Towards open smart services platform

Hamid R. Motahari-Nezhad1, and Larisa Schwartz2

1 IBM Almaden Research Center2 IBM TJ Watson Research Center

Towards Open Smart Services PlatformA Foundation for Cognitive Enterprise Services

©2010IBMCorporation

EnterpriseServices

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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 ofOwnership Relationship

(B on C)

Forms ofService Relationship

(A & B co-create value)

Forms ofResponsibility Relationship

(A on C)

Forms ofService 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). Evolving to a new dominant logic for marketing. Journal of Marketing, 68, 1 – 17.

“Service is the application of competence for the benefit of another entity.”

MajorTypesofService(providerperspective):• Computational/technologyservices• Business/Enterpriseservices• PeopleServices

ServiceOfferings

Definition&Design

ServiceSalesPursuit

TransitionandTransformation

ServiceDelivery&Operation

LifecycleofEnterprise(IT)Services


MegaTrendsinEnterpriseServices

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 integrationn “Hybrid Cloud and IT as Service Broker” became a top trend in

2014

Service integration guidelines for Multi-sourcingn 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 VirtualKnowledgeEngineers★ JamieErbes,HamidR.Motahari Nezhad,SvenGraupner:TheFutureofEnterprise ITinthe

Cloud. IEEEComputer45(5):66-72(2012)


EnterpriseWorkforce:ThemovetowardsOnDemand,andDigital!

Enterprise workforce shift: online staffingn 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 outsourcingn 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): A bank 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


Theneedforanopenplatform/marketplaceforEnterpriseITServices

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


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 ClientsCRM 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

IT S

ervi

ces

Plat

form

Man

agem

ent

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/SLA analysis

Hybrid services provider analytics

Knowledge management and analytics)

Services Offerings Management

Provider Subscription Management

Multi-vendor and Hybrid Service Governance

Workforcemanagement

Travel


SelectTechnicalChallengesofOpenServicesPlatform

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•Discoveryofclientbusiness “functions” anddependencies onclient'sITcomponents and/orrequirements•Automateddecomposition ofthefunctions tointomultiple(independent) serviceproviders, translationofbusiness-to-IT requirements(e.g.,SLAs)

Businessfunctionouttasking

•Business function riskassessment/prediction andITincidentresolution basedonmultiple(interdependent) serviceprovideractivities,withlimitedcontrolsintoproviders’ infrastructures

•Howdoes theServicebroker coordinatetheactivitiesofdifferentservice providers toprovideplatform-levelguarantees?

Multi-providergovernance

•Universaldatamodels (ontologies) andconfigurationmanagementsupporting low-risk, low-delayserviceproviderinterchangeability(e.g.,whatifagentsareused)

Service integrationabstractions,andmodels

•Coordinating activities, andintegrating theoutputs fromcomputationalunits(digitalworkforce)andcrowd-sourced staffforouttasking

Crowdsourced andDigitalworkforcemanagement

•Abilitytoofferadvancedanalytics totheserviceprovidersonopportunity selection, clientrequirementanalysis

•Abilityfortheserviceprovidertoputtogether asolutionoverthecapabilitiesofserviceproviders.

ServiceAnalytics andCognitiveSupport forservicesales&

operation


TheLifecycleofanEnterpriseITServices(Contract)

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PriorDeals ServiceOfferings

Guidelines,methodologies

PeopleProfiles

LessonsLearned

ServiceDeliveryData

Opportunity DealDeal Deal Checkpoints/ Contract T&TSteady-StateRenewalIdentification Validation Qualification Pursuit QA/RiskAnalysis Delivery

EngagementTransition &

Transformation RenewalSteady-StateDelivery

BusinessDevelopment

Current DealsPipeline

Revenue&FinanceInformation

IntegrateandMaketheDataAvailableUsingInterfaces(APIs)DealInformationManagement

EnableReusingDealArtifactsandSharingKnowledge

CognitiveBusinessRequirementsUnderstanding AnalyzingRFPstoextractrequirements,andauthorRFPResponse

CognitiveSolutioning Composethesetofserviceofferingsthatmeetsclientsrequirements

CognitiveProcessAutomation

CognitiveRoboticAutomation

Cognitive Requirements Identification and Service Solution Draft Generation

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ProblemofRequirementsIdentificationinRFPs

§ RFPturnaroundtimesarechallenging– Typically3to6weeks(havebeenshrinkingovertime)

§ RFPdocumentscontains10sofdocument,each100sofpagesdescribingvariousaspectsoftherequirements

§ InitialRFPReadingandUnderstandingisTimeConsuming§ AnalyzingtheRFPisChallengingandTimeConsuming§ Technicalchallenges

– Therearehundreds ofrequirements statedineachRFPthatneedtobeidentified andanalyzed, includingwhoseresponsibility (serviceproviderorcustomer) istoperformthem• Usingdifferentdocument structure,languagestructures,wordings,fileformats,etc.• Consistency,ambiguity,understandingthemfromSO’sofferingsperspective

– Identificationofwhatconstitutearequirement isverychallenging– Identificationofkeyrequirements (amongall),andtheirrelationships toIBMofferings isakey– Customerinstructionsontheformatandresponserequirementsneedtobeunderstood


Requirementsexpressedindifferentformandstructures:tablesandtext

InSection3(ITServiceManagement- ServiceRequirements)

ASubsection

Sub-requirements

SP’sRequirementIndicators

SPRequirements(Extractthese!)

ARequirement

Titleofthetable,potentiallyTopic

[Customer]


RFPCogforCognitiveRequirementsUnderstandingandServiceSolutionGeneration

RFP Documents

RequirementsIdentification

Service Catalogs

ITIL

Cognitive Service Composition

Requirements-driven Technical Solutions Composition

SolutionPatternsCustomer

Service Vocabulary

SolutionsTaxonomy

ProviderOffering Taxonomy

What are client requirement statements?

How client works?

What services offerings/services would meet these requirements?

ServiceRequestIdentificationandGrouping

What are in-scope and out-of-scope service?

workflows

Instructions/Procedures

HamidR.MotahariNezhad,JuanM.Cappi,TaigaNakamura,MuQiao:RFPCog:Linguistic-Based Identification andMappingofServiceRequirements inRequestforProposals(RFPs)toITServiceSolutions. HICSS2016:1691-1700


CognitiveServiceComposition

§ Knowledge-DrivenCapabilityDecomposition– Buildingaknowledgegraphofprovider servicecapabilitiesbybuilding onindustry taxonomy (ITIL)andproviderservicetaxonomies

§ KeyFactorsinCognitiveSolutionComposition:afitnessscoreforservicecapabilitiesinacomposition– SemanticmappingofRequirementsdescription toServiceCapabilityDescription

• Word2Vecbasedmapping,specificallytrainedforITservicesdomain• LDA-basedmatchingofservicerequestwithservicecapabilities

– Ontology-drivenmapping servicerequirements toservicecapabilities– Structurally-awaremapping ofrequirements toservicecapabilities

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©2010IBMCorporation14

RFPCog PoC – RequirementsMarking,andRequirements- ServiceMappings

HumanInteractionandFeedbackEnablement:• Requirements– NotaRequirement• Requirements– MissedaRequirement• Matching– IncorrectMatching• Matching–MissedaMatching

Feedbackisfedbackintothesystemtore-trainitadaptively,andinanonline/offlinemanner


RequirementstoServiceMapping– InteractiveandExplorativeVisualization

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ExperimentalResults

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ML-based Topic Classification Performance (TP Rate)

0.9518 0.87330.7587

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

TP R

ate

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


eAssistant for Cognitive Process Assistance

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Watson (& BigInsight NLP) Apps and Services on BlueMix

Colla

bora

tion

Tool

s

Enterprise Repositories, Applications and Data Sources

FeedsRepositories

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

LabelingPOS tagging Dependency

AnalysisCo-reference

resolutionNamed Entity

Recognition

Knowledge GraphBuilder

HamidR.MotahariNezhad,CognitiveAssistanceatWork,inAAAIFallSymposium2015.

RichardHull,HamidR.MotahariNezhad:RethinkingBPMinaCognitiveWorld:TransformingHowWeLearnandPerformBusinessProcesses.BPM2016:3-19

Furtherdetails:


CompositionofDigitalWorkforce,APIs&peopleinofferingEnterpriseServices

§ IncurrentHybridcomposition/mashup (People,Services)methods:– ServicesarerepresentedwithAPIcalls– PeopleareintegratedwithHumanTasks(GUIistheinteractionparadigm)

– Composition methods arefindingdeterministicmodels ofinteractions, defined apriori

§ Wewillbemovingtowardsdynamiccompositionofcogsandhumaninwhich– CogsareparticipatinginNLconversations– Humanareapproached throughmessagingandnaturallanguage

– Composition areperformeddynamicallyduringtheconversation, requirenon-deterministic models, definedinonline andon-demandmodel

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Weather Cog

Health Agent

PersonalityInsight Cog.

ProviderCogs

TravelCog1

TravelCog2

PlanningaVacationTrip

Consideringpreferences,experience,conditions,cost,Availability,etc.

MediatedandfacilitatedbyCogs

Human-Coginteraction

Cog-CoginteractionNaturalLanguage

NaturalLanguage,CCL,(ACL,KQML,etc.)?

ACL:AgentCommunicationLanguage,KQML,etc.


Summary&Conclusion

§ TheFutureofComputingis….

§ TheFutureofWorkis….

§ TheFutureofServicesis….

§ TheFutureofWorkProcessesis….

§ Ahuge,unprecedentedopportunity fortheresearchcommunitytoadvanceourunderstanding,methodsandtechnologyunderpinningthesetransformationsanddisruptions!

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CognitiveCognitiveComputing

CognitiveAssistance

CognitiveServices

CognitiveBPM


Questions?

ThankYou!

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Data & Analytics

Towards open smart services platform