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Building an Analytics CoE (Center of Excellence)

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This deck is from a workshop I conducted at the Indian Institute of Management, Bangalore (IIMB) on 20th July, 2013.
Agenda:
* What does the organization want to do with analytics? What is the role of the CoE that they envision?
* What is the organizational context? Current providers of analytics? Leadership support?
* What will the Analytics CoE need to be like (now and in the future, up to the planning horizon)?
* Where do we stand with analytics capabilities now, compared to what we need?
* How will we evolve the CoE? Set expectations, drive the evolution, establish the value.

Published in: Data & Analytics, Technology
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Building an Analytics CoE (Center of Excellence)

  1. 1. Building an Analytics CoE Rahul Saxena Workshop at IIM Bangalore July 20, 2013 This presentation is based on the material available in the book: Business Analytics: A Practitioner's Guide by Rahul Saxena & Anand Srinivasan Springer International Series in Operations Research & Management Science http://www.amazon.com/dp/1461460794
  2. 2. Agenda  Introductions – about the group, about me. What is "analytics"? What is an "Analytics CoE"?  What does the organization want to do with analytics? What is the role of the CoE that they envision?  What is the organizational context? Current providers of analytics? Leadership support?  What will the Analytics CoE need to be like (now and in the future, up to the planning horizon)?  Where do we stand with analytics capabilities now, compared to what we need?  How will we evolve the CoE? Set expectations, drive the evolution, establish the value. Confidential 2CobotSystems.com
  3. 3. About the group … Confidential 3CobotSystems.com STUDENT WORKING 0-5 Years 5-10 Years 10-20 Years >20 Years Full-time student, 0-5 years of experience Currently working, 0-5 years of experience Demographics TEACHING Currently teaching, 0-5 years of experience PROVIDER ANALYTICS IT (BI, DW) BUSINESS OTHER (Academic, etc.) Provided analytics as an analytics professional Provided analytics as part of an IT role Provided analytics as part of a business role Provided analytics as part of an academic or other role CONSUMER Consumed analytics from professional analytics provider Consumed analytics from IT provider Consumed analytics from business provider Consumed analytics from other provider Perspectives
  4. 4. About me Confidential 4CobotSystems.com NowCobotSystems 2013Cisco 2012Cisco 2011Cisco 2010Cisco 2009Cisco 2008McAfee 2007McAfee 2006Epiance 2005Epiance 2004IBM 2003IBM 2002IBM 2001IBM 2000IBM 1999IBM 1998IBM 1997IBM 1996LaitramCorp 1995LaitramCorp 1994TulaneMBA 1993TulaneMBA 1992IndianRailways 1991IndianRailways 1990IndianRailways 1989IndianRailways 1988IndianRailways 1987SCRAJamalpur 1986SCRAJamalpur 1985SCRAJamalpur 1984SCRAJamalpur 1983IITKanpur 1982 1981 1980 1979 1978 1977 1976 1975 1974 1973 1972 1971 1970 1969 1968 1967 1966 1965 Engineering Mgmt ERP, e-Biz, CRM MBA Analytics Management Management Consulting US based A timeline diagram Business Architecture Business Analytics
  5. 5. What is “analytics”? Confidential 5CobotSystems.com Management Information Systems Industrial Engineering Operations Research Finance Planning & Analysis Statistics Business Intelligence Strategy & PlanningBiz Ops (SCM, CRM, Svc, etc.) ANALYTICS Computer Science … diverse antecedents Business Strategy Psychology 6 sigma, Quality, Lean
  6. 6. What is “analytics” used for? Confidential 6CobotSystems.com … create value by driving decisions from idea to execution •Frame •Inform •Forecast •Deliberate •Recommend
  7. 7. What methods/techniques does “analytics” use? Confidential 7CobotSystems.com ILLUMINATE DIAGNOSE FORECAST OPTIMIZE • Charts & Tables in Reports & Dashboards • Alerts, Visualizations, and Simulations • Analysis, Interpretation & Recommendations • Multi-Criteria Decision Models (MCDM), etc. … use any method that helps to drive from idea to execution MCDM, etc.
  8. 8. What data does “analytics” use? Confidential 8CobotSystems.com TRANSACTIONS CONVERSATIONS OBSERVATIONS • Structured • ERP • CRM • HRMS … • Unstructured • Documents • Websites • Social Media sites like Facebook, Twitter, LinkedIn, YouTube, Blogs … • Sensors & Signals (M2M) • Scans (Bar-codes, RFID, proximity, etc.) • SCADA (Control Systems) • Temperature, pressure, illumination, etc. • Location (GPS, etc.) • Smart-phone data feeds • Network monitors • Video feeds … … use any data as needed, internal & external
  9. 9. What domains is “analytics” used in? Confidential 9CobotSystems.com Decision Layers Strategy, Capacity, Scheduling, Execution … use wherever there is a need for making rational decisions Verticals Telecom, High-Tech, BF&S, Oil & Gas, Healthcare, Government, etc. Functions Marketing, Sales, e-Commerce, Fulfillment, Supply Chain, Product Lifecycle, Strategy, Finance, etc.
  10. 10. What systems/tools does “analytics” use? Confidential CobotSystems.com … use whatever tools are needed Business EPM, Collaborative Decision Making, Decision-Support, Alerts & Feedback IT Data Warehouses, ETL (Extract, Transform, & Load) Business Intelligence (Dashboards, Reports, Self-service) Big Data Analytics Innovation: from idea to value Operations: continuous value realization 10
  11. 11. … a working definition Confidential CobotSystems.com Analytics is used to create value by driving decisions from idea to execution … use any method that helps to drive from idea to execution … use any data as needed, internal & external … use wherever there is a need for making rational decisions … use whatever tools are needed 11
  12. 12. What is an "Analytics CoE"? Applies insights to data to produce analytics deliverables and drive business value Confidential 12CobotSystems.com Variety of Analytical Insights Process System Skills Knowledge Decision Support Data Variety of Deliverables for various Business Decision Contexts & Processes Drive Business Value Variety of Data Sources &Errors New sources & errors New insights New Opportunities & Issues
  13. 13. Agenda  Introductions – about the group, about me. What is "analytics"? What is an "Analytics CoE"?  What does the organization want to do with analytics? What is the role of the CoE that they envision?  What is the organizational context? Current providers of analytics? Leadership support?  What will the Analytics CoE need to be like (now and in the future, up to the planning horizon)?  Where do we stand with analytics capabilities now, compared to what we need?  How will we evolve the CoE? Set expectations, drive the evolution, establish the value. Confidential 13CobotSystems.com
  14. 14. What do leaders talk about when they talk of analytics? Confidential 14CobotSystems.com Supply DemandCurrent State Future State How should we manage analytics investments to gain efficiency? Why do we need so many reports? Why does it take so long or cost so much? How can we develop analytics capabilities to meet demands? My peer has this, I want one too! What can analytics do to improve our business results? Beat the competition?
  15. 15. What do the leaders want to do with analytics?  The CEO asked for it  The CIO has plans for it  XYZ business leader wants it Confidential 15CobotSystems.com FOR WHOM? Finance Planning & Analysis Strategy & Planning Biz Ops (SCM, CRM, Svc, etc.) … for whom will you create value? … what decisions will you drive? … do the current decision-owners think you’re helping?
  16. 16. What decisions will you drive with analytics? Confidential 16CobotSystems.com Analyze contract renewal data to find opportunities Feed the workload (renewal opportunities) to Sales Schedule follow-ups by the Sales Call Center Get the renewals, improve renewal rate Finance Planning & Analysis Sales Ops Call Center Ops Call Center Ops
  17. 17. Answer the “what”, enlist the “who” Confidential 17CobotSystems.com Opportunity Pipeline Bookings Backlog Delivery Deal P&L Impact Analytics Strategic Account Analytics Delivery Optimization Analytics Revenue Revenue Gap Analytics Bookings Trend Analytics Talent & Skills Analytics Resource Planning Analytics Revenue & Cost Alignment … get clients by offering business value
  18. 18. Confidential 18CobotSystems.com  Protect margin using deal analysis  Improve quality of business by targeting deals • Analyze each deal for timing of costs (COGS & PCOGS), revenues (milestones), & risks (e.g., pay per SLA); assess FMV and VSOE impacts; calculate deal impact on the P&L • Plug-in deals pipeline into the P&L projections, provide updates based on actual deals and run-rate • Work with Geo leaders to drive decisions to improve the Sales P&L • Approve or modify deals based on insight into P&L impact • Deal targeting to actively manage and improve the Geo P&L P&L Deals Analysis Improved P&L Control M1 M2 M3 M4 M5 M6 COGS $33 $33 $33 $33 $33 $33 PCOGS $21 $21 $21 $21 $21 $21 COSTS $54 $54 $54 $54 $54 $54 DELIVERY HLD LLD NRFU REVENUE $50 $270 $310 Q1 Q2 Q3 Q4 Full Year PROJECT MARGIN ($8) $34 $56 $43 $125 P&L IMPACT -1% 4% 7% 5% 4% Q1 Q2 Deal P&L Impact Analytics PROJECT METHOD DECISION • Geo P&L Owner • Geo Vertical Leads OWNERS • Geo Finance Lead • Geo Sales Ops Lead … also track costs & value … keep clients by delivering business value
  19. 19. What is the role of the CoE that they envision? Confidential 19CobotSystems.com … provide us the analysis, we promise to use it to create business value … help us throughout the idea to execution cycle to deliver business value … provide us decision advice based on analytics
  20. 20. Agenda  Introductions – about the group, about me. What is "analytics"? What is an "Analytics CoE"?  What does the organization want to do with analytics? What is the role of the CoE that they envision?  What is the organizational context? Current providers of analytics? Leadership support?  What will the Analytics CoE need to be like (now and in the future, up to the planning horizon)?  Where do we stand with analytics capabilities now, compared to what we need?  How will we evolve the CoE? Set expectations, drive the evolution, establish the value. Confidential 20CobotSystems.com
  21. 21. What is the organizational context? Confidential 21CobotSystems.com DRIVE DECISIONS Analytics Providers • Meetings (with customers, suppliers, project teams, colleagues, etc.) • Walking around, observing • Mass media (Newspapers, TV, etc.) • Internet, Books, Gut Feel, etc. Suppliers Substitutes  Relevant  True (data is correct, models are verified)  Actionable (provides the basis for specific action) … apply the noise filter
  22. 22. What do analytics deliverables look like? Confidential 22CobotSystems.com CommunicationDeliverable Messages (email, SMS) to Inform & Recommend Documents (Reports, Dashboards) to Inform, Forecast, & Recommend Decision Explorers to Frame & Deliberate
  23. 23. Where will we find Analytics Providers? Analytics providers are found in many places, it helps to cluster them into these five domains 1. Business: managers and their assistants 2. Analytics: analysts in “analytics” teams 3. IT: in the BI, DW, or Reporting teams 4. External BI Providers 5. External Analytics Providers Confidential CobotSystems.com 23
  24. 24. Who are the current providers of analytics? Confidential 24CobotSystems.com Leader & Department Data Providers Noise Filter Analytics Providers Tom, VP, Sales IT, BizA-CoE, MktDudes.com Jack, Director Sales Ops Jack, Director Sales Ops, MktDudes.com Jim, VP, Engineering IT, PLM-Specialists.com PLM-Specialists.com Mary, PLM Manager Harry, CFO BizA-CoE BizA-CoE BizA-CoE
  25. 25. Not Used Data Provider Trusted & Relevant Decision Modelers Decision Advisors Inconsistent Decisions Leadership support? Confidential 25CobotSystems.com SUPPLY Consistent & Disciplined Data Oriented Decision Models Learn & Ingrain DEMAND Harry 0% to +10% More than 10% Reduce Jim • The size of the bubble denotes $ funding • The color of the bubble denotes growth Tom
  26. 26. Agenda  Introductions – about the group, about me. What is "analytics"? What is an "Analytics CoE"?  What does the organization want to do with analytics? What is the role of the CoE that they envision?  What is the organizational context? Current providers of analytics? Leadership support?  What will the Analytics CoE need to be like (now and in the future, up to the planning horizon)?  Where do we stand with analytics capabilities now, compared to what we need?  How will we evolve the CoE? Set expectations, drive the evolution, establish the value. Confidential 26CobotSystems.com
  27. 27. Analytics Provider Network The analytics function cannot be the locus of all the analytics assets (and talent) for the organization – it is, instead, a capability that enables the effective use of analytics … understand the network, figure out your partnering strategy Confidential CobotSystems.com 27
  28. 28. Enable the Analytics Network for the organization Confidential 28CobotSystems.com DRIVE DECISIONS BICC (IT) ERP (IT) CRM (IT) BizA CoE Sales Ops PLM Mgr SAS D2 IIM B PLM.com Dir FP&A Zoom out of the “centralized / distributed / hybrid” debate … it’s a network Is analytics everyone’s job? Isn’t it?
  29. 29. Enable the Analytics Network for the organization Confidential 29CobotSystems.com Shared Data in an Agile Data Platform, Rapidly Extensible Relevance & Trust built into Deliverables via a Rules-base Decision Models built and provided where Relevant Learn & Ingrain, rapidly adapt/evolve all layers Data, in context Relevance Data-driven Decisions Adapt & evolve Provide the analytics platform to enable everyone in the network … make “analytics” work for your organization
  30. 30. Where is the bottleneck? Demand or Supply? Confidential 30CobotSystems.com Actual demand = Low Potential demand = High Actual supply = High Potential supply = Low Demand is a function of leadership & imagination: stimulate the imagination, deliver successes, make analytics accessible with a clear business value proposition … transform the organization culture to use analytics ... align supply to demand
  31. 31. Not Used Data Provider Trusted & Relevant Decision Modelers Decision Advisors Harry Align supply to demand, and also stimulate demand Confidential 31CobotSystems.com SUPPLY: Processes, Skills & Systems Jim Tom Jim Tom Harry Shared Data, Agile Data Platform Relevance & Trust Decision Models Learn & Ingrain … provide the analytics platform … stimulate demand: in-house successes, industry examples, conferences, peer-to- peer networks, decision advisors
  32. 32. Analytics Network dynamics  Nodes Evolve: Mature, Add, Re-organize, Disappear  Deliverables Evolve: Innovation  Operation  Data Evolves: Federate the data to keep pace  Platforms Evolve: Avoid obsolescence, embrace agility  Talent Flows: Enable people with career paths  Funds Flow: Manage funding for nodes & the platform Confidential 32CobotSystems.com
  33. 33. Deliverables Evolve: Innovation  Operation Confidential 33CobotSystems.com INNOVATE CULTIVATE EXECUTE  Work with data providers to improve data  Drive value realization through analytics usage  Ensure ongoing validity of the analytics  Provide analytics deliverables per SLA  Develop new insights & concepts  Drive from Idea to Execution  Assess value & need  Explore and Fail-fast  Continual creation of Analytics Deliverables  Continual assessment of Data & Model Validity  Continual governance of Policies  Continual monitoring of Usage INNOVATION: TALENT-DRIVEN OPERATIONS: PROCESS-DRIVEN
  34. 34. Deliverables Evolve: Innovation  Operation Confidential 34CobotSystems.com Junk 1-time Useful 1 100% 0% 100% 80% 16% 4% 2 100% 4% 96% 77% 15% 4% 3 100% 8% 92% 74% 15% 4% 4 100% 12% 88% 71% 14% 4% 5 100% 15% 85% 68% 14% 3% 6 100% 18% 82% 65% 13% 3% 7 100% 22% 78% 63% 13% 3% 8 100% 25% 75% 60% 12% 3% 9 100% 28% 72% 58% 12% 3% 10 100% 31% 69% 55% 11% 3% 11 100% 34% 66% 53% 11% 3% 12 100% 36% 64% 51% 10% 3% 13 100% 39% 61% 49% 10% 2% 14 100% 41% 59% 47% 9% 2% 15 100% 44% 56% 45% 9% 2% 16 100% 46% 54% 43% 9% 2% 17 100% 48% 52% 42% 8% 2% 18 100% 50% 50% 40% 8% 2% Repeat Delivery Total Capacity Capacity for New New Delivery The suppliers’ dilemma: the more useful analytics you produce, the more you get mired in repeat delivery … which is valuable repeat business but boring workJunk Always Useful 1-time Useful Repeat Operations Repeat Operations over time, the operations workloads pile up … this is a mark of success: your stuff is useful! … manage it with automation TIME 100% Innovation
  35. 35. Agenda  Introductions – about the group, about me. What is "analytics"? What is an "Analytics CoE"?  What does the organization want to do with analytics? What is the role of the CoE that they envision?  What is the organizational context? Current providers of analytics? Leadership support?  What will the Analytics CoE need to be like (now and in the future, up to the planning horizon)?  Where do we stand with analytics capabilities now, compared to what we need?  How will we evolve the CoE? Set expectations, drive the evolution, establish the value. Confidential 35CobotSystems.com
  36. 36. Analytics roles and functions Confidential 36CobotSystems.com
  37. 37. Agile & Production Analytics: Innovation & Operation Confidential 37CobotSystems.com
  38. 38. Workloads: what do your "Analytics" people do? Confidential 38CobotSystems.com Strategic Scorecards, Metrics Portfolios, & Scenarios Reports & Commentaries; including Forecasts Consultative Analysis Projects (Stats, Optimization, Simulation, etc.) Enterprise Modeling, Business Modeling, Industry/Market Analysis Data Stewardship (Assess, Cleanse, Enrich) Business Case Modeling, Business Value Analysis, Valuation (Financial) Dashboards Governance Meetings & Follow-ups Target, Actual, Outlook, and Revision Alerts & Follow-ups Communication & Driving Adoption of Data-driven Management o Frame the Decision Need o Generate Ideas o Support Decision Making o Monitor Execution o Drive Results
  39. 39. Regression & Correlation Propensity Models (Logistic Regressions, Multinomial Models) Statistical Hypothesis Testing Forecasting Clustering and Segmentation Optimization (LP, NLP, etc.) Sampling & Surveys Benchmarking Pricing Optimization & Revenue Management Design of Experiments Financial & Risk Management Search & Search Optimization Queuing, Simulation Statistical Process Control (R Charts, P Charts, etc.) Planning, Scheduling, & Dispatch; Campaign Tracking Decision Analysis, Multi-Criteria Decision Making, Game Theory Project & Program Management, PERT, CPM Quality Management (TQM, 6Sigma, ZeroDefect, etc.) Business Architecture & Systems Modeling Controls & Compliance (SOX, Basel, ISACA, etc.) Organizational Behavior, Organization Theory, and Strategic Mgmt Techniques: what methods & techniques do you use? Confidential 39CobotSystems.com o Frame the Decision Need o Generate Ideas o Support Decision Making o Monitor Execution o Drive Results
  40. 40. Systems: what tools do you use? … the BI view  Data Loading & Processing  Batch  Stream  Data Sourcing  Transactions  Conversations  Observations  Data Marts & Warehouses  Closed Access (only via IT)  Open Access  Offline Analytics Tools  Reporting  Dashboards  Self Service, Slice/Dice, Drill-down  Data Quality  In-line Analytics  Surveying & Feedback Confidential 40CobotSystems.com
  41. 41. Systems: what tools do you use? … the Analytics gap Confidential CobotSystems.com  Innovation  Frame decision needs in an enterprise model  Manage idea-to-execution pipeline  Visualize, Explore, Cluster, Segment, Forecast, Optimize, Simulate, Machine Learning, etc.  Decision support (AHP, MCDM, Bayes, etc.)  Operations  Execution (Trusted, Actionable, Responsive)  Learn & Ingrain  Data Provisioning  Agility, Reliability & Serviceability  Traceability & Fidelity  Data Assessment & Scrubbing  Manage Data Problems  Manage Data Dictionary  Master Data & Hierarchies  Enterprise Ontology Model  Shared Ontology & Enrichments  Privacy, Security and Availability 41
  42. 42. Capability: does the analytics team leverage the spectrum of analytics techniques 1. Get/provide data, measure and improve data quality 2. Observe, understand and explain business issues – create analyses, generate insights, monitor execution, guide value realization 3. Forecast trends, predict outcomes and behaviors (assess possibilities) 4. Formulate, simulate, and assess scenarios, develop ideas and courses of action (develop ideas) 5. Recommend courses of action (select the best ideas: feasible and optimal or Pareto optimal) Confidential 42CobotSystems.com  Statistics  OR  Decision Advice
  43. 43. Culture: how readily do business people use the analytics? 1. Unaware of how analytics can be used 2. Aware of analytics but do not use it for various reasons 3. Use analytics for specific decisions and actions 4. Support the creation and usage of analytics, metrics and decision rules in an organizational model, can assess the value of analytics 5. Leader in using analytics, recognize applicability, & demand the best analytics; innovate, learn, & ingrain analytics in business processes Confidential 43CobotSystems.com  Trusted  Actionable  Responsive  Learn  Ingrain
  44. 44. Technology: do the analytics teams get the systems, tools and infrastructure support they need? 1. Unable to provide analytics systems (data, tools & infrastructure) 2. Partially provides the analytics systems and data required and refreshes the data periodically for off-line analyses 3. Fully provides analytics systems and refreshes the data periodically for off-line analyses 4. Enables analytics to be executed in-line, i.e., used seamlessly within business processes 5. Delivers enterprise-wide in-line analytics, so the organization can use analytics at scale and without delay Confidential 44CobotSystems.com  Shared data  Trusted, Actionable, & Responsive  Fast decisions  Closed loop
  45. 45. Agenda  Introductions – about the group, about me. What is "analytics"? What is an "Analytics CoE"?  What does the organization want to do with analytics? What is the role of the CoE that they envision?  What is the organizational context? Current providers of analytics? Leadership support?  What will the Analytics CoE need to be like (now and in the future, up to the planning horizon)?  Where do we stand with analytics capabilities now, compared to what we need?  How will we evolve the CoE? Set expectations, drive the evolution, establish the value. Confidential 45CobotSystems.com
  46. 46. How will we evolve the CoE? Confidential 46CobotSystems.com  What is the organizational context? Current providers of analytics? Leadership support?  Where do we stand with analytics capabilities now, compared to what we need? TARGET STATE CURRENT STATE  What does the organization want to do with analytics? What is the role of the CoE that they envision?  What will the Analytics CoE need to be like (now and in the future, up to the planning horizon)?  How will we evolve the CoE? Set expectations, drive the evolution, establish the value
  47. 47. Establish the value Experimentation (A/B Compare)  The model is used in an “experimental” setting, against the current “gold standard” method  Compare the results of the model to the “gold standard” Before/After Compare  The model is deployed globally  Compare the results before and after the model is deployed (problem remains that there can be other explanatory factors) Confidential 47CobotSystems.com
  48. 48. Move fast & patiently What can be done fast  Bring right expertise (skills) into the analytics network  Set up the analytics platform What takes time  Change the decision-making culture of the organization Confidential 48CobotSystems.com  Produce relevant, trusted & actionable analytics  Help people to use the analytics deliverables  Track the value created What must be done right
  49. 49. Evolve the analytics process capabilities Failure is part of innovation … manage it by ensuring it occurs in the context of the analytics platform and processes (back those innovation efforts that have an idea-to-execution perspective, remember and learn) Confidential 49CobotSystems.com Concept to Value Realization Process Value Management Capability Value Management Organizational Value Management INNOVATION: TALENT-DRIVEN OPERATIONS: PROCESS-DRIVEN EVOLVE Role Coverage Obsolescence is part of operations … manage it by ensuring it occurs in the context of long term relevance (don’t lose memory)
  50. 50. Today 1 year 2 years 3 years 4 years Inconsistent Decisions Change the decision-making culture of the organization Consider leadership, trajectory, overshoot and undershoot Confidential 50CobotSystems.com SUPPLY Consistent & Disciplined Data Oriented Decision Models Learn & Ingrain DEMAND Jim Harry Tom Jim Harry Tom
  51. 51. This presentation is based on the material available in the book: Business Analytics: A Practitioner's Guide By Rahul Saxena & Anand Srinivasan Springer International Series in Operations Research & Management Science http://www.amazon.com/dp/1461460794

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