You should consider the following three aspects of your Business Analytics Program: * The Business (not just data science, big data, and technology) * Analytics as the DNA of the company (and not just a competency of an elite few) * A Programmatic approach that sustainable for the life of the company (and not just a one-time project or initiative) What role do classical statistics, Bayesian statistics, judgment under uncertainty, heuristics, biases, categorical data analysis, etc., play in such a program? A COE (Center of Excellence) framework seeks to address these aspects and ensure the company can progress on all fronts.

1. The Analytics COE
Positioning Your Business Analytics
Program for Success
Kiran Garimella, Ph.D.
Principal Consultant, XBITALIGN
Excellence in Business & IT Alignment
© XBITALIGN

2. Overview
A business analytics program is more than the application of data science and Big Data technology to data.
Success should be measured not only by the valuable insights the program delivers, but also by how well
it is sustained and how much the ‘analytics mindset’ becomes part of the company’s DNA. The journey is
not only from data to information, but also from information to knowledge, and from knowledge to
intelligence. The foundation for making this happen is a well-structured Analytics Center of Excellence
(CoE).
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Business Analytics Program =
(Big) Data + Technology + (Data) Science + ???
Business Analytics Program =
Setup + Analysis -> Insight + then what ???
Business Analytics Program =
A few expert data scientists OR part of the Corporate DNA?
The spectrum of COEs:
Do it for them versus enable them to do it
© XBITALIGN

3. 3
The Main Thing
It isn’t about technology, but what’s in it for the decision-makers.
My stakeholder – ex-Vice Chairman of GE – said to me:
“20 years ago, my MIS department would put in front of me,
every morning, a reliable report about revenue and other
metrics from various regions based on products and services. It
looks like that’s not possible anymore.”
If you can’t help decision-makers make better decisions faster while
minimizing risk, you have done nothing.
© XBITALIGN

4. 4
OWL
BAM
BI
CAF
Portals
BPEL
WYMIWYR
CMS
Web 2.0
BPEL
Cloud
Social
Complex Event Processing
ICE
PLM
PPM
SAAS
Agile
Big Data
AnalyticsHadoop python
scala
BPM
d3js
wsdl
Mobile
What we give them: CTAs
(Collage of Terrifying Acronyms)
R
Data Science
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5. 5
What your users care about
Process Cycle Time
Throughput Yield
Bottlenecks
Wait-times
Defects per million opportunities
Latency Process Variance
Inventory Turns
SLA Violations
False Demand Triggers
Return Rate
Percentage Rework
Cost of Poor QualityUnnecessary Motion
Excess Processing
Economic Value AddTransportation Waste
Process Variance
Process Capability
Process Capacity
Excess Transactions
Root Cause
Voice of the Customer
Run Chart
Reduction of Waste
Overall Equipment EffectivenessKey Performance Indicators
Baseline Conditions
Compliance
Customer Satisfaction
Customer Satisfaction
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6. The Ecosystem of Analytics
 Strategies &
Strategic Objectives
 Products
 Services
 Projects
66
Providers
PayersPharmacists
Clinicians
Device
Suppliers
Employers
Patients (&
Families)
R&D
Academia
Professional
Bodies
Regulators
Big Pharma
 Business Capabilities
 Technical Capabilities
 IT Applications
 IT Services
© XBITALIGN

7. The lifecycle of data
Raw data
generation
Extraction
Collection
Cleansing
Analyzing
Packaging/
(Information)
Consuming
Decisioning
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8. The Taxonomy of Analytics
8
Insight
Knowledge
Information
Data
Competitive Advantage
Transformation
Standardization,
Simplification
IT
8
Foundation
Value
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9. 9
The Analytic Landscape
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10. Key Elements of a COE
10
People
TechnologyProcess
LearningGoverning
Sustaining
Enabling Communicating
Tooling
IntegrationBuilding
Improving
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11. Maturing a COE
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12. Example of a COE Roadmap
12
Rationale & Business Case Assessment, Analysis, & Prioritization COE Organization Model
COE Governance Model Competency Model & Action Plan Training Plan
COE Roadmap
© XBITALIGN

13. 13
Enterprise Architecture
Technical
Architecture
Applications
Technical
Infrastructure
Services
Business
Architecture
Information
Process
Performance
Execution
Solution
Development
Project
Management
Program
Management
Operations
Operations:
Transition &
Deployment
Release
Management
Operations:
Monitor &
Control
Business
Alignment
Strategy
Change
Management
Governance
Enablement
Knowledge
Management &
Education
Personal & Team
Effectiveness
Continuous
Improvement
Business
Structure
Business Model
Ecosystem
Organization
Enterprise Capabilities Alignment Framework
for Centers of Excellence
© XBITALIGN

14. General Observations on Analytics
• Data -> Information -> Knowledge -> Insight
• Insight also comes from a mass of interconnected knowledge, not
only from a dataset
• If you torture the data long enough, it’ll confess to anything you want
• Do you really want to buy a Ferrari to go get groceries?
• Perceptual errors are almost always errors of higher cognition!
(Pencil in a glass of water appears bent.)
• No amount of training will change perception (a Noble Prize physicist
and a peasant will both see a bent pencil in a glass of water)
• Humans are poorly equipped to deal with probability, statistics, and
consistency in logical thinking
• Training can mitigate cognitive errors
• Tooling must provide the safety harness and the do the grunt work
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15. Next Steps: Get Started!
Use the Enterprise Capabilities Alignment Framework (ECAF™)
for COEs to determine:
 Who you are (culture, stakeholders)
 Why (drivers)
 Who you want to be (vision, mission)
 How (high level: strategies, goals)
 Where you are (current level of maturity)
 Focus areas: prioritize (don’t try to boil the ocean)
 Include some elements to cover people, process, and
technology
 Establish governance (top-down or bootstrap)
 How (detailed: phases, roadmap, maturation)
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