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

1. ANALYTICS
CAPABILITY
FRAMEWORK
ASSESS
UNDERSTAND
GROW

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
Actions
2 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. Statistics
3 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 the
4 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 tenancy
Decision
Support
• Dashboards, BI Tools
Visualization / BI for
1.Product Design 3 Decisions
•
•
In process Visualization
Interactive, Virtual Reality
2.Policy Offering
• BPO Operations
Operations
3.Renewals
4 Integrations
•
•
Business Model Changes
Product. Services re-design
4.Root Cause
Analysis
• Mobility and Web front end interface
5.Performance
Reporting
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 common
1 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 Process
2 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 Analytics
3 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 through
4 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 Management
DATA
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 and
VISUALIZATION
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- Metrics
PROCESS [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 Dashboards
Common Market Reports
Understanding 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 Analytics
1. 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 Market
1. 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 being
2. 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 Measures
5. 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 the
7. What stage of implementation tool in?
have the visual components
been deployed at?

10. METHODOLOGY
Analytics
Solution
Sales
1. 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 1
2. 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 solutions
3. 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