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Five Keys to a Better Supply-Chain Forecast Analysis

  • By Kiron Varma
  • Published: 3/24/2016
forecast1111Forecast analysis is a frequently overlooked feature of the sales and operations planning process, where the generic approach is to validate the variance of the current forecast against the previous forecast or the budgeted figure. Though effective, this might not give an accurate picture of the forecast efficacy.

The following are common methods of analyzing a forecast, predominantly from a supply chain perspective.

1. Convert the physical forecast into a financial forecast. This is probably the best method of reviewing the forecast from an accounting/finance perspective. The financial value of the forecast can be obtained by multiplying the units with the value (selling price) of the unit. A financial value of the forecast would give an indicative value of the inventory (opening and closing), which can then be incorporated into the budget. The financial forecast would also help in correcting the implications of markdowns and discounted sales, thereby giving an accurate picture of the value of goods sold.

2. Monitor the forecast of ‘A’ -class items. ‘A’ -class items are those which contribute to 80 percent of sales. A quick review and analysis of these items will provide an indication of the overall health and trend of the forecast. It is critical that these items have an accurate forecast to avoid loss of sales and shortage of inventory.

3. Separate the impact of markdowns/discounts/promotions. Often while reviewing forecasts, the forecast for a time bucket is compared directly to the next/corresponding time bucket. This would provide inaccurate analysis if any promotions are included in one time bucket. It is always a good practice to compare the absolute figures excluding the promotions to arrive at an accurate comparison of the forecasts.

4. Avoid unplanned promotions during the forecast cycle. I have noticed that many organizations include an unplanned promotion during the forecast cycle. High inventory levels and low sales are some of the reasons why an unplanned promotion is included in the forecast cycle. Though not unavoidable, the logic of including unplanned promotions for fast moving items has to be questioned and rationalized.

5. Identify outliers. This is the simplest and easiest way to analyze a forecast. Outliers can be defined as values that seem to lie outside of the normal ranges. The critical term here is normal range, which has to be determined either as an average value of maximum or minimum or the absolute historical maximum and minimum. One of the best practices in forecasting is to mention the absolute historical maximums and minimums in the report. This is helpful to identify the outliers which lie beyond those limits.

There is never a right or wrong way to analyze the forecast, but the forecast analysis and the forecast in general should be driven by data. The methods for analyzing the forecast must constantly evolve and adapt to meet changes in product lines and organizational structure. It is also important to adopt new techniques for evaluating and analyzing the forecast rather than using a single method.

Kiron Varma is an Agile Business Analyst with Lion, Melbourne, Australia.

A longer version of this article will appear in an upcoming edition of AFP Exchange.
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