Demand planning strikes the balance between having sufficient stock levels to meet demand without having surplus as the end goal. But figuring out the quality of your forecast requires accurate data. In other words, the way in which you test the quality of your forecast is to calculate its forecast accuracy.
What is forecast accuracy?
The deviation, or margin of error, between the actual demand figures and the forecasted result in the demand plan. By finding out the forecast accuracy, you can factor this into your future demand plans and make the relevant adjustments.
Demand planners use the forecast accuracy stats to:
1. Mitigate future risks
Firstly, the quantitative result of calculating the forecast accuracy provides a good estimation of the quality of your past forecasts. This means you can factor in risks in your forecasts and determine how uncertain a forecast is for future business periods. It also means you can proactively adjust your inventories, labour management and increase safety stock levels to cover the uncertain periods in your demand plans.
2. Prioritize questionable forecasts
Secondly, If the margin of forecast accuracy is high, you can identify this and focus particular attention to monitor future demand and stock levels to correct for smaller future deviations.
3. Refine and improve forecast accuracy
Thirdly, if you continue to have high rates of deviation, it’s likely that you need to correct the demand plan techniques, look at new technologies, or assess the quality of the data you’re using as a foundation of your demand plan.
Finally, One of the best ways to ensure this accuracy is leveraging automation technology. The functionality will automatically calculate the forecast errors. But in order to implement an automated approach you’ll need to ensure your data and cross functional collaboration is in order in the system. Also, effective demand planning will assist your business to foresee challenges and react accordingly.
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