Transform the disadvantage of “poor forecasts” into an opportunity to improve them and optimize your entire Supply Chain by following the Diagma view described bellow.
Leveraging the Diagma View of how to use “poor forecasts”
When it comes to continuously improving supply chains for competitive advantage and business success, the goal is to effectively balance the tradeoffs associated with delivering good quality products with good levels of service for the minimum cost. But what if demand forecast issues are infiltrating your planning processes, leading to less than desirable service and cost outputs?
The Diagma view involves transforming any demand forecast method (no matter the quality) into a superior one to optimize planning
In fact, there will always be uncertainty in your forecast. Too many companies fret about this uncertainty without calculating it and fully leveraging it to their advantage. Instead of worrying about the uncertainty in demand, we recommend that companies follow this process:
Plot your current forecast error as a numerical value.
Thinking about forecast error as a percentage of demand can obscure useful patterns and biases present in your current forecasting method. It is better to plot the numerical value of forecast error against to the numerical forecast for each forecast period to spot these patterns quickly.
Determine if your forecast is biased.
Moreover, if 50% of the period forecast errors are negative and 50% are positive, that is a good indicator that your forecast is unbiased. Oftentimes, the simple modeling of a regression line through the forecast error plot will reveal a forecast error bias trending either upwards or downwards with forecast quantity. If you find that your forecast has some bias, you can move on to the next step.
Use Diagma’s method to eliminate the forecast bias.
At Diagma, we use an analytical method to apply a corrective factor to any demand forecast method to eliminate the observed forecast bias.
Leverage the improved forecast to optimize planning.
By using the updated forecasting method as an input to your planning processes, you can better optimize your inventory flows and resource allocations. This allows you to improve service to your customers while reducing costs.
Those who have not analyzed their forecast method to determine whether it is biased are likely facing its consequences in terms of unsatisfactory customer service and wasted resources. But those who follow the Diagma view and account for the uncertainty inherent to the forecast problem can fully leverage that uncertainty to their advantage, ultimately resulting in optimized planning.
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