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The Analytics COE positioning your business analytics program for success

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Kiran Garimella
Kiran Garimella

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.

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The Analytics COE Positioning Your Business Analytics Program for Success Kiran Garimella, Ph.D. Principal Consultant, XBITALIGN Excellence in Business & IT Alignment © XBITALIGN
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). (c) XBITALIGN 22 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 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 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 © XBITALIGN 4
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 © XBITALIGN
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
The lifecycle of data Raw data generation Extraction Collection Cleansing Analyzing Packaging/ (Information) Consuming Decisioning 7© XBITALIGN
The Taxonomy of Analytics 8 Insight Knowledge Information Data Competitive Advantage Transformation Standardization, Simplification IT 8 Foundation Value © XBITALIGN
9 The Analytic Landscape © XBITALIGN
Key Elements of a COE 10 People TechnologyProcess LearningGoverning Sustaining Enabling Communicating Tooling IntegrationBuilding Improving © XBITALIGN
Maturing a COE 11© XBITALIGN
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 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
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 14© XBITALIGN
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) 15© XBITALIGN

More Related Content

The Analytics COE positioning your business analytics program for success

  • 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). (c) XBITALIGN 22 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 © XBITALIGN 4
  • 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 © XBITALIGN
  • 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 7© XBITALIGN
  • 8. The Taxonomy of Analytics 8 Insight Knowledge Information Data Competitive Advantage Transformation Standardization, Simplification IT 8 Foundation Value © XBITALIGN
  • 10. Key Elements of a COE 10 People TechnologyProcess LearningGoverning Sustaining Enabling Communicating Tooling IntegrationBuilding Improving © XBITALIGN
  • 11. Maturing a COE 11© XBITALIGN
  • 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 14© XBITALIGN
  • 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) 15© XBITALIGN

Editor's Notes

  1. “Integration” – not in the sense of App Int, but in the sense of connecting Analytics to the rest of the informational and decision-theoretic assets in the ecosystem.