Analytics capability framework viramdas 201212 ssnet

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how enterprise can adopt analytics and measure their internal capability they have within the data - analytics space.

how enterprise can adopt analytics and measure their internal capability they have within the data - analytics space.

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  • 1. ANALYTICSCAPABILITYFRAMEWORKASSESSUNDERSTANDGROW
  • 2. 4 AREAS CRITICAL TO SYSTEMATIC ANALYTICS DATA | data mgmt , integration, big-data,1 unstructured data, MDM, other capabilities to enable analysis. Includes instrumentation, data capture capabilities within the systems DESIGN CYCLE OPERATE CYCLE Value Chain ANALYTICS | Applied statistical and Process Actions Outcomes Metrics Break down Process Actions2 math models along with simulation, scenarios, text and media analysis capabilities to discover Visualization Process Map Infographics Interactive -Visuals Visualization insights relevant to business Dashboards Reports Analytics What-If Analytics Scenarios- Simulation VISUALIZATION | ability to present Text, Visual Analytics Adv. Statistics3 data for human consumption integrated into systems, includes new forms of representation, Data Simple Math BigData Unstructured Unified Data interaction and drill down etc.. Fragmented PROCESS | ability to integrate the4 model into business through systems, operations, org readiness, ultimately applying for actionable business value
  • 3. PROCESS  INTO THE BUSINESS DNA.. Integration into • Data Integration – dual channel 1 Systems • • Rules Engines / configurators Work flow Management / API • Organization Structures, Roles Organization • Training, Re-Skilling 2 Readiness – OCM* • Sourcing Models | Service – multi tenancyDecisionSupport • Dashboards, BI Tools Visualization / BI for1.Product Design 3 Decisions • • In process Visualization Interactive, Virtual Reality2.Policy Offering • BPO Operations Operations3.Renewals 4 Integrations • • Business Model Changes Product. Services re-design4.Root CauseAnalysis • Mobility and Web front end interface5.PerformanceReporting 5 Emerging Platforms • • Hosting – Cloud Big Data and Unstructured data sources
  • 4. DEFINING CAPABILITY FOR ANALYTICS Common Understanding of the solutions worked on the ground, to provide a common1 baseline for all analytics solutions within and across vertical domains. Identify Opportunities Areas to build DESIGN CYCLE OPERATE CYCLE capability of analytics solutions across Process Value Chain Process2 People, Tools, Services and Vision. Actions Outcomes Metrics Break down Process Map Actions Visualization Infographics Visualization Interactive -Visuals Dashboards Reports Position Analytics to Clients by CEM & sales Analytics What-If Analytics Scenarios- Simulation appropriately to clients across Process, Text, Visual Analytics3 Analytics, Visualization and Data Management aspects of Analytics. Data Adv. Statistics Simple Math BigData Unstructured Data Unified Fragmented Identify Strategic Areas for vertical domains to enhance analytics capability through4 Partnerships, acquisitions and internal development, when maturity is aggregated across solutions..
  • 5. MATURITY MODEL LEVEL – DETAILED INTO 10 CORE AREAS.. FRAGMENTED ALIGNED INTEGRATED OPTIMIZING Simple structure, numeric [ cardinal] Structured Data with metadata Unstructured text, Data Scale – Size Data as Media like Voice, Image and SCALE / STRUCTURE and non-numeric- [ Ordinal] support, and time Video Bigdata ManagementDATA Integrated data sets through DB- Access to non standard data, late SOURCE / RETRIEVE Internal Local Files, federated external connectors – API, structure binding DWH, SQL based retrieve Real time search Compliance and traceability effort in late binding – auto discovery of CONFIG - CONTROL User Configuration, Data Security adding new data sources structure Simple 2-Dimensional Graphs andVISUALIZATION PRESENTATION reports including Types of Visuals Maps, Multi-dimensional Graphs, Composite Visuals, infographics Storyboards, Virtual Reality STRUCTURE supported? Static simple play out pivot based interaction – User self System Generation-Automation , Actions integration - external INTERACTION service visual re-formation, systems. Complex Statistics [econometrics] , Linear Functions, Regression, Text & Analytics, Neural Networks,ANALYTICS ALGORITHM Basic Functions and statistics Numerical Method, Clustering Statistics, fractals, Analysis, Single Iteration playout MODELING scenario analysis, what -if analysis, Simulation, optimization, Computational Flows Process Maps, Kpi- MetricsPROCESS [ACTIONS] Value Chain Analysis , Benchmark DESIGN Ad-hoc Customer opportunity Breakdowns, Data Tactical Changes – re-structure to Strategy Changes - New services MANAGE Operational Changes > New Revenue Models Business operations, processes.. models, synthesis of business value Integrated Partner Actions, EXECUTE Manual Process Change / Actions Sense and response mechanisms, Automation into systems,
  • 6. APPROACH – METHOD AND STRUCTURE..Common Understanding Service Capability Revenue - GTM Market Strategy Capability Business Value Models Assessment 1. Solution X Accounts 1. Understand Business Landscape 2. Market Mix 1. Framework 2. Value Chain Analysis 2. Ongoing – Assessment 3. Key Performance Metrics -KPI 3. Gap - Roadmap 4. Industry Benchmarks, trends Marketing 1. Portal-Website 2. Collaterals Solution Catalog 3. Media 4. Forums Best – Practice 1. Analytics HotSpots 5. Analyst Reports 2. Market Trends & Analysis 6. Thought Leadership 1. Solution Inventory 3. Offering / Solution Details 2. Case and materials Events 1. Customer Advocacy Capability 2. Account Based Mktg 3. Industry Forums Internal – Advocacy Development 1. News-letter 1. Analytics Leads –Soln Domains 2. Forums 2. Organization Structure Deals 3. Showcase 3. Partnerships 4. Knowledge Mgmt 4. Labs – Experiments 1. POC 5. BAP Charter, 5. Incubation 2. Consulting 6. Training 3. Operations 4. AS a Service
  • 7. ANALYTICS CAPABILITY FRAMEWORK & APPROACH 1. Service 1. Scoping Capability 1. Solutions List 2. Market DESIGN CYCLE OPERATE CYCLE 2. Contribution to Business 2. Assessment Capability Process - Actions Value Chain Outcomes Process - Actions Metrics Break down Process Map Visualization Infographics Visualization Interactive -Visuals DATA ANALYTICS VISUALIZATION PROCESS [ACTIONS] PRODUCT – Goto DashboardsCommon Market ReportsUnderstanding Big Data Mgmt Industry Awards - Recog Optimizing Realtime Search - Scenario - Models Analytics What-If Analytics Aggregation Managed Svcs Deals Scenarios- Simulation Sense & response Late Str. Binding Simulation Interactive Visualization Adv. Statistics Feedback Ops Deals Simple Math Compliance-Traceability Advanced Visualization Lab – Pilot - POC OR - Solvers Integrated Unstructured DataSet Consulting Deals Data BigData Data Advanced Statistics Multi-source Integration Integrated Execution Industry Forums Unstructured Unified Metrics BreakDown Internal Forums Fragmented Aligned Data Configuration Dashboard Process Details L1-L3 Mktg Collateral DW - ETL Product / Service Basic Aggr Ftns Pivots Value Chain Analysis Packaging Office – Based Models Fragmented Office Data Sets Office – Based Models Reports 4. Actions Impaired 1. Service Capability 2. Go to Market Capability Index Inner-Ware Market-ware 3. Report-out 1. Portfolio View 2. Gaps in solution 3. Slicing – Dicing Views No-Ware Vapor-Ware Marketability-Index
  • 8. QUESTIONNAIRE STRUCTURE..Background Process Analytics1. How did the solution get 1. Did the solution design involve 1. what is the operational model developed? Background? a systematic study of the of Analysis? industry process?2. What are the detailed 2. What is the typical age of the components of the solution? 2. Does the solution impact the data on which the solution is business strategy? Or modeled?3. What is the core Value Structure? proposition of the solution? 3. What type of analytics 3. Does the solution collect algorithms does the solution feedback from business use actions into the model for further fine tuning? How? 4. How does the solution integrate into business execution and operations?
  • 9. QUESTIONNAIRE STRUCTURE..Visualization Data Goto Market1. Does the solution offer 1. What types of data structures are 1. In what stage of development Advanced presentation handled by the solution? is the solution? structures? 2. From what data sources does solution get & Store data? 2. What are the accounts being2. Does the solution offer targeted for this solution? 3. How much time lag is there to Dashboard and integrated consolidate new data sources? presentation capabiilty 3. What is the GTM Work 4. How is data integrated and underway for the solution?3. How Does the solution support consolidated into solution? / enhance user interaction? 5. How scalable is the solution? 4. What is the customer profile?4. How much efforts is used in 6. What are control and access to End users for configuration, fine-tuning? visualizing? 7. What are the Warranty Measures5. How useful have the Visual set in place for the solution? Component been for the 8. What is the organization capablity busienss customer? within data management?6. What is the organization 9. How does it help improve customer capablity within Visualization? experience & customer business ? 10. What stage of implementation is the7. What stage of implementation tool in? have the visual components been deployed at?
  • 10. METHODOLOGY Analytics Solution Sales1. The Assessment is based on Interviews with team members and presentation made on the solution. Direct observations of the Soln1 1 2 solution have not been made. soln2 1 2 1 Soln3.. 1 1 12. The Assessment is based on a Structured Questionnaire Spanning 1. 4 Areas for Analytics Capablity [Process, Visualization, Analytics, Data] & 2. Goto Market Readiness of the solutions3. The Study followed the 3 in a box model with Sales, Domain & Delivery and technical resources being interviewed..4. Aggregation of scores are done based on weighted average scores for each sub section