"At the most basic instance, a company can say it's going to measure the number of cases that are picked," says David Erickson, vice president, product development for RedPrairie, Waukesha, WI. "That's going to set an expectation for the number of cases that it wants picked and it's going to measure against that."
However, many companies need to account for the fact that a case isn't always a case, especially in a DC that may be shipping a variety of products from thumbtacks, all the way up to table saws. Companies who operate under the "picking is picking" or "putting-away is putting away" school of thought risk creating false statistical information, not to mention employees who become disgruntled due to unrealistic expectations of them.
"It's not going to be the same if you're unloading paper towels as opposed to cans of green beans, there's a lot more effort in the cans," agrees Tompkins' Brockmann.
According to the experts, companies must strive for a more "granular" data capture, a more adept description of the actual work being done, each individual move and action. "What exactly are my workers putting away and how long should that particular item take?"
In terms of receiving metrics, the same applies. "If you're looking at how many cases you're receiving per man hour, it really depends on what shows up at the door," says Brockmann. "If it's a straight load, then everything's hunky dory and your cases per man hour is going to be extremely high, but if the next week, you're getting a lot of imports, everything's floor loaded or something, the productivity is going to drop dramatically."
Brockmann says that if his clients look at only one particular metric, it becomes misleading and confusing. "People need to look at a balance of metrics." A true labor management system will take into consideration the fact that a worker may do the same task twenty times and each time the task may have slight variables. The LMS should have the different frequencies programmed into it and calculate twenty different expected times.
Time metrics utilized in the creation of standards also need to be realistic. The best way for this to happen is for managers to perform actual time studies.
"That's where you're going out there and timing an operation," says Brockmann. He notes that an LMS is good at calculating how long it takes a worker to travel from one point to the next, but there are some elements the LMS isn't going to be able to track.
"You don't want to not account for an operator that has to get off the lift truck and go adjust the cases on a pallet, so what you have to do is go out there and do some labor engineering standards. Make some frequency checks. It may be 10 percent of the time that he has to get off the truck and do some adjustments. You have to add all the frequencies in there."
With accurate information, companies will be able to set exacting time goals-goals which they will be able to defend to any detractors because they've accurately modeled the nuances of the job.
Model The Activities
Another important thing that managers sometimes fail to remember when they are modeling a job for their LMS to track is not only how fast they want the job done, but how they need it to be performed-in other words, what other metrics do they want measured while an employee is picking?
"Model the job to ensure that such things as efficiency, accuracy, quality and safety also go into the model," notes RedPrairie's Erickson. "In recent years we've added capabilities in our system to measure quality, to measure safety, to ensure proper training of employees and proper supervisor observation-all those dimensions of the preferred method-to bring them into a holistic picture and bring a reporting structure to bear that says: ‘I'm going to measure you on every facet we're trying to achieve with these engineering efforts.'"
Erickson's colleague at RedPrairie, Jim Le Tart, director of marketing, cites an example of how modeling accuracy metrics into a large food company's LMS led to a dramatic efficiency change for the company.
"We were looking at the work flow in the facility and they realized they had a lot of narrow, dead-end aisles that forklift drivers would go down. Other pickers would have to wait at the end of the aisles to do their picks, until the truck would back out. It was very inefficient," says Le Tart.