In an economy where warehouses have become order fulfillment centers (OFCs) for retailers pushing out thousands of individual orders, there have been a number of media stories examining the difficult working conditions at these facilities.
New research from the Wisconsin School of Business suggests that companies like Amazon, Zappos, and other e-commerce companies looking to control costs and improve productivity, should be doing more to reduce employee turnover and keep experienced workers on the job. The study by Robert Batt, assistant professor of operations and information management at the Wisconsin School of Business and Santiago Gallino of Dartmouth College, found that having experienced “pick-workers,” employees tasked with rounding up individual items for shipment from among thousands of storage bins in an OFC, significantly reduces pick time and can improve productivity.
“As online retailing continues to grow, customers will come to expect a seamless shopping experience and that means increased pressure on retailers to make order fulfillment a strategic part of their business,” says Batt. “Too often, companies have missed the boat by using distance minimization algorithms to plan pick-worker routes when they should be looking at time minimization tactics that take into account bin density and worker experience.”
Batt adds, “Newer workers have such a hard time searching through crowded bins with many different items that it’s better to have them walk more than twice as far to get to a low-density bin. Our work provides a new way to look at how to improve operations and best manage these order fulfillment centers.”
Retailers selling widely varying product types have OFCs that use what is called “chaotic storage,” a system where inventory is not stored together with like items in predefined locations but is instead split up and assigned to any space that is available. In the OFC reviewed in the study, pick-workers push a laptop computer on a wheeled cart that provides the item number, a photograph, and the bin number of the items to picked out and shipped to a customer. Since bins can contain many different items, a key part of the process is the amount of time a picker takes to find the required item in a crowded bin.
The research found that mean pick time drops by 4.2% with each doubling of a pick-worker’s experience level and that time improvement is the result of the reduced bin-searching time as opposed to faster travel time between bins. How does experience come into play? Over time, pick-workers:
- get better at looking for visual clues (such as color and pattern);
- become more familiar with the descriptive text used to identify items; and
- learn where item ID tags are commonly placed on different kinds of items.
Overall, companies could achieve a 5% increase in productivity by considering the experience of pick-workers and bin density when developing pick routes and assigning tasks. Because experienced pickers are significantly more productive than inexperienced ones, companies might want to consider incentives to reward experienced employees, while considering improvements to working conditions that will increase worker retention.
“Managers may want to consider optimally assigning more experienced pick-workers to routes with higher bin density while allowing inexperienced workers to learn and gain experience on shorter, lower density pick assignments,” says Batt. “Creating financial incentives, such as pay raises and better working conditions, can go a long way to reducing employee turnover and retaining employees who are going to be more productive and help the company lower their operational costs.”
The researchers reviewed nine months of data from a women’s apparel retailer in California, with a 100,000 square foot OFC with an inventory of 180,000 items and that was responsible for shipping out some 20,000 items to customers each day.
The paper, “Finding a Needle in a Haystack: The Effects of Searching and Learning in Pick-Worker Performance” is forthcoming in Management Science.
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