Picking a Winner
A frustrated beer distributor turns an Internet search for picking software into a magical find.
Joe Puglia, director of operations at Schenck Company, an Orlando-based beer distributor, was frustrated because he couldn’t find a solution to his picking problem.
“I had checked into just about every potential solution, trying to find a picking system that could do exactly what we wanted,” he says.
“One day, on a whim, I tried a Google search on ‘pallet building’ and ‘case picking,’ says Puglia.
Amazingly, through that simple Google search Puglia was able to find what has become not only a solution to his picking problems, but a productivity booster as well.
The search led Puglia to Warehouse Optimization, Nashville, Tenn., the developer of AutoPalletP3. The software system creates the most efficient pick route and configuration for a given situation. The rest, as they say, is history.
Schenck’s distribution operations are centered in a new, 300,000-square-foot DC that houses about 350 SKUs. The 100-plus employees distribute Miller, Coors, and specialty brews to bars, restaurants, and convenience stores throughout central Florida.
Like many distribution centers, Schenck’s operations involve a lot of picking—an estimated 40 percent of its total labor. That volume is largely due to specific picking requirements, such as special pallet sizes or a particular order of layering on the pallet.
These special requirements are made more complicated by the fact that pickers are often the newest employees in a DC and require a good deal of training. Schenck managers found themselves spending a lot of time training new employees on all the ins and outs of picking at the facility.
Weighing Down Operations
Unfortunately, Schenck found that its picking system—or lack thereof—was weighing down operations. The company depended on a manual picking approach, which led to significant slowdowns.
“Our route accounting software would, for example, send an order of 200 SKUs,” explains Puglia. “The pickers had to look at the order, figure out how many pallets they would need, and how to build them.”
Pickers would spend 15 to 20 minutes simply figuring out how to pick every order. After that, they invested more time to actually pick the orders. Then pickers often had to retrace their steps to fill orders. It all added up to far too much time spent on picking operations.
“We needed to find a system that could break the orders down for the pickers and tell them exactly the order in which to pick,” says Puglia. “We wanted the picking order to flow so that pickers didn’t have to backtrack and waste their time.”
Schenck wanted to cut down on the “think time” required of pickers and to smooth out the work flow. When Puglia’s Google search directed him to Warehouse Optimization’s AutoPalletP3, he knew he was on to something.
“I was shocked to see that there was a product that could do exactly what we needed it to do,” he says.
Tom Moore, present of Warehouse Optimization, was equally shocked to hear from Puglia. “We thought our market was Fortune 50 companies,” he says. “So when Joe Puglia approached us, we were floored.”
Schenck broke new territory for Warehouse Optimization. “The company was unique both in size and scope,” Moore says. “We didn’t understand its business at all.”
But Schenck did share something in common with the large consumer product goods companies that made up Warehouse Optimization’s customer base—the need for a palletizing software system to make operations run efficiently. And because the scope of the Schenck project was smaller than what Warehouse Optimization is used to, Moore found that the implementation process was easier.
“Schenck’s systems are less complex than the larger companies we work with, so the integration process was much simpler,” he says. Schenck’s systems team also was a great partner, supplying all the information Warehouse Optimization needed to complete the implementation.
“We had to understand and duplicate Schenck’s rules,” Moore says. “Once we understood this, we just configured the software to generate the output they needed.”
While the implementation process was relatively straightforward, trade-offs had to be made in order to successfully get up and running, as in all software implementations, Moore says.
In all, the implementation required just one weekend. “The challenge was inputting our hundreds of rules so that the pallets would get set up exactly as we needed,” Puglia explains.
Mimicking Best Practices
The AutoPalletP3 system works by mimicking what the best picker would do. For each order, the system considers the rules it must follow, then designs the pallet picking order to the company’s preferences—stronger cases are placed on the bottom of the pallet, for example. In addition, each picker’s travel distance is kept to a minimum.
Warehouse Optimization originally designed AutoPalletP3 for Procter & Gamble in 1992.
“P&G had analyzed its case pickers and determined that 20 percent of their time was spent thinking about how to pack their pallets,” says Moore. “The company came up with the idea of this software, and we designed the code for it.” Only recently did P&G authorize Warehouse Optimization to market the software to other companies. Now in place at Schenck, the software receives orders from the company’s route accounting system. AutoPalletP3 goes through Schenck’s order list and determines the best layer order for the pallets to be picked. It prints a pick list for the pickers to follow.
“The software tells the pickers exactly what order to pick in so they don’t have to think about what they are picking,” says Puglia. “Because the software makes sure the pallet is layered correctly, we also know the orders are correct.”
Orders are received at Schenck each day. At night, the trucks are loaded according to the AutoPalletP3-designed list, then they roll each morning.
What started out as a seemingly futile search for a pallet building solution has turned into a “magical find” for Schenck, says Puglia. Since implementing AutoPalletP3, Schenck’s productivity has soared.
“Prior to installing the software, we averaged about 120 cases per person per hour,” Puglia says.”Now we average 180 to 190 cases per hour.”
Error rates also have improved. “We’re working much more efficiently and handling more volume with fewer people,” says Puglia.
As is often the case with change, Schenck employees were skeptical of the new software at first.
“Pickers have their own way of doing things, and they didn’t like the idea of changing that,” Puglia explains. “But now each person can pick so quickly that even the veterans like it.”
So do new employees. It used to take about one month for a typical new picker to achieve handling 150 cases per hour. Now, says Puglia, new pickers can get to that rate within about two weeks.
And just as AutoPalletP3 was a find for Schenck, the beer distributor has opened new markets for Warehouse Optimization.
“Joe Puglia is a visionary in his industry. He saw how this software could work for him,” says Moore. “If the system makes sense for Schenck, then it might make sense for others.”