![]() So long as conditions in his market did not change, predicting future staffing needs was straightforward. His business had also been growing at a fairly steady rate. His historical staffing levels were appropriate because he had hired staff as he needed them, albeit somewhat after his backlog reached a crisis. Using a statistical modeling approach, I found that his historical staffing was highly correlated to just one factor, the number of units of one of the products he produced in the prior year. A few avoided giving the administrative assistant any forecasts at all, so she just used numbers from the previous year. Others estimated fewer sales so that they would have a better chance of making whatever goal might be given to them. Some of the sales force estimated more sales than they expected to try to impress the boss. Moreover, it took his administrative assistant several weeks each year to collect the projected sales data to input into the model. Even after tinkering with the manufacturing times and correcting for employee leave, administrative functions, and inefficiency, the model still wasn’t very accurate. It was a classic bottom-up modeling approach. ![]() He reasoned that adding up the time it took to produce a product multiplied by the number of expected orders would give him the number of man hours he would need. Then he had his sales force estimate the number of orders they expected the following year. He collected data on how many of each type of product he had produced over the past five years and from that data had his managers estimate how long it took to make each product and complete the most common customizations. A few years earlier, he had gone to great effort and expense to develop a model to predict his man-power needs. His company produced three lines of products, most of which were customized for individual customers. I had a client, a very skilled engineer, who wanted a model to predict how many workers he would need to hire during the year. ![]() You have to put your model in a form that will be palatable to users. But just as mountain climbers have to descend, model builders have to deploy. It’s what gives you that euphoric feeling of accomplishment when you’re finished. It’s what you spend so much time planning for. Model building is like climbing a mountain.
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