Measuring Forecast Error – Constrained or Unconstrained Forecast?

Is it better to correct the actual sales for supply constraints and come up with a version of the actual demand that is unconstrained?

Measurement is an ex-post event that should not affect the actual forecasting process. If the Sales force is encouraged to think about a constrained forecast, the organization will lose visibility to the true unconstrained demand.

One option will be to use a disciplined process to measure true demand every month and evaluat the unconstrained forecast with this version of true demand.

What To Measure or Forecast Accuracy – SKU/DC, SKU/National, SKU/Plant?

Although most demand planners and COE professionals understand the mechanics of these measures, there is some confusion on what to measure and why.
Measurement depends on what you are trying to drive – what you are using the forecast for? So level of aggregations matter as well. We explain some examples on what circumstances drive which measures.

Are You Still Using Excel For Forecasting And Planning?

Some of the big names who have used our services and expertise include Honeywell, Pepsi Foods, Brown-Forman, Labatt, Yaskawa, Coleman, McCain Foods, Lindt and many other small and medium size companies.

We can be reached at www.demandplanning.net. You can also contact our Business Development Manager at hatimr@demandplanning.net . We would be glad to have an initial call for a short diagnostic of the current processes and pain points.

Forecast Error Benchmarking Across Various Industry – Survey Results

we started conducting the survey across supply chain and demand planning professionals from various industries. This survey was meant to compile information about their pain points, forecast error metrics they use, industry they work for, and who owns the demand planning function. We are publishing the first installment of the results from this survey in this newsletter.

As expected one of the metrics used by 52% of the respondents is WMAPE or volume weighted MAPE, calculated as Sum of Absolute errors divided by sum of actual demand.

Forecast Reconciliation and Proportional Forecasting – My e-book On Amazon.com

First e-book on forecast reconciliation and proportional forecasting released through Amazon.com.