The past 30 years has seen some dramatic changes in the ways we consumers purchase everything from books to batteries, cameras to clothing and TV’s to trampolines. The changes are not only in the products themselves, but in the channels of delivery. For example, when I was growing up in the 70’s and 80’s the only chain businesses that I can remember were Sears and McDonald’s. Even then, you had to live in a fairly good sized town to have either of these stores. Today, any town of any size in America has not only a McDonald’s, but a Wal-Mart, Home Depot, Starbucks, Olive Garden, etc., etc. Yes, the chain stores have certainly replaced the mom and pop shops that were so prevalent just a generation ago. This change has led to an explosion in the number and size of distribution centers around the country and the folks running these DC’s are constantly looking for ways to get more product through their systems in less time and for lower cost.
I recently had the chance to work with one of our customers who was modeling a proposed layout change to their DC floor plan. The change was already being piloted in a particular DC, and a model was being developed to test the merits of the new layout under various product demand and mix scenarios. The early results from the real-life pilot were promising, showing that relieving forklift congestion could increase the throughput of the system, even if the forklifts had to travel longer distances to avoid congestion. As such, a change was about to be implemented in each of this customer’s DC’s across the US, at the cost of over $2 million.
My contact had the opportunity to use simulation to determine the expected improvement of the new floor layout in other DC’s throughout their network. To his surprise, the model predicted exactly the opposite results! Not only would the new layout actually reduce throughput, it would increase the operating cost of the system by requiring more forklifts and, hence, more drivers to maintain the previous level of productivity. How could this be since the real-life pilot was showing moderate (but not stellar) improvements? Enter something called the Hawthorne effect…
Stated simply, the Hawthorne effect is a temporary improvement in productivity that results when management pays greater attention to an established process. In other words, what gets measured gets done better and faster than it was before. In this case, the fact that the pilot area was the focus of management attention at this DC meant that the workers were unconsciously improving their performance. The simulation, on the other hand, was completely unbiased and used the same assumptions regarding forklift travel speeds, put and pick times, and operator work habits across both scenarios.
In the end, the existing system proved to be more efficient because the frequency and duration of forklift congestion events was less detrimental than the additional travel distance in the new layout that was required to eliminate those events.
In summary, whenever human operations are a significant part of a production process, consideration must be given to the methods in which physical simulations, i.e. pilot tests are performed on the floor. Otherwise, the Hawthorne effect just may result in a wrong (and costly) change to procedures.