1. Session 1: The forecasting process Demand Forecasting and Planning in Crisis 30-31 July, Shanghai Joseph Ogrodowczyk, Ph.D.

2. Session 1 Joseph Ogrodowczyk, Ph.D. Demand Forecasting and Planning in Crisis 30-31 July, Shanghai 2 The forecasting process Session agenda  Practical guidelines to creating a forecasting process  Forecasting and revenue management: Are they the same?  Tips for the successful forecasting function  Disaggregation: Top-down or bottom-up?  Activity: Group discussion of forecasting process

3. Session 1 Joseph Ogrodowczyk, Ph.D. Demand Forecasting and Planning in Crisis 30-31 July, Shanghai 3 The forecasting process Practical Guidelines for Forecasting  What is forecasting? Numerical estimates achieved through a systematic process Systematic process using statistical and judgmental (expert) analysis Estimates targeted for specific dates or times in the future Estimates used for business planning purposes including strategic acquisitions, operational decisions, process improvement and other business goals

4. Session 1 Joseph Ogrodowczyk, Ph.D. Demand Forecasting and Planning in Crisis 30-31 July, Shanghai 4 The forecasting process Practical Guidelines for Forecasting  Why should businesses seek to forecast? Forecasting cannot be avoided  Everyone guesses about future events/information Forecasting (and data analysis) is a critical component to decision making  Better (more accurate) forecasts lead to better decisions Questions to guide the forecasting process  How will the forecasts be used?  What requires prediction?  What is the value of increased accuracy?  What resources/data are available for forecasting?  How can those resources/data be allocated?

5. Session 1 Joseph Ogrodowczyk, Ph.D. Demand Forecasting and Planning in Crisis 30-31 July, Shanghai 5 The forecasting process Practical Guidelines for Forecasting  Importance of measurement Overforecasting leads to excess inventory and overcapacity Underforecasting leads to product shortages and lines down What should be measured and how should it be measured?  Forecast accuracy & measurement metrics are covered on Day 2  Role of the forecaster Impartial data analyst, not biased implementer  Difficult role because we do not work in a vacuum, but unbiased forecasts require objectiveness Forecaster needs to be fully integrated into the decision making process

6. Session 1 Joseph Ogrodowczyk, Ph.D. Demand Forecasting and Planning in Crisis 30-31 July, Shanghai 6 The forecasting process Forecasting and Revenue Management  What is revenue management? Revenue management: selling the right product at the right time and price to maximize revenue (profit)  Revenue and profit are not the same Forecasting: Unbiased prediction of future demand usually unconstrained by capacity or other supply chain issues  How forecasting aids in revenue management Forecasting should be based on units, not dollars  Forecasting in dollars does not account for changes in prices against changes in quantities RM brings in pricing and costs

7. Session 1 Joseph Ogrodowczyk, Ph.D. Demand Forecasting and Planning in Crisis 30-31 July, Shanghai 7 The forecasting process Forecasting and Revenue Management  Temptations and pitfalls Forecasting in dollars  Forecasting in dollars does not account for changes in prices against changes in quantities Calculating forecasts based on revenue goals  This is backwards logic  Revenue goals originate in the finance department while forecasts originate with planning/capacity/supply chain  Best practice forecasts are separate from any production constraints (capacity, retail space, etc.)

8. Session 1 Joseph Ogrodowczyk, Ph.D. Demand Forecasting and Planning in Crisis 30-31 July, Shanghai 8 The forecasting process Tips for a successful forecasting function  Important elements in describing the forecasting process Purpose of forecast, including a timeframe  May include multiple forecasts for different objectives (e.g. strategic planning) Model type and any underlying model assumptions Historical data used Forecasts produced  Include units, hierarchy level (product, geography and time intersection) Graphical display of data and results Tracking and reporting accuracy of prior forecast performance

9. Session 1 Joseph Ogrodowczyk, Ph.D. Demand Forecasting and Planning in Crisis 30-31 July, Shanghai 9 The forecasting process Tips for a successful forecasting function  Knowing the limitations of forecasting Believing too much in the reliability of models can lead to underestimating future uncertainty Believing too little in the reliability of models can lead to omitting valuable information in the decision-making process  Management support Improvement in the forecasting process is dependent upon accountability of the forecasters and measurement of forecast Needed for a consensus forecast and company-wide use of forecast  Expert knowledge Can be used to guide statistical models Disagreements can illuminate important variables

10. Session 1 Joseph Ogrodowczyk, Ph.D. Demand Forecasting and Planning in Crisis 30-31 July, Shanghai 10 The forecasting process Disaggregation: Top-down or bottom-up  What is disaggregation and when is it used? Business needs often require forecasts to be made in groups such as similar customers, regional retail stores, family of products, or market segment Disaggregation is the distribution method for allocating quantities of a group forecast to the individual members

11. Session 1 Joseph Ogrodowczyk, Ph.D. Demand Forecasting and Planning in Crisis 30-31 July, Shanghai 11 The forecasting process Disaggregation: Top-down or bottom-up  Top-down forecasting: Producing forecasts at an aggregate level (by grouping products, customers, etc.) and allocating the forecasted quantities to its members  Reasons for top-down forecasting Data availability: Lack of historical data at lower level Resource accessibility: Inadequate resources for producing large sets of forecasts Forecasting implementation: Judgment forecasts and managerial adjustments are more easily accomplished at higher levels  Note: Forecasting at the lower level may be unwise Analyze the returns to and the costs associated with forecasting at lower-levels

12. Session 1 Joseph Ogrodowczyk, Ph.D. Demand Forecasting and Planning in Crisis 30-31 July, Shanghai 12 The forecasting process Disaggregation: Top-down or bottom-up  Bottom-up forecasting: Producing forecasts at customer, item, or store level (most detailed level of data available) and adding forecasts to produce aggregated information  Reasons for bottom-up forecasting Data behavior: Individual components have very different demand patterns Resource planning: Inventory, transportation logistics or product manufacturing requires specific information Disaggregation methods: No reliable method exists for disaggregation of forecasts. Benefits of chosen methods are subjective

13. Session 1 Joseph Ogrodowczyk, Ph.D. Demand Forecasting and Planning in Crisis 30-31 July, Shanghai 13 The forecasting process Disaggregation: Top-down or bottom-up? Top-down Examples

14. Session 1 Joseph Ogrodowczyk, Ph.D. Demand Forecasting and Planning in Crisis 30-31 July, Shanghai 14 The forecasting process Disaggregation: Top-down or bottom-up? Top-down Examples

15. Session 1 Joseph Ogrodowczyk, Ph.D. Demand Forecasting and Planning in Crisis 30-31 July, Shanghai 15 The forecasting process Disaggregation: Top-down or bottom-up? Bottom-up Examples

16. Session 1 Joseph Ogrodowczyk, Ph.D. Demand Forecasting and Planning in Crisis 30-31 July, Shanghai 16 The forecasting process Disaggregation: Top-down or bottom-up? Bottom-up Examples

17. Session 1 Joseph Ogrodowczyk, Ph.D. Demand Forecasting and Planning in Crisis 30-31 July, Shanghai 17 The forecasting process Disaggregation: Top-down or bottom-up?  Methods to disaggregation Disaggregate before forecasting (Called decomposition)  Bottom-up forecasting  Forecasting parts of the whole  Forecast trend and seasonal components separately Disaggregate after forecasting (done with Top-down)  Many methods for this based on:  Number of products within a grouping  Percentages of historical demand  Combining with bottom-up forecasts

18. Session 1 Joseph Ogrodowczyk, Ph.D. Demand Forecasting and Planning in Crisis 30-31 July, Shanghai 18 The forecasting process References  Jain, Chaman L. and Jack Malehorn. 2005. Practical Guide to Business Forecasting (2nd Ed.). Flushing, New York: Graceway Publishing Inc.  Lapide, Larry. 2006. Top-down and bottom-up forecasting in S&OP. Journal of Business Forecasting. Summer: 14-16.  Newbold, Paul and Theodore Bos. 1994. Introductory Business & Economic Forecasting (2nd Ed.). Cincinnati, Ohio: South-Western Publishing Co.