Jul 27 2016
How Does This All Play Out?
It is a seemingly simple question, but one that is not asked as often as it should be. It challenges managers to consider the responses of other stakeholders and think beyond immediate consequences. It checks their “bias for action,” and makes them take a pause to think farther than one move ahead.
If you outsource an item, for example, will the new supplier eventually morph into a competitor? What know-how might you lose? How will it affect employee morale? Are you putting your quality reputation at risk? The question is an invitation to work through multiple scenarios of responses by your suppliers, your work force, and your customers, reaching into the future.
Jul 16 2021
Sales Forecasts – Part 1. Evaluation
When sizing a new factory or production line, or when setting work hours for the next three months, most manufacturers have no choice but to rely on sales forecasts as a basis for decisions.
But how far can you trust sales forecasts? You use a training set of data to fit a particular model and a testing set of actual data observed over a time horizon of interest following the end of the training set period. The training set may, for example, cover 5 years of data about product sales up to June 30, 2021, and the testing set the actual sales in July, 2021.
The forecasters’ first concern is to establish how well a method works on the testing set so that the decision makers can rely on it for the future. For this, they need metrics that reflect end results and that end-users of forecasts can understand. You cannot assume that they are up to speed or interested in forecasting technology.
Forecasters also need to compare the performance of different algorithms and to monitor the progress of an algorithm as it “learns,” and only they need to understand the metrics they use for this purpose.
By Michel Baudin • Tools • 11 • Tags: Kanban, Production planning, Sales forecast