Last month I attended JDA Focus, the company’s annual user conference. My favorite presentation from the event was that by Tony Simmons, an Operations Analyst from Genco. The presentation discussed Genco’s application of JDA Warehouse Labor Management (JDA WLM) to manage and ultimately reengineer its business processes. I found it to be a great example of how perceptive individuals, when digging into a project, can yield insights and performance improvements beyond the original intent. This warehouse operations case would also be a good example of “real options” in the finance world.
Genco manages a number of warehouses for a large US-based food producer. A few years ago, Genco ran a time study at a greenfield distribution center. The workers were not informed of the study taking place, assumedly to arrive at unbiased results. Subsequently, management informed the workers of the ongoing employee performance and reporting process. Thereafter, performance improved by 60 percent, likely due to the presence of the labor tracking and management. This alone is a notable efficiency improvement. However, the following results are what I found most interesting.
After a short time, performance improvements flat lined. Genco then decided to group data by operation (as opposed to grouping by worker) in JDA WLM to analyze the efficiency of the various tasks and jobs, including indirect labor time. This data was coupled with warehouse layout parameters such as travel distances. The analysis uncovered that workers were “performing inefficient work, efficiently.” Specifically, workers were traveling too far from pick-up to deposit, and deposit to next pick-up. They were also traveling excessively between areas. This information, along with further analysis regarding forklift mobility, led to a new travel sequence and warehouse layout that reduced pick-up to deposit travel times and downtime. To reduce time from deposit to the next pick-up (deadhead flow), Genco decreased the size of work zones within the facilities and prioritized job sequencing to those in the same work zone. This process change also decreased congestion and waiting during peak hours. Finally, Genco adjusted its product placement by placing greater emphasis on shipping tasks and more closely storing items that often ship together. This adjustment reduced travel for picking and put-away and enabled workers to turn staging lanes more quickly.
Tony wrapped up his presentation by categorizing the obtained insights into those expected at the project inception – employee accountability and performance visibility; and those that were discovered during the process –warehouse layout, operator flow, and product placement improvement options. However, I see the discoveries as an example of improvement options that come to light from a better understanding of one’s business processes and a motivation to improve.