Tracking, measuring, and analyzing metrics and key performance indicators (KPIs) are crucial to improving warehouse operations. However, not all metrics and KPIs matter. Every business has its own circumstances and faces unique challenges. Setting relevant and meaningful KPIs mean having a clear line of sight to their purpose in operations, value to the business, and benefit to customers.
We compiled a list of essential KPIs for warehouse operations that should be tracked and measured. It’s not a definitive list, but it serves as a springboard that companies that adapt for their warehouse. Our guide covers metrics for productivity, inventory, and processes or workflows. Analytics, which builds on advanced techniques and technologies, can be the much-needed push for breathing deeply and more easily.
Many conventional metrics that measure productivity and efficiency involve labor, space, and equipment, and their entailing costs. Metrics for inventory not only gives a glimpse into the movement of goods — they also reveal, for example, insights on the supply and demand of products and relationships with vendors and suppliers:
| Productivity and Costs | Inventory |
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There’s a host of other KPIs that reveal the performance of the warehouse’s operations. They are typically categorized into the following:
Internal: Processes and workflows that are unique to the warehouse and are closely aligned with the business’s strategic goals
Inbound: Processes and workflows for the movement of resources from an external channel to the warehouse, including the sourcing, purchase, and acquisition of materials or products, and their delivery, reception, and storage
Outbound: Processes and workflows related to the shipment of materials or products from the warehouse to a designated destination
The inherent nature and life cycle of warehouse operations mean these KPIs will inevitably cross paths and sometimes overlap, so it’s up to warehouse manager to disperse gray areas:
| Internal | Inbound | Outbound |
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Analytics gives warehouse managers and decision-makers foresight into what is happening, what will most likely happen, and how they can adapt to it. When needed, it builds on operations research and advanced techniques like AI and machine learning to improve or automate business processes and extend the life and value of assets in the supply chain. It’s no surprise that 91% of supply chain leaders are actively investing on these capabilities.
A more tangible example is a warehouse KPI dashboard. It pulls datasets from various sources and converts them into visuals that can be readily accessed and interpreted. Warehouse KPI dashboards can be built depending on business need: forecasting demand and generating predictions, tracking activities within the warehouse, defining critical success factors, or everything in between. However, there are technical requirements for creating an actionable dashboard — from the right data storage and management technologies to back-end architectures that process data. Even complementing it with advanced analytics has its own prerequisites.
Download our guide to get a closer look at these essential KPIs, their industry benchmarks, how to calculate them, and how analytics can help operationalize them.