanding is Time Consuming § Analyzing the RFP is Challenging and Time Consuming § Technical challenges – There are hundreds of requirements stated in each RFP that need to be identified and analyzed, including whose responsibility (service provider or customer) is to perform them • Using different document structure, language structures, wordings, file formats, etc. • Consistency, ambiguity, understanding them from SO’s offerings perspective – Identification of what constitute a requirement is very challenging – Identification of key requirements (among all), and their relationships to IBM offerings is a key – Customer instructions on the format and response requirements need to be understood
  11. 11. © 2010 IBM Corporation Requirements expressed in different form and structures: tables and text In Section 3 (IT Service Management - Service Requirements) A Subsection Sub-requirements SP’s Requirement Indicators SP Requirements (Extract these!) A Requirement Title of the table, potentially Topic [Customer]
  12. 12. © 2010 IBM Corporation RFPCog for Cognitive Requirements Understanding and Service Solution Generation RFP Documents Requirements Identification Service Catalogs ITIL Cognitive Service Composition Requirements-driven Technical Solutions Composition Solution Patterns Customer Service Vocabulary Solutions Taxonomy Provider Offering Taxonomy What are client requirement statements? How client works? What services offerings/services would meet these requirements? Service Request Identification and Grouping What are in-scope and out-of-scope service? workflows Instructions/ Procedures Hamid R. Motahari Nezhad, Juan M. Cappi, Taiga Nakamura, Mu Qiao:RFPCog: Linguistic-Based Identification and Mapping of Service Requirements in Request for Proposals (RFPs) to IT Service Solutions. HICSS 2016: 1691-1700
  13. 13. © 2010 IBM Corporation Cognitive Service Composition § Knowledge-Driven Capability Decomposition – Building a knowledge graph of provider service capabilities by building on industry taxonomy (ITIL) and provider service taxonomies § Key Factors in Cognitive Solution Composition: a fitness score for service capabilities in a composition – Semantic mapping of Requirements description to Service Capability Description • Word2Vec based mapping, specifically trained for IT services domain • LDA-based matching of service request with service capabilities – Ontology-driven mapping service requirements to service capabilities – Structurally-aware mapping of requirements to service capabilities 13
  14. 14. © 2010 IBM Corporation14 RFPCog PoC – Requirements Marking, and Requirements- Service Mappings Human Interaction and Feedback Enablement: • Requirements – Not a Requirement • Requirements – Missed a Requirement • Matching – Incorrect Matching • Matching – Missed a Matching Feedback is fed back into the system to re- train it adaptively, and in an online/offline manner
  15. 15. © 2010 IBM Corporation Requirements to Service Mapping – Interactive and Explorative Visualization 15
  16. 16. © 2010 IBM Corporation Experimental Results 16 ML-based Topic Classification Performance (TP Rate) 0.9518 0.8733 0.7587 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 SVM Logistic Regression Naïve Bayes TPRate Support Vector Machine (SVM) Performance Details TP Rate FP Rate Precision Recall FMeasure ROC Area Class 0.986 0.232 0.958 0.986 0.972 0.877 F 0.768 0.014 0.908 0.768 0.832 0.877 T Weighted Avg. 0.952 0.198 0.951 0.952 0.950 0.877
  17. 17. © 2010 IBM Corporation eAssistantfor CognitiveProcess Assistance 17 Watson (& BigInsight NLP) Apps and Services on BlueMix CollaborationTools Enterprise Repositories, Applications and Data Sources Feeds Repositories Document collections … eAssistant Apps Process Knowledge Graph Builder Conversation Analytics, Auto-Response, Prioritization Calendar and Scheduling Assistant Cognitive Process Learning Process Assistant Cognitive Work Assistant APIs Semantic Role Labeling POS tagging Dependency Analysis Co-reference resolution Named Entity Recognition Knowledge Graph Builder Hamid R. Motahari Nezhad, Cognitive Assistance at Work, in AAAI Fall Symposium 2015. Richard Hull, Hamid R. Motahari Nezhad: Rethinking BPM in a Cognitive World: Transforming How We Learn and Perform Business Processes. BPM 2016: 3-19 Further details:
  18. 18. © 2010 IBM Corporation Composition of Digital Workforce, APIs & people in offering Enterprise Services § In current Hybrid composition/mashup (People, Services) methods: – Services are represented with API calls – People are integrated with Human Tasks (GUI is the interaction paradigm) – Composition methods are finding deterministic models of interactions, defined apriori § We will be moving towards dynamic composition of cogs and human in which – Cogs are participating in NL conversations – Human are approached through messaging and natural language – Composition are performed dynamically during the conversation, require non-deterministic models, defined in online and on-demand model 18 Weather Cog Health Agent Personality Insight Cog. Provider Cogs Travel Cog 1 Travel Cog 2 Planning a Vacation Trip Considering preferences, experience, conditions, cost, Availability, etc. Mediated and facilitated by Cogs Human-Cog interaction Cog-Cog interaction Natural Language Natural Language, CCL, (ACL, KQML, etc.)? ACL: Agent Communication Language, KQML, etc.
  19. 19. © 2010 IBM Corporation Summary & Conclusion § The Future of Computing is …. § The Future of Work is …. § The Future of Services is …. § The Future of Work Processes is …. § A huge, unprecedented opportunity for the research community to advance our understanding, methods and technology underpinning these transformations and disruptions! 19 Cognitive Cognitive Computing Cognitive Assistance Cognitive Services Cognitive BPM
  20. 20. © 2010 IBM Corporation Questions? Thank You! 20

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