Crystal ball for EPM - Dave Hammal

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Oracle Hyperion Day 2011, 19.04.2011 r.

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  • It is not possible to use Crystal Ball Optquest directly against HSF.However, it is possible to use HSF & CB together for project selection / portfolio optimisation which is probably the likeliest use case when considering HSF.There is a recorded example at http://launch.oracle.com/?cbtraining called ‘Project Selection’
  • Ensure objective and requirements match those shown.Maximise the number of projects we can deliver with our available headcount
  • The optimisation is set to run for only 25 iterations.25 different possible numbers of projects are tested – each time checking that headcount restrictions are met.After 25 iterations, 30 seconds, we have a solution that maximises our utilisation
  • We can also use Crystal Ball to improve the what-if capabilities.Rather than searching for the best production levels and sales discounting in an ad-hoc style through trial and error we can make the search more structured through Crystal BallWe define what are our controllable inputs (% New Production and % discount) as CB Decision Variables and what are the feasible bounds to search within.
  • We can then use CB Optquest wizard to specify what it is our objective plus any other requirements or constraints.In this case we are setting the objective of bringing the WhatIf scenario back in line with our plan. (We set a target of WhatIf vs Plan = 0)
  • The optimiser searches for the best solution to bring stocks back to planned level. It quickly tells us the production and discount levels needed to achieve this.
  • The optimisation can be done at any level. Perhaps more realistically you would set different production levels or discounts for each location and/or product line.The more decisions or numbers you need to set the more advantage of using Crystal Ball for a structured search than the trial-and-error approach through just Essbase alone.
  • We can use Crystal Ball Predictor to also create time-series forecasts.
  • Use the Predictor wizard to first highlight the historical data that you would like to use to generate your forecast
  • CB Predictor will automatically detect if your historical data has seasonal patterns or not.
  • And fill in any missing values
  • It will then forecast using all the non-seasonal and seasonal methods…
  • …and rank them according to which is the best fitting.Value added to Essbase: More forecasting methods. Selection of method is data driven (not user selection) though can manually over-write if neededIn addition we get a range around the forecast. In this case the red lines around the forecast highlight our 90% confidence range. We can be 90% confident of the forecast being within this range
  • The best method is selected per data-series. E.g. for business line the seasonal additive was best fitting, where as for machines & co the double moving average works better
  • It is also possible to get the forecasted values for future time periods pasted as Crystal Ball Assumptions.We can see visually the uncertainty in our forecasts.These could then be used in a risk-analysis simulation
  • HSF and Crystal Ball results
  • CB results from the Portfolio model, submitted to essbase, reports with Answers
  • Using bin data to recreate forecast charts and charting all the stats and percentiles
  • Crystal ball for EPM - Dave Hammal

    1. 1.
    2. 2. Crystal Ball EPM<br />Dave Hammal 19th April 2011<br />Crystal Ball Solution Specialist Warsaw <br />
    3. 3. Agenda<br />Benefits of Crystal Ball<br />Crystal Ball EPM<br />Simulation – “What if?”<br />Forecasting – “What’s next?”<br />Optimisation – “What’s best?”<br />Discussion / Q&A<br />
    4. 4. Metrics are necessary, but are they sufficient?<br />
    5. 5. Metrics are necessary, but are they sufficient?<br /><ul><li>I can invest in Project A
    6. 6. With a forecast revenue of EUR100 million in the next fiscal year
    7. 7. And a 90% certainty of achieving that value
    8. 8. And a 100% certainty of a positive return (>$0 value)</li></ul>Or<br /><ul><li>I can invest in Project B
    9. 9. With a forecast revenue of EUR200 million in the next fiscal year
    10. 10. And a 40% certainty of achieving that value
    11. 11. And a 70% certainty of a positive return (>$0 value)</li></li></ul><li>Why Use Crystal Ball?<br />Use Crystal Ball to<br />See all possible outcomes<br />“Think in Ranges”<br />Improve quality of your decision making<br />Benefits to you<br />Easy<br />Effective<br />Enhance Credibility<br />
    12. 12. <ul><li> Range of Outcomes</li></ul>28%<br /><ul><li> Probability of Failure</li></ul>Profit<br />$2 M<br />- $2 M<br />- $4 M<br />$4 M<br />$6 M<br />$8 M<br />$0 M<br />Benefits of Simulation in Risk Analysis<br />What do you think would happen if we did not use simulation?<br />Would you accept this budget?<br /><ul><li> Single-Point Estimate</li></li></ul><li>Report on Risk<br />Planning<br />Siebel Marketing<br />Essbase<br /> HSF, HFM <br /> More<br />Credit Risk<br /> Earnings Per Share<br />Cash balance<br /> NPV<br /> More<br />Any Oracle Technology<br />Any Number<br />Finance, Energy<br />Life Sciences<br />Public Sector<br />Manufacturing<br />More<br />Any Industry<br />Model the scenarios<br />Calculate the probabilities<br />Report on the risk<br />See more than naked numbers. Report on key metrics PLUS their associated risk.<br />
    13. 13. Report on Risk<br />EBS Projects,<br />EBS Financials,<br />Siebel Marketing<br />Essbase<br /> EPM/BI,<br /> More<br />Costs,<br /> Finish dates,<br />Revenue,<br /> NPV<br /> More<br />Any Oracle Technology<br />Any Number<br />Manufacturing,<br />Construction,<br />Engineering,<br />Transport<br />More<br />Any Industry<br />Model the scenarios<br />Calculate the probabilities<br />Report on the risk<br />See more than naked numbers. Report on key metrics PLUS their associated risk.<br />
    14. 14. Crystal Ball DemoSimulationEURO 2012 Qualification<br />
    15. 15. Simulate the outcome of a match<br />
    16. 16. Simulate goals scored<br />
    17. 17. Step through to see simulated results<br />
    18. 18. Step through to see simulated results<br />
    19. 19. Extend to all Group fixtures<br />See Final Table<br />
    20. 20. Learn probability of qualifying<br />And the key fixtures<br />
    21. 21. Some countries have little hope<br />Repeat for any Group<br />
    22. 22. Capture Summary data<br />
    23. 23. What Are Simulations?<br />Process of experimenting with a model to measure performance and behavior of inputs in a system<br />What are the Benefits?<br />Gain general insight into the nature of a process<br />Identify problems with system design <br />Manage risk by understanding costs and benefits<br />
    24. 24. What Is Monte Carlo Simulation?<br />A system that uses random numbers to measure the effects of uncertainty.<br />A computer simulation of N (e.g. 1000) trials where<br />Each trial samples input values from defined probability distribution functions (PDFs)<br />Applies the input values to the model and records the output<br />Outputs:<br />Prediction of Output Variation (Probability of Cost Overrun, Probability of Exceeding Deadline)<br />Identification of Primary Variation Drivers (Sensitivity Analysis)<br />
    25. 25. Three Easy Steps to Mitigating Risk and Understanding Uncertainty<br />1. Model Uncertainty<br />Specify the range of input assumptions<br />Simulate possible outcomes (Monte Carlo)<br />
    26. 26. Three Easy Steps to Mitigating Risk and Understanding Uncertainty<br />1. Model<br />Specify the range of input assumptions<br />Simulate possible outcomes (Monte Carlo)<br />2. Quantify<br />Range and likelihood of outcomes<br />
    27. 27. Three Easy Steps to Mitigating Risk and Understanding Uncertainty<br />1. Model<br />Specify the range of input assumptions<br />Simulate possible outcomes (Monte Carlo)<br />2. Quantify<br />Range and likelihood of outcomes<br />Relative importance of input assumptions<br />
    28. 28. Three Easy Steps to Mitigating Risk and Understanding Uncertainty<br />1. Model<br />Specify the range of input assumptions<br />Simulate possible outcomes (Monte Carlo)<br />2. Quantify<br />Range and likelihood of outcomes<br />Relative importance of input assumptions<br />3. Decide<br />Focus on what matters<br />Prioritize the outcomes by balancing risk and reward<br />
    29. 29. Monte Carlo Simulation Results<br />Number of data points displayed in the chart for this response variable (Y)<br />Number of simulation trials performed<br />Parts within the spec limits are shown in blue, parts outside spec limits are shown red<br />Display range<br />Upper Spec Limit (USL) )/<br />Value of Interest<br />Lower Spec Limit (LSL)/<br />Value of Interest<br />Certainty (probability) that the forecast lies between LSL and USL<br />Explore the range of possible outcomes AND the probability of their occurrence<br />
    30. 30. Sensitivity Analysis Results<br />Examine which few critical factors (X’s) in your analysis cause the predominance of variation in the response variable of interest (Y) <br />
    31. 31. Crystal Ball EPM<br />
    32. 32. Simulation for Hyperion Strategic Finance<br />
    33. 33. Excel Can Lack Integrated Modeling to Assess Financial Impact of Corporate Strategy<br />Complex spreadsheet models<br />Spreadsheets are error prone<br />Limited accounting integrity<br />Typically built for a single purpose upfront <br />Grow increasingly more complex over time.<br />Lack of integrated models make scenario analysis cumbersome<br />Long simulation times<br />Banks<br />Board of Directors<br />Senior Management<br />Investor Community<br />Corporate Finance<br />Acquisition Targets<br />
    34. 34. Integrated Financial Modeling Critical to Manage Corporate Value<br />CFO<br />Treasury<br />Corporate<br />Finance<br />CorporateDevelopment<br /><ul><li>Top-Down Target Setting
    35. 35. Contingency Planning
    36. 36. Strategy Screening
    37. 37. Covenant/Ratio Analysis
    38. 38. Funding Alternatives
    39. 39. Rating Agencies
    40. 40. Mergers & Acquisitions
    41. 41. Valuation Analysis
    42. 42. Divestitures</li></li></ul><li>Executive Dashboard (Interactive Reporting): Evaluating Strategic Decisions<br />
    43. 43. What Crystal Ball brings to HSF<br />A simple-to-use simulation tool<br />Ability to easily think and work in ranges<br />Eliminate manual multiple what-if scenarios<br />Replace best/worst case estimates with more accurate range of all possible outcomes<br />Increased confidence in your numbers<br />Immediate insight on the key drivers and areas to focus your attention<br />Better quality decisions<br />
    44. 44. How Crystal Ball adds to HSF<br />Allows Monte Carlo Simulation using Crystal Ball to be added to HSF<br />HSF provides a robust financial model for Crystal Ball to work with<br />Wizard guides you through the set up where you<br />Quantify the uncertainty in your inputs such as Unit Sales<br />Define your key outputs of interest such as EPS<br />Quick access to the variability in your key metrics such as NPV, EPS<br />Learn the probability of the project being a success <br />Understand which factors are key to making it a success<br />
    45. 45. Crystal Ball and HSF Demo<br />
    46. 46. Use HSF to model your long term plan<br />
    47. 47. Use Crystal Ball to quantify uncertainty<br />Oil Production Rate<br />Oil Price<br />Oil presence!<br />
    48. 48. See impact on NPV<br />
    49. 49. Repeat for all Projects<br />
    50. 50. Compare all Projects<br />
    51. 51. Analyse Portfolio<br />
    52. 52. Benefits of Optimisation in Risk Analysis<br />Optimisation tells us “what’s best”<br />Used when there are numbers you have control over or decisions to make e.g.<br />Which projects should I select in my portfolio?<br />What should I set production levels at?<br />What’s the best price for my product?<br />How should I allocate my funds across my portfolio of investments<br />Optimisation combined with simulation allows us to know what’s best even in uncertain conditions<br />Which projects should I select to maximise NPV and ensure 95% certainty of at least break even<br />
    53. 53. Optimise your portfolio<br />
    54. 54. Compare to original<br />Verify Improvements<br />
    55. 55. Crystal Ball : Strategic Finance Setup<br />
    56. 56. Strategic Finance Setup : Choose HSF Entity<br />
    57. 57. Strategic Finance Setup : Choose Time Periods and Scenario<br />
    58. 58. Strategic Finance Setup : Choose HSF Accounts to be Defined as CB Assumptions<br />
    59. 59. Strategic Finance Setup: Choose HSF Account(s) to be Defined as CB Forecast(s)<br />
    60. 60. Setup Complete : Strategic Finance Worksheet<br />
    61. 61. CB : Define Assumptions and Forecasts<br />*To Run Simulation*<br />*Displays HSF Forecast Method*<br />*Displays HSF Forecast Methods*<br />
    62. 62. Crystal Ball Analysis<br />
    63. 63. Data flow between Crystal Ball & HSF<br />Wizard Set-Up<br />
    64. 64. Align the Enterprise Planning Process<br />Strategic Planning<br />Corporate<br />Development<br />Long-TermPlanning<br />ValueManagement<br />Treasury<br />Strategies<br />UpdateStrategic Planswith Latest Forecasts<br />Hyperion Strategic Finance<br />Seed Budgets with Strategic Targets<br />Hyperion Planning<br />PeriodicForecasts<br />Annual<br />Budget<br />Capital<br />Planning<br />Workforce<br />Planning<br />Planning, Budgeting and Forecasting<br />
    65. 65. AstraZenecaHyperion Strategic Finance and Crystal Ball EPM<br /><ul><li>Business Problem
    66. 66. Long term group financial planning currently in disparate Excel models
    67. 67. Need to see impact of risks and opportunities on EPS & Cash Flow
    68. 68. Risk management subcontracted making it difficult to drill into details, modify or perform ad-hoc analysis
    69. 69. Solution
    70. 70. HSF provides a common, centralized long term modeling solution
    71. 71. HSF model designed with risks and opportunities each having a probability and associated impact
    72. 72. Crystal Ball simulates all possible risks & opportunities, quantifying the impact on EPS & Cash Flow
    73. 73. Sales team
    74. 74. Sales: Paul Houghton (HSF) & Justin Stewart (CB)
    75. 75. Pre-sales: Dave Hammal and Graham Cardwell (now at Blue Stone)
    76. 76. About
    77. 77. One of the world’s leading pharmaceutical companies
    78. 78. Sales in 2009: US$ 32.8 Billion
    79. 79. Employees: 62,000
    80. 80. Products
    81. 81. Hyperion Strategic Finance
    82. 82. Oracle Crystal Ball EPM
    83. 83. Implementation
    84. 84. Live: August 2010
    85. 85. Users:25
    86. 86. Partner: Blue Stone International implemented HSF and CB with support from CB team via Oracle On Demand</li></ul>Internal Use Only<br />September 2010<br />
    87. 87. Crystal Ball DemoForecasting<br />
    88. 88. Crystal Ball DemoOptimisation<br />
    89. 89. Forecasting with HFM<br />
    90. 90. What Crystal Ball brings to HFM<br />A simple to use but highly effective forecasting tool<br />Improved accuracy in your forecasts<br />Increased confidence in your numbers<br />Better quality decisions<br />
    91. 91. Crystal Ball with HFM: Forecasting<br />Analyses the levels, trends and cycles within your historical data<br />Uses time-series forecasting methods to make statistically sound predictions<br />Gives predictions as distributions allowing you to talk with confidence about the likelihood of hitting your goals<br />Ability to modify base prediction with expert opinion accounting for increased sales due to marketing campaign or effect of increased competition<br />Validate your rolled-up plan. What does history say about likelihood of hitting our plan?<br />
    92. 92. Data Flow: Forecasting with Planning & CB<br />time<br />Planning or Essbase or HFM or Enterprise<br />SmartView<br />Submit Data<br />SmartView<br />Retrieve Data<br />Actuals<br />Forecast<br />
    93. 93. Crystal Ball DemoForecasting with HFM<br />
    94. 94. Crystal Ball & Essbase<br />
    95. 95. Crystal ball & Essbase<br />Essbase as a data source<br />Essbase as a model<br />Simulation<br />Optimisation<br />Essbase for reporting<br />
    96. 96. Essbase as a data source<br />Use Essbase to store the data for use in an Excel model<br />Ensures integrity of data<br />Single version of the truth<br />Allows a model to be re-used<br />If you have a standardised model, re-use changing the inputs for the new project from a guaranteed data source<br />
    97. 97. Use Essbase to store all your data<br />
    98. 98. Retain your Excel models <br />Have model inputs stored in Essbase<br />
    99. 99. Simply change the project on the drop down<br />
    100. 100. Refresh the data. Then you can re-use the same Excel model for another project<br />
    101. 101. Essbase as a model<br />An alternative modelling tool to MS Excel<br />Replace your Excel model with an Essbase model<br />Secure access<br />Same central model can be used by many<br />Any view of the data<br />Works for both simulation and optimisation<br />
    102. 102. No longer any formula in the spreadsheet<br />
    103. 103. They are held centrally in the secure Essbase Outline<br />
    104. 104. Crystal Ball with Essbase: Simulation<br />Address the uncertainty in your Essbase models<br />Use the logic and business rules of Essbase<br />Use the Monte Carlo Simulation of Crystal Ball<br />Use on any ad-hoc view in SmartView<br />Place Crystal Ball Assumptions on your uncertain inputs<br />Place Crystal Ball Forecasts on your key outputs of interest<br />Increased confidence in your numbers<br />
    105. 105. Data Flow: Simulation with Essbase & CB<br />sample<br />submit<br />retrieve<br />recalculate<br />
    106. 106. Demonstration:Crystal Ball simulation with Essbase<br />
    107. 107. An Example – Cost Estimation<br />Problem: What is the project really going to cost?<br />How much should I budget for?<br />What target should I set for the contractor’s incentive scheme?<br />
    108. 108. What is the project going to cost?<br />
    109. 109. Model in Essbase<br />
    110. 110. Quantify Uncertainty<br />
    111. 111. Simulate with Crystal Ball<br />
    112. 112. Understand the Key Drivers<br />
    113. 113. Set realistic budgets and targets<br />
    114. 114. Crystal Ball with Essbase: Optimisation<br />Optimisation tells us “what’s best”<br />Used when there are numbers you have control over or decisions to make e.g.<br />What should I set production levels at?<br />What’s the best price for my product?<br />Which projects should I select in my portfolio?<br />
    115. 115. Value added to Essbase<br />Improved what-if analysis<br />Structured search for best solution through optimisation algoirthms<br />Essbase what-if is simply manual trial and error<br />Wizard interface for setting of objective, requirements and constraints<br />Best solution highlighted for submitting back to Essbase<br />All solutions recorded for quick comparison and improved decision making<br />
    116. 116. Demonstration:Crystal Ball with Essbase Optimisation<br />
    117. 117. Resource Optimisation<br />Problem: Headcount requirements above staffing levels<br />Driver:-<br />Number of projected projects<br />
    118. 118. Headcount is above our capacity of 10<br />
    119. 119. Same BI data through Essbase<br />
    120. 120. Set goals<br />
    121. 121. Our optimal solution is found<br />
    122. 122. Copy Solution back to spreadsheet<br />
    123. 123. Submit back to Essbase<br />
    124. 124. Headcount of 10 for What If scenario<br />
    125. 125. Coffee demo<br />Inventory levels are too high – how can we reduce?<br />Drivers:-<br />Production levels<br />Sales discounting<br />Click to jump to Summary<br />
    126. 126. Inventory levels too high vs plan<br />
    127. 127. Define drivers<br />
    128. 128. Set goals<br />
    129. 129. Our optimal solution is found<br />
    130. 130. Stock levels are back to plan<br />
    131. 131.
    132. 132. Easily expand to other dimensions<br />
    133. 133. Essbase for Reporting<br />At the end of a simulation and/or optimisation you have a lot of data<br />Essbase can provide storage of that data which you can then slice and dice into whatever view you like<br />Useful for reporting to compare<br />Different scenarios from a simulation<br />Different decisions in an optimisation<br />
    134. 134. After an optimisation we can access data from all iterations<br />
    135. 135. Then extract all the data and submit to an Essbase cube<br />
    136. 136. In this case we use Visual Explorer to view all portfolios<br />
    137. 137. Then handpick the one we like<br />
    138. 138. Demonstration:Crystal Ball with Essbase Forecasting<br />
    139. 139.
    140. 140.
    141. 141.
    142. 142.
    143. 143.
    144. 144.
    145. 145.
    146. 146.
    147. 147. Benefits of forecasting<br />Forecasting tells us “What’s next”<br />Analyses the levels, trends and cycles within your historical data<br />Uses time-series forecasting methods to make statistically sound predictions<br />Option to choose which forecast to accept based on confidence levels<br />E.g. select 20% to have a forecast you are 80% certain of surpassing<br />Optionally, get predictions as distributions to feed a simulation<br />
    148. 148. Predictive Modeling for Hyperion Planning<br />
    149. 149. What Crystal Ball brings to Planning<br />A simple-to-use but highly effective tool for:<br />Simulation – “What if?”<br />Forecasting – “What’s next?”<br />Optimisation – “What’s best?” <br />Improved accuracy in your forecasts<br />Increased confidence in your numbers<br />Better quality decisions<br />
    150. 150. Crystal Ball with Planning: Forecasting<br />Forecasting tells us “What’s next”<br />Analyses the levels, trends and cycles within your historical data<br />Uses time-series forecasting methods to make statistically sound predictions<br />Overlay special events e.g. marketing campaign<br />Choose which forecast to accept based on confidence levels<br />E.g. select 20% to have a forecast you are 80% certain of surpassing<br />Optionally, get predictions as distributions to feed a simulation<br />
    151. 151. Crystal Ball DemoForecasting with Planning<br />
    152. 152. Data Flow: Forecasting with Planning & CB<br />time<br />Planning or Essbase or HFM or Enterprise<br />SmartView<br />Submit Data<br />SmartView<br />Retrieve Data<br />Actuals<br />Forecast<br />
    153. 153. Crystal Ball with Planning: Simulation<br />Address the uncertainty in your planning models<br />Use the logic and business rules of Planning/Essbase<br />Use the Monte Carlo Simulation of Crystal Ball<br />Use on any planning form or ad-hoc view in SmartView<br />Place Crystal Ball Assumptions on your uncertain inputs<br />Place Crystal Ball Forecasts on your key outputs of interest<br />Increased confidence in your numbers<br />
    154. 154. Data Flow: Simulation with Planning & CB<br />Planning or Essbase or HPCM<br />
    155. 155. Crystal Ball DemoSimulation with Planning<br />
    156. 156. Crystal Ball DemoOptimisation with Planning<br />
    157. 157. Crystal Ball & Business Intelligence<br />Reporting<br />Add Crystal Ball data to BI reports<br />
    158. 158. Add certainty to any reported number<br />
    159. 159. Report on any statistics…<br />…or percentiles<br />
    160. 160. Recreate forecast charts<br />
    161. 161. Summary<br />Crystal Ball is an Uncertainty Management tool for Uncertain times.  <br />Failure to include the impact of uncertainty and risk in your analyses can derail your financial plans<br />Crystal Ball is an easy to use tool that allows you to:<br />quantify the uncertainty in your inputs<br />see how these see the impact your KPI’s <br />understand what are the biggest risk drivers.<br />The result is better quality decisions and increased confidence in your numbers<br />
    162. 162. Q & A<br />For Further Info:<br />http://launch.oracle.com<br />PIN: CBWarsaw<br />

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