This video from Synoptic Panel’s website shows a small-scale example of visualizing a warehouse.
The Synoptic Panel custom application in Power BI presents a useful alternative. With thousands of SKU numbers and locations, this can be extremely cumbersome. Historically, this has involved linking multiple inventory- and velocity- related data pulls into spreadsheets, and then digging through this data via formulas to understand if a product is slotted correctly according to historical velocity. Once a warehouse inventory manager decides on a slotting strategy and implements it, the difficult next task is measuring the effectiveness of the implemented strategy. For large DCs, the variety and complexity of inputs and outputs for slotting algorithms can be vast. One of the key strategies to accomplish this is slotting, the process of optimizing the layout of inventory in a DC based on factors like size, format, storage medium, seasonal velocity, and affinity with other products.
The modern-day warehouse management team is responsible for keeping these buildings running smoothly and to do this, they must sift through mountains of generated data to minimize handling of inventory while maximizing throughput. DCs vary in complexity, but range in size to upwards of 1 million square feet, with thousands of distinct products inside, and miles of conveyor belts. In between, the product is likely stored in one or many distribution centers (DCs). Each and every day, billions of dollars of inventory move around the world and into the hands of consumers. With the holiday shopping season upon us and a global supply chain crunch dominating the headlines, it’s worth reflecting on the miracle of logistics that occurs between a product’s manufacture and its arrival to final destination.
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