The Planning Maturity Curve (Palo Alto June 15)

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The Planning Maturity Curve (Palo Alto June 15)

  1. 1. The Planning Maturity Curve: Where Are You? Where Do You Want to Be? Rand Heer, CEO Alight PlanningBen Lamorte, VP Marking Alight Planning © 2011 Alight Planning Slide 1
  2. 2. Today‘s SpeakerRand Heer Business Activities  CEO, Alight Planning (Planning software)  Co-Founder, Aspirity (Microsoft BI consulting)  Founder, FP&A Train (Essbase training)  Founder, Pillar Corporation (Enterprise budgeting)  CFO for 2 public companies  Rockwell Int‘l, Biz Unit CFO and Corporate Publications  Coauthor: “Business Intelligence: Making Better Decisions Faster”  Author of 10 white papers on planning/reporting topics Education  MBA degree Harvard Business School © 2011 Alight Planning Slide 2
  3. 3. Agenda Introductions The Planning Maturity Curve  Level One: Seat of the Pants  Level Two: Budgeting  Level Three: Reporting  Level Four: Forecasting  Level Five: Agile Planning Case Study in Agile Planning: Pittsburgh Mercy Short Break Agile Planning Simulation Implementing Agile Planning  Out of Excel  Level of Detail  Driver-Based Planning  Integrating Actuals  Scenario Analysis © 2011 Alight Planning Slide 3
  4. 4. Business Value from Planning Insights  Understanding things we didn‘t see before Actionable Knowledge  Planning scenarios gives us the financial impact of choices Decisions  Having choices sets up decision making © 2011 Alight Planning Slide 4
  5. 5. Planning Maturity—Agile PlanningEffort Planning Maturity Curve (PMC) Forecasting Reporting Forecasting/Agile Planning Budgeting Seat of Pants Business Value © 2011 Alight Planning Slide 5
  6. 6. Capability Maturity Model for FP&A Seat of Pants Budgeting Reporting Forecasting Agile PlanningGoals Why Do It? EffectivenessKey Process Areas The Capability Maturity Model Who Drives Carnegie Mellon University Who Participates First described by Watts Humphrey Frequency Cycle time  Capability Maturity Model applied to financialFeatures planning and analysis. Data Type Data entry Level of detailPractices Modeling Data Integration Iteration Tools Presentation © 2011 Alight Planning Slide 6
  7. 7. Planning Maturity—Seat-of-Pants The Happy Caveman © 2011 Alight Planning Slide 7
  8. 8. Planning Maturity—Budgeting The Happy Accountant © 2011 Alight Planning Slide 8
  9. 9. Planning Maturity—Budgeting The Happy Accountant © 2011 Alight Planning Slide 9
  10. 10. Planning Maturity—Reporting The Reluctant Managers © 2011 Alight Planning Slide 10
  11. 11. Planning Maturity—Forecasting The Grumpy CFO © 2011 Alight Planning Slide 11
  12. 12. Where Are You on the Curve? © 2011 Alight Planning Slide 12
  13. 13. Planning Maturity—Agile Planning The Happy Team © 2011 Alight Planning Slide 13
  14. 14. Planning Maturity—Full Matrix © 2011 Alight Planning Slide 14
  15. 15. Planning Maturity—Agile PlanningEffort Planning Maturity Curve (PMC) Forecasting Implement driver-based planning Integrate (don’t just import) actuals Reporting Implement scenario analysis Forecasting/Agile Planning Move out of Excel Reduce level of detail Budgeting Seat of Pants Business Value © 2011 Alight Planning Slide 15
  16. 16. Case Study: Pittsburgh MercyRay Wolfe Business Activities  Chief Financial Officer, Pittsburgh Mercy Health System 2006-present  Director of Fiscal and Information Systems– Mercy Behavioral Health 1996-2006  Chief Fiscal Officer, Summit Center for Human Development, 1988-1996  St. Francis Medical Center, Patient Account Manager, 1986-1988 Awards: Ventana Leadership 2010 Education  Juris Doctorate, West Virginia University 1977  BA, Marshall University, 1974 © 2011 Alight Planning Slide 16
  17. 17. Case Study: Pittsburgh Mercy Community Mental Health and Health Care Related  Mental Health, Mental Retardation, Drug/Alcohol, Homeless  Prevention Services and a Private Foundation  Serving Southwestern Pennsylvania Business Metrics Pittsburgh Mercy Health System has  3 subsidiary corporations  60 community locations  27 major programs product lines  260 revenue/cost center  1,700 employees; 106 Managers & Supervisors  Funded through traditional insurance billing, government grants and capitation contracts, Private Foundations © 2011 Alight Planning Slide 17
  18. 18. Case Study: Pittsburgh Mercy Demographic Problems  Managers with only clinical backgrounds/ no business skills  60 sites yielded communication barriers and no common language Excel based —  Overload mode of worksheets with link and formula errors  Too much time to maintain and no certainty of integrity  No way to import and compare actual data to the budget design Budgeting became a ritual without meaning  Budgeting full year totals with no seasonality  Tops down budgets w/o manager buy in  No P&L visibility by critical factors  No operational integration © 2011 Alight Planning Slide 18
  19. 19. Case Study: Pittsburgh Mercy Organization of Forecast Groups and Processes  Group managers by functional areas—e.g.  Community Treatment Teams  Outpatient Clinics  Child Services  15 Groups each meet once a quarter  3 to 12 managers per group  4 members from accounting/finance  Real time process elements  Alight Planning displayed on Overhead Projector with Smart Board  CFO is facilitator; Alight Admin on the mouse and keyboard  Review/ make changes in real time  Everyone sees everything! © 2011 Alight Planning Slide 19
  20. 20. Level of Detail Technical Issues  What level of detail? Actuals and plan  Transportation example © 2011 Alight Planning Slide 20
  21. 21. Using Actuals to Drive Plan Technical Issues  Visibility into Units/Rates/Amounts  Revenue and Allowance Rate Example © 2011 Alight Planning Slide 21
  22. 22. Case Study: Pittsburgh Mercy Progress to Date  Financial Results  $600K+ in documented revenue increases and cost cuts from MET goals  Process Results  No budgeting  Global updates twice a year – detailed updates quarterly  Forecast accuracy to 2%  Manager commitments based on demonstrated best practices  Understanding the business as an operating entity  Reaction to issues on a two year horizon, e.g. present cut plan  Model Status  Now on third model iteration built from scratch © 2011 Alight Planning Slide 22
  23. 23. Planning Maturity—Agile PlanningEffort Planning Maturity Curve (PMC) Forecasting Implement driver-based planning Integrate (don’t just import) actuals Reporting Implement scenario analysis Forecasting/Agile Planning Move out of Excel Reduce level of detail Budgeting Seat of Pants Business Value © 2011 Alight Planning Slide 23
  24. 24. Guidelines for Agile PlanningTM1. Move Out of Excel  Deal with structure issues  Deal with modeling issues2. Reduce Level of Detail  Plan the way managers think; not the Happy Accountant  Reduce detail to better integrate strategy3. Implement Driver-Based Planning  Reduce direct input data volumes  Increase ‗modeled elements‘—operational/driver based planning4. Integrate (Don‘t Just Import) Actuals  ―Rolling over‖ actuals in plan files—apples to apples  Using actuals to understand trends—focus on rates5. Implement Scenario Analysis  You can‘t predict the future, but you can construct scenarios  You‘re looking for easy maintenance and comparisons at all levels © 2011 Alight Planning Slide 24
  25. 25. The Need for Real Time The Excel PowerPoint Cycle © 2011 Alight Planning Slide 25
  26. 26. The Need for Real Time The ―need for speed‖  Everything refreshes in near real time  The planning tool is the presentation tool  The planning tool enables collaboration on-the-fly © 2011 Alight Planning Slide 26
  27. 27. Agile Planning Simulation Background  Wombat, Ltd: mid market ERP for verticals: healthcare, manufacturing, technology  Bongo is main competitor in manufacturing  Event driver: Bongo cuts prices 30% in manufacturing The Players  Ben, Sales Guy  Rand, Finance Guy  Sid, Services Guy  Phyllis, CEO (not present) What You‘ll See  Real Time Collaboration  Driver-Based Financial Model  Scenario Planning © 2011 Alight Planning Slide 27
  28. 28. Follow Up with Alight Follow up with Ben  Blamorte@AlightPlanning. com  Telephone: (415) 456-8528 Webinar Resources  Transforming Planning at Pittsburgh Mercy:  www.Alightplanning.com/Webinars/PM/Video.html  Application Requirements for Rolling Forecasts  www.AlightPlanning.com/Workshop/Requirements-for-Rolling-Forecasts/Video.html  Forecasting for Black Swans:  www.ie.articfoxtv.com/224/planning-for-black-swans © 2011 Alight Planning Slide 28
  29. 29. 1. Out of Excel Structure Issues  Bound by templates: can‘t add line items on-the-fly  Rollup structures with dimensions are difficult to create and maintain  No multi-user security/process controls  Importing (rekeying) actuals is error prone/cumbersome Structure problems Save As relate to budget templates where you need to build in structure and financial intelligence from scratch. Version A Version N… © 2011 Alight Planning Slide 29
  30. 30. 1. Out of Excel Modeling Issues  Formula and structure errors—aka #Refs  Dependency on key individuals—Lone Ranger Syndrome  Line manager spreadsheet skills are limited; untrained/dangerous. Modeling problems: cell- based linking which discourages driver-based planning which is the source of most errors. © 2011 Alight Planning Slide 30
  31. 31. 1. Out of Excel What to Look for in Planning Applications  You can build rollup structures with multiple dimensions/attributes  Application incorporates multi-user security and process controls  Users can create line items on-the-fly without breaking things A fundamental deliverable of a Planning Application is user security and process controls. © 2011 Alight Planning Slide 31
  32. 32. 1. Out of Excel What to Look for in Planning Applications  You can build rollup structures with multiple dimensions/attributes  Application incorporates multi-user security and process controls  Users can create line items on-the-fly without breaking things  Importing capabilities—aka ETL (Extract, Transform & Load)  Object-based linking with audit trails Object-based linking is critical for implementing driver-based planning. © 2011 Alight Planning Slide 32
  33. 33. 2. Reduce Level of Detail Plan at the Right Level  Lowest level natural class accounts create too much detail  Let managers plan the way they think  Set the stage for driver-based planning It‘s the data that‘s the killer 7 T&E accounts * 100 cost centers * 12 months = 8,400 © 2011 Alight Planning Slide 33
  34. 34. 2. Reduce Level of Detail Guidelines for ―Right Level‖  Plan/report at a higher level—especially for natural accounts; or  Set up a dual system: traditional budgeting plus forecast at higher level.  Do the math for various alternatives; test imports for a ‗visual picture‘.  Go step-by-step: not everything need be done all at once.  The planning application must have line item detail Example of an account structure at a higher level with line items created by managers. © 2011 Alight Planning Slide 34
  35. 35. 2. Reduce Level of Detail Benefits of Reducing Level of Detail  Better operational connection for line managers  Reduces overall data volumes; better visibility  Set the stage for driver-based planning Reducing level of detail along with moving out of spreadsheets reduces Effort and enhances Business Value. © 2011 Alight Planning Slide 35
  36. 36. 3. Driver-Based Planning What Is Driver-Based Planning?  A series of sub-models for revenues and expenses based on drivers  Drivers are typically units of things: unit sales, customers, transactions  The fundamental structure is: Units * Rate = Amount  The spending focus is on big ticket items and large departments Example of a driver model that calculates amount of explosives for a gold mining operation. © 2011 Alight Planning Slide 36
  37. 37. 3. Driver-Based PlanningSoftware Conversion # Services Hours Per Billable Bill Rate BillableLicenses rate Customers Customer Services Services Sold Hours Revenues Predictive logic diagram for a software/services business It’s about Activities & Rates © 2011 Alight Planning Slide 37
  38. 38. 3. Driver-Based PlanningSoftware Conversion # Services Hours Per Billable Bill Rate BillableLicenses rate Customers Customer Services Services Sold Hours Revenues Staff Utilization Predictive logic Rate diagram for a Services Hours Per Services Staffing Month Staffing software/services Hours Heads business Services Expenses  Salaries It’s about  PR taxes/ benefits  Supplies Activities & Rates  Travel  Recruitment Training  Etc. Services Profitability © 2011 Alight Planning Slide 38
  39. 39. 3. Driver-Based Planning Benefits of Driver-Based Planning?  Tight turn-around for forecasting has a chance  Enforces focus on important operational drivers  Visibility into the numbers—allows meaningful causal analysis of variances  Sets up ―real time planning‖ for scenario analysis Driver-based planning delivers a significant increase in Business Value © 2011 Alight Planning Slide 39
  40. 40. 4. Integrate Actuals Import Actuals  Metadata and data imports based on chart of accounts structures  Monthly updates from the general ledger  Automated with ―connectors‖ or semi-automated with ETL tools Integrate Actuals  Any source—GL,HR, CRM, RDBMS, OLAP  Any data type—text, number, currency, percentage, currency  Any level—line item, natural accounts, cost center, etc.  Any modeling—simple of complex linking, back calculate rates © 2011 Alight Planning Slide 40
  41. 41. 4. Integrate Actuals Integration Issues  Data spread across multiple sources  Actuals and Plan at different levels  No underlying activity drivers  Actual and plan structures out of sync © 2011 Alight Planning Slide 41
  42. 42. 4. Integrate Actuals Integration Issues  Data spread across multiple sources  Actuals and Plan at different levels  No underlying activity drivers  Actual and plan structures out of sync © 2011 Alight Planning Slide 42
  43. 43. 5. Implement Scenario Analysis Deliverables  Insights: What‘s Going On with the Numbers  Actionable Knowledge: What Are Our Choices Between Things To Do  Decisions: ―OK gang, here‘s what we‘re going to do!‖ About the Future “Trying to predict the future is like driving down a country road at night with no lights while looking out the back window.” Peter Drucker “The future ain’t what it used to be…” Yogi Berra © 2011 Alight Planning Slide 43
  44. 44. 5. Implement Scenario Analysis Types of Scenario Analysis  Manage Resource Allocations: Adjust Short Term ―Who Gets What‖  Strategic Planning: Extend Time Frames; Same Model As Short Term © 2011 Alight Planning Slide 44
  45. 45. 5. Implement Scenario Analysis Types of Scenario Analysis  Manage Resource Allocations: Adjust Short Term ―Who Gets What‖  Strategic Planning: Extend Time Frames; Same Model As Short Term  Black Swan Planning: Understand Improbable Events [Nassim Taleb] © 2011 Alight Planning Slide 45
  46. 46. 5. Implement Scenario Analysis Implementation Guidelines  Easy to Create: On-the-Fly; No IT; Selectively Include Line Managers  Easy to Maintain: Change Data and Structure in Near Real Time  Scenario Drill Down: Comparison & Analysis at All Levels  Real Time Feedback: The Planning Tool is the Presentation Tool © 2011 Alight Planning Slide 46
  47. 47. Spreadsheet Issues Spreadsheets Don‘t Do the Job  Not multi-user: security and process control issues  Not a database: consolidation and reporting issues  Not multi-dimensional: reporting and analysis issues  Cell based modeling: limitations on driver-based planning  Save As for versions and scenarios: just not viable! Scenario A Scenario B Scenario C © 2011 Alight Planning Slide 47

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