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

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. © 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. © 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. © 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. © 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. © 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. © 2010 IBM Corporation
Select Technical Challenges of Open Services Platform
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•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. © 2010 IBM Corporation
The Lifecycle of an Enterprise IT Services (Contract)
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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. Cognitive Requirements Identification and Service
Solution Draft Generation
9

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. © 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. © 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. © 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
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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. © 2010 IBM Corporation
Requirements to Service Mapping – Interactive and Explorative Visualization
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16. © 2010 IBM Corporation
Experimental Results
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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. © 2010 IBM Corporation
eAssistantfor CognitiveProcess Assistance
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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. © 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
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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. © 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!
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Cognitive
Cognitive Computing
Cognitive Assistance
Cognitive Services
Cognitive BPM

20. © 2010 IBM Corporation
Questions?
Thank You!
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