It Pays to be Data Savvy

Last time we talked about the Internet of Things and the importance of data -- not just today but well into the future. Which brings up an interesting question. What data are you collecting right now to measure and manage your operations?

When we asked OPEX’s Frank Wang about people’s habits, he said “half of the people I talk to have at least a partial understanding on how they are operating. The other half are less sure of their metrics.”

And for Frank, that creates an interesting challenge. He’s a business development analyst at OPEX. That means Frank helps develop the Perfect Pick or Sure Sort system that can improve your operations. The only catch is he needs to know some metrics up front to develop the most suitable system.

So, we asked Frank for his top 10 metrics. And since he’s a thorough guy and not at all superstitious, he gave us a lucky 13 instead. Here they are (in no particular order):
  • Pick rate (units, cases and pallets)
  • Throughput (cubic volume)
  • Number of orders a day
  • Number of lines picked a day
  • Number of SKUs stored
  • Average number of units stored per SKU
  • Number of active/inactive SKUs
  • SKU slotting
  • SKU population change rate
  • Order cycle time
  • Number of emergency orders a day
  • Average pick rate per person per hour
  • Storage space needed for all inventory
That’s quite a list. And just out of curiosity, how many of these can you either recall off the top of your head or uncover with a little research?

By the way, Frank says an important and easily overlooked item in that list is the SKU population change rate, especially in the apparel industry where SKU’s are constantly changing. “That number plays a very large role in deciding how many totes and SKU cells within those totes your system will need,” he says. Well, that didn’t take long to get into the details of designing your system, did it?

“You see,” says Frank, “we have to build a logic behind the system and its design. So not only is the population change rate critical, but the number of active/inactive SKUs is too. We have to know the profile of your A, B, C, and D movers.”

He goes on to say one of the toughest metrics to pin down is number of orders a day. While a warehouse manager may say 3,000, that’s a rough generalization most of the time. What about peak days? What about slow days? The material handling system Frank comes up with has to be able to accommodate both just as well.

“In the end, we have to design the system to minimize bottlenecks regardless of the level of activity on any given day,” says Frank. “It’s critical to minimize bottlenecks in moving inventory to and from the Perfect Pick and Sure Sort. The system might have picked or sorted everything highly efficiently but the impact of that is diminished if those items get bottlenecked and can’t move to the next station. These systems cannot be isolated in any operation,” he adds.

So keep in mind the Lucky 13 list. It pays to be data savvy.

Gary Forger is the former editor of Modern Materials Handling magazine and the Material Handling & Logistics U.S. Roadmap to 2030. 

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