Warehouse Analytics is a fancy buzzword. Yep, I said it. However, Warehouse analytics really means applying data to solve problems within the warehouse. How do you use data to solve problems in the warehouse? Easy – make data-driven decision with the quality tools to improve performance. Quality tools like run and Pareto charts can be applied to analyzing space, motion and errors within the warehouse. Warehouse Engineers and Analytics focuses specifically on increasing warehouse utilization and efficiency.
"What’s your best-selling item & where is it located?”
The response should be SKU 10012 Tennis Ball located in row X- rack 2- shelf 13. If this is the response, problems are easier to solve. However, if the response is “Um… it’s tennis balls, and I’m not sure where we put them last “the data collection process will take some time. Depending on your process and technology, warehouse analytics may vary in time and results. But Warehouse Engineers is willing to work with anyone regardless of where they are at.
“What’s your warehouse capacity and utilization?”
A typically response is about 3,000 pallets (a rounded number to the nearest 100th), and we’re about 80% full. While operating a warehouse, I understand there’s ebbs and flows, on a seasonal, weekly and even daily basis. When all the orders are staged 1st thing in the morning, it appears as if there is no warehouse space, but after lunch it seems product disappeared. Going back to the example of a best-selling item and location, examining the entire warehouse allows you make data-driven decision on the best location to stock items and allocate space. Typically, too much space is allocated to slow moving and dead inventory, and analytics solves this problem.
Data collection is the first step in warehouse analytics. Depending on your procedures and program, a Six Sigma Organization would call it the measure phase, Lean refers to it as Planning, and SPC refers to as chart selection. If no programs are in place, that’s fine too. We can start with a pen and a pad and find out what are the fastest and slowest moving items. After collecting the data, analysis or stratification in categories is next. Typically, data is broken into 3 categories A, B, and C called a Pareto Chart. Pareto Charts are built on the theory 80% of activity come from 20% of inventory. Trust me, the results are never this clean, but stratifying the data creates a good starting point to improve utilization and motion. Heat Maps are another tool that can be applied in warehouse analytics. A heat map visualizes activity in the warehouse where “A” Items red or “hot.”
After collecting and analyzing data with insightful tools, action is the next step. In Six Sigma this is the improve phase and others may call it an action plan, regardless of names, a change is made based on the data. A change could be to live load “A” items or stock “C” items in the back corner of the warehouse. A WMS may or not solve this problem for you. I know most WMS’ slotting strategy is based on a FIFO rotation so manual changes may be required. In my experience the changing the process or procedure is the fun part. There’s different tools and techniques to work with associates and managers to improve the process, and typically the boring, hard part is the data collection. No worries – you can hire Warehouse Engineers for the boring, hard tasks.