1. Demand Planning and Forecasting Session 5 Selecting and Monitoring a Forecast System By K. Sashi Rao Management Teacher and Trainer

2. Choice of Forecasting Method Time SpanPurposeForecasting Method LONG RANGE- 3 YEARS OR MORE Capital Budgeting Product Selection Plant Selection Delphi Expert Judgment Sales Force Composite Survey Methods INTERMEDIATE- 1 TO 3 YEARS Capacity Planning Sales Planning Regression Time Series Decomposition SHORT RANGE- 1 YEAR OR LESS Sales Forecasting Operational Scheduling Inventory Control Trend Projections Moving Averages Exponential Smoothing

3. Key Methodology Issues Choice of method/model determined by forecast need and purpose Accuracy level required for predictions and trade-offs involved Extent to which chosen model assumes past relationships and patterns which are expected to remain so in future Appropriate forecasting horizon that reflects current lead time for capacity creation Need to match existing business patterns( constant, trend, seasonal et al) with selected forecasting model

4. Developing the Forecasting Logic STARTSSTT Idnetify /////identify Develop Test STOP START STOP Identify PURPOSE -use -horizon -data needed Identify TECHNIQUE -collect/analyze past data -select suitable model Develop FORECASTING LOGIC -establish model parameters -build the model Test MODEL ADEQUACY -test using historical data MODEL SATISFACTORY ?? NO YES

5. 7-5 Basic Approach to Forecasting Understand the objectives of forecasting Integrate demand planning and forecasting Identify major factors that influence the demand forecast Understand and identify customer segments Determine the appropriate forecasting technique Establish performance and error measures for the forecast

6. Developing a Forecasting System Three step process involves: Developing a forecasting logic by identifying the purpose, data, models and methods to be used Establishing a control mechanism to obtain reliable forecasts Incorporating managerial considerations in using the forecasting system

7. Establishing a Forecast System Importing historical sales data Creating statistical forecasts Importing customer forecasts Collaborating with customers Managing forecasts Building consensus forecasts Supply and demand collaboration Securing constrained forecasts Confirmation with customers Re-examining data and adjusting planning accordingly.

8. Features of a Good Forecast Accuracy- with small errors Unbiased- so as not to overestimate or underestimate demand Responsiveness – to frequent changes in demand ( high alpha choice) Stability- strike balance with responsiveness ( low alpha choice) Accommodative – of odd unusual figures Timeliness – to meet its purpose Cost-effective- forecasts benefits more than costs Easiness - to understand and operate Sustaining- useful for reasonable time before needed changes

9. Forecasting Principles Unless method is 100% accurate( very rarely so!), the chosen one should be simple to understand and use by all concerned at all levels Every forecast should state the estimate of likely error as +/- % error ( as measure of accuracy) Individual items best forecast for shorter periods with only as groups/families of items for longer periods Managerial judgments should be used, if necessary, over forecasts generated by any method Forecasts are not an end in themselves, but done for a purpose, and should finally be useful for decision-making

10. 7-10 Forecasting in Practice Recognize that forecasting is an essential part of business planning Involve all those who can contribute to building good forecasts Actively collaborate with all above in building forecasts The value of data depends on where you are in the supply chain Be sure to distinguish between demand and sales forecasting Ensure that forecasting models are periodically reviewed for their utility of purpose

11. Forecasting Issues in Small/New Ventures They also need forecasts to plan and run their businesses But they don’t have data-rich environments Forecasting for new/constantly evolving products more challenging There may not be much historical/time series data They lack the resources and/or capability to develop and use advanced forecasting techniques Should make do with external data/forecasting resources Will still have to develop own practical forecasting solutions conscious of forecast inaccuracies

12. Managerial Issues in Forecasting G CH COSTDTIMTI GETTING STARTED - Choice of model - Estimation of parameters USING THE SYSTEM -how to incorporate external information -stability versus responsiveness CHANGING THE SYSTEM -parameter re-estimation versus model change COST- BENEFIT DATA AVAILABILTY TIME FRAME KEY INFERENCES NEW COMPETITION SALES PROMOTION FORECAST RELIABILITY

13. Some Last Words The future is not ‘knowable’ in the sense of exact predictions. Life is filled with surrealistic surprise. Even the seemingly ‘hardest ‘ models and data are frequently based on ‘soft’ assumptions – Alvin Toffler, Future Shock It is far better to foresee into the future without certainty than not to foresee at all- Henry Poincare

14. Thank you All the very best