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• W63673053 abstract "EXECUTIVE SUMMARY |Because of rapidly changing market dynamics, exceptions are now part of doing business. To survive and grow in this market, it is important to leverage exceptions; this article outlines a strategy to leverage them. To do that, the author suggests first preparing exception reports by ABC classification, at an account level, by items and category, based on statistical forecasts as well as ones that include overrides by Marketing and Sales, and then taking corrective actions. He discusses in detail which action will be appropriate under what circumstances.Thevolatilityindemand brought about by globalization, emerging economies, and recessions has highlighted the need to better leverage exceptions and metrics in demand planning. Most firms have adopted high-level performance indicators, such as forecast accuracy, using MAPE at the product group and business unit levels. This level of measurement is useful when communicating overall forecast performance to leadership. However, diagnostic Key Performance Indicators (KPIs) and exception reports by individual are critical to ensure continuous improvement in the demand forecasting process.USING SEGMENTATION TO FOCUS EFFORTSBefore establishing a forecast diagnosis process, the firm must segment items based on volume-variance analysis. Volume segments (ABC) are usually decided based on annual revenueshare.Themost popular approach to variance segmentation is the use of the Coefficient of Variance (COV) formula, which is:CV = Standard Deviation in Period Demand/Average Demand of the PeriodFor example, if the standard deviation for 12 months of demand data is 100 and the average monthly sales are 200, the CV = 0.5. Variance segments (XYZ) are based on CV range. The volume-variance classification is used to decide how demand will be planned for the product. Table 1 gives a sample of Volume-Variance analysis.The results of volume-variance analysis are used in developing the forecasting approach and, therefore, are helpful in establishing exception reports and diagnostic KPIs. Marketing and Sales should focus on those items that impact the business most (A & ? items), and avoid expending time and energy on low volume items. Exception reports and diagnostic metrics should also focus on the items for which Marketing and Sales provide input. Low volume (C) items should be reviewed periodically to decide on how to plan their replenishment.Table 2 gives an example of how to align action with segmentation.Notice for those items with low volume and low to medium variance, Sales input is by exception only. They are not expected to routinely diagnose or offer input on these items. Their focus is on the & ? segments where improvement in forecasting has a high impact on business performance. However, stocking approach and policies are applied to both low volume and high variance in demand.EXCEPTION REPORTS FOR A& ? ITEMSException reports should include individual forecasting performance. As mentioned earlier, sales representatives may be forecasting dozens of SKUs or more, so emphasis must be placed on those items for which forecasting error is the highest. One approach is to develop and communicate a Worst 10 report at the individual level. (See Table 3) Again, the report only includes & ? items for which the demand planning process includes Sales input.Absolute error is used in determining the poorest forecast performance. History is maintained in the system, and the Demand Planner reviews ongoing results to ensure sales representatives are taking action to improve performance. Notice that in this case, four items had significant forecasts but no sales. This will also be highlighted in the forecasting system as this is a standard exception rule.Forecasting performance should also be viewed from a Key Account perspective. (See Table 4) These A customers are candidates for further collaborations, such as joint demand planning to improve forecast accuracy. …" @default.
• W63673053 created "2016-06-24" @default.
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• W63673053 date "2013-07-01" @default.
• W63673053 modified "2023-09-23" @default.
• W63673053 title "Leveraging Exceptions and KPIs to Improve the Demand Forecast" @default.
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