2. Forecasting-Process Forecasts are estimates of timing and magnitude of the occurrence of future events Key functions: An estimation tool A way of addressing the complex and uncertain environment surrounding business decision making. A tool for predicting events related to operations, planning and control. A vital perquisite for the planning process in organizations.
3. Why do we forecast… Dynamic and complex environment Short term fluctuations in production Better materials management Rationalize man-power decisions Basis for planning and scheduling Strategic decisions
4. Focus-Forecasting-Introduction Bernie Smith- Servistardivision of TruValue Two Principle theory All complex forecasting models are not always better than simpler ones. No single technique for products and services Simple techniques that work on past data also helps in developing forecasts about future as well Reasonable approach for short term (period less than a year)
12. Contd.. For items with an irregular demand history Sales for the item in the next quarter will be half of actual sales over the last 6 months F = Forecast for the item over the next quarter Q1 = Actual Sales over the most recent 3 months° (example : 100) °the first quarter in the past counting backwards from now Q2 = Actual Sales over the 3 months before that ° (example : 150 ) ° the second quarter in the past counting backwards from now ( Q1 + Q2/2)=(100 + 150)/2 = 125 for the next quarter This formula generates a reasonable forecast despite a demand history needing to be corrected
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15. Helps people in forecasting seasonality, trends, items with sporadic history and other demand conditions
16. Selects the best option which results in the least error out of varied forecasting models
18. It can even include methods like exponential smoothing, if desired
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20. Ad hoc system with no theoretical basis to aid analysis or understanding.
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22. Contd… process involves the recognition of demand netting of those requirements against available and scheduled quantities generation of recommendations to meet those requirements proceeds top-down through the bill of material
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24. Contd.. Considers alternate forecast scenarios, and so the forecasts are stated in a Master Demand Schedule (MDS) determine how much demand satisfied from existing stock or existing orders Oracle Demand Planning generates forecast data. Oracle Inventory and Master Scheduling/MRP provide basic methods to generate forecasts from historical data one forecast typically contains multiple items; each item has multiple entries. For ease of use and to control forecast consumption, forecasts are grouped into forecast sets and forecasts and forecasts sets are identified by unique names
25. Generating Forecasts from Historical Information Statistical Forecasts: can span multiple periods and can recognize trend and seasonality. Focus Forecasts: examines five different forecast models against past history, determines the model that would best have predicted the history, and uses that model to generate a forecast for the current period
26. Generating Forecasts defining a forecast rule forecast method (statistical or focus), and the sources of demand in the Generate Forecast window Name of the forecast you want to populate. Forecast rule Selection criteria to identify the items An overwrite option Start date and cutoff date Post this Oracle uses Open Forecast interface and forecast entries API to integrate with other systems
