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Service Costing/TCO Data Assessment

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Workshop Guide slides from the Atlanta ITFMA conference- Presented July 13, 2015.
How to assess your data readiness for Service Costing/TCO activities.
Note, the second half of the workshop was in spreadsheets note included here. Please contact us for more information or templates.

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Service Costing/TCO Data Assessment

  1. 1. Data Prep for Service Costing Copyright 2014 Thavron Solutions, LLC
  2. 2. Agenda • Introductions • Overview • What is Data Maturity? • Assessment- – Why – When – How • Opportunities for small group data evaluations Copyright 2014 Thavron Solutions, LLC
  3. 3. INTRODUCTIONS Copyright 2014 Thavron Solutions, LLC
  4. 4. Introductions • Us: Nan Braun • CEO Thavron Solutions • nbraun@thavronsolutions.com/ @thavronsol / http://thavron.com/blog • Corporate IT – many roles- “hands” on to BRM to architecture • CTO, ontological modeling • Director, TBM Practice Terry Dawkins • TBM Consultant/Data Architect Thavron Solutions • tdawkins@thavronsolutions.com Copyright 2014 Thavron Solutions, LLC
  5. 5. Introductions • You? – Name – Role – Company/Organization – Did you bring data to work on? Copyright 2014 Thavron Solutions, LLC
  6. 6. Thavron Biases • Systems Thinking • Universal Business Service Model • Manufacturing – Lean (MESA Lean Manufacturing Strategic Initiative Guidebook author, Toyota Method via GM/Delphi) • Modeling/Frameworks • Common Sense Copyright 2015 Thavron Solutions, LLC
  7. 7. OVERVIEW Data Model for Service Costing Copyright 2015 Thavron Solutions, LLC
  8. 8. Data for Service Costing • Dependent on Service Costing Philosophy – Defined Allocation – Calculated Allocation – Consumption – Based Model Copyright 2015 Thavron Solutions, LLC
  9. 9. Assessment Philosophy Design First, then Assess for Capability • Design ideal model based on Stakeholder input • Pros: – Stakeholder buy in /ownsership – Ideal solution from the start • Cons: – Data not capable of supporting model – Project “hangs” or collapses Assess first, Design to Capability • Understand current data status, design model to capability with specific maturity goals • Pros: – Design will succeed – Rapid transparency to data “imperfections” • Cons: – Resistance to evolving/maturing model Copyright 2014 Thavron Solutions, LLC
  10. 10. Types of data for a Consumption Based Model • Service Cost Components: – Labor – Infrastructure – Software – Maintenance & Support – Ongoing Development – Depreciation – Service Consumption Records Copyright 2015 Thavron Solutions, LLC
  11. 11. Where does the data come from? • Finance System • Depreciation Tracking • CMDB • Asset Management • Storage Management System(s) • Data Center Management • Project Management/Tracking • Ticketing System(s) • Server Management Software • VCenter or equivalent • Cloud Provider Invoicing • HRIS • Network Management System(s) • License Management System(s) Copyright 2015 Thavron Solutions, LLC
  12. 12. How Does the Data Fit Together? • Not a direct linkage to Service in all data sources- – Layered model / Cost Components that are assembled into Services • Does need key field linkage between data sources within components or Business Rules that link them together. Copyright 2014 Thavron Solutions, LLC
  13. 13. What to measure? • Stability • Completeness • Correctness Copyright 2014 Thavron Solutions, LLC
  14. 14. Data Stability • Column order and headers are unchanging • Values in a column are consistent in meaning – no context sensitive values • Format of data is stable over time and between data sources – Automated versus hand entered Copyright 2014 Thavron Solutions, LLC
  15. 15. Data Completeness • 80-90 % of data needed for common linkages are present • Are your required fields also required data fields in source system? Copyright 2014 Thavron Solutions, LLC
  16. 16. Data Correctness • Effort to measure before modeling begins almost never worth the “win” • Ownership belongs with Source Data Owners – Engage them early and share reports/results frequently – Build a partnership Copyright 2014 Thavron Solutions, LLC
  17. 17. The Myth of Perfect Data Myth: You need perfectly clean and aligned data to get insight to service costing Fact: You need data that is “clean enough” to allow your model to function consistently to get insight to service costing Copyright 2015 Thavron Solutions, LLC
  18. 18. What is Clean Enough to Build? • Contains key fields needed to model • Data has good Stability • Data has reasonable Completeness • Correctness will come with validation Copyright 2015 Thavron Solutions, LLC
  19. 19. Creating a Data Assessment Plan • Coordinate with Source System owners/SMEs • Extracts in raw format for assessment • Careful measurement of Stability and completeness • Calculation of maturity and readiness Copyright 2015 Thavron Solutions, LLC
  20. 20. Pitfalls • Data Samples can miss errors/problems • Perception of “problem data” can slow down your project • Data Extracts change when you go to launch • System changes/updates/upgrades impact extracts Copyright 2015 Thavron Solutions, LLC
  21. 21. DATA ASSESSMENT: ASSESSMENT HOW TO Copyright 2015 Thavron Solutions, LLC

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