Best Practices for Tracking Warehouse KPIs

Best practices for tracking warehouse KPIs
Best practices for tracking warehouse KPIs

A warehouse manager plays a crucial and highly demanding role in the supply chain. Their work has many moving parts that involve people, machineries, and workflows, with the ultimate goal of ensuring the safe, accurate, on-time, and efficient delivery of products and services to the customer.

Tracking key performance indicators (KPIs) enables these warehouse managers to meet this goal by showing how the entire operations is running and revealing areas for improvement. There are essential metrics and KPIs for managing warehouse operations, but measuring and monitoring all of these could lead to information overload, not to mention the uncertainty of knowing where and how to start tracking them. There are some ways and best practices to make it more doable and achievable — with the right analytics tools and technologies.


Choosing the right KPIs for warehouse operations

A more focused approach to choosing KPIs helps avoid overwhelming managers and decision-makers. These steps can aid in finding suitable KPIs that paint a more vivid picture of a warehouse’s operations:

  1. Identify goals. Start by asking what needs to be achieved, such as speeding up operations or minimizing spending. This narrows down options to the most relevant KPIs.

  2. Choose relevant and implementable KPIs. Tracking only a few but highly targeted KPIs can be enough to demonstrate warehouse performance while keeping decision-makers from drowning in data.

  3. Build a warehouse KPI dashboard. Warehouse managers can then feed these chosen KPIs into a business intelligence (BI) dashboard for visualization and automated analysis.

  4. Review and calibrate. No process or dashboard is perfect. Regularly reviewing the data reveals areas for improvement in both operations and the team’s approach to gathering data.

Here, we focus on five key indicators: inbound, outbound, putaway, storage, and picking and packing. These are often what give managers a clearer picture of the warehouse’s end-to-end performance, from the moment the materials or products arrive until their delivery to their next destination.


Inbound KPIs: Focusing on speed, accuracy, costs

When measuring the performance of delivering products from an external channel to the warehouse, speed, accuracy, cost, and efficiency are crucial. They have a domino effect on all succeeding processes, from putaway all the way to delivery.

  • Inbound performance: This shows how many lines or items a warehouse can process during a shift or in a period. Poor inbound performance might suggest issues like missing barcodes or lack of workforce during peak periods like holidays.

  • Loading gate utilization: This measures the percentage of dock doors at the warehouse being used. A higher percentage would suggest that many orders are arriving at the warehouse. Data here can help in resource planning, especially during a warehouse’s busiest hours.

  • Receiving order accuracy: This KPI shows received orders that don’t match the purchase orders (POs). Accuracy below the WERC’s 99.3% median accuracy benchmark might compel managers to implement more stringent quality control, automate certain processes to minimize human error, and train personnel to follow best practices.

  • Operation time: Long operation times (i.e., the time it takes to process an order) might point to bottlenecks, such as when there are too many inbound orders than the available workforce can handle.

  • Cost per line: This refers to all the costs a warehouse incurs when processing one line. Labor costs are the primary driver of this KPI, so managers seeking to lower their cost per line can consider automating processes where applicable.


Outbound KPIs: Emphasizing accuracy, availability

When moving products from the warehouse to an external destination, it’s vital to track delivery speed, stock availability, and order fulfillment accuracy. These ensure complete, on-time, in-full, and error-free delivery of customers’ orders, which minimize the possibility of returns and encourage repeat business.

  • Order time: Long order times— the time it takes from an order’s placement to receipt — might suggest inefficiencies in one or several processes. This could require checking other KPIs to see exactly where these inefficiencies lie. For example, a long operation time during the inbound process and poor putaway performance will both impact order time.

  • Out of stock orders: An increase in demand for a certain item may empty a warehouse’s stock sooner than expected. This KPI reveals whether the increase is a one-time event (suggesting that the item’s popularity waned as quickly as it became in demand), seasonal, or consistent. Examples include increased demand for Halloween decorations in the weeks leading up to October and demand for medical masks during the pandemic. This will help the team plan and ensure the availability of stocks in the future.

  • Order score: This KPI measures the number of items that have been shipped out and delivered accurately to their destination. A low score might suggest the need for better quality control, such as properly scanning barcodes and attaching labels to packages, and personnel training, like standardizing practices in putaway and picking and packing.


Putaway KPIs: Optimizing efficiencies and processes

Measuring putaway performance entails tracking KPIs that convey the efficiency, speed, cost, and accuracy of moving products to storage and adding them to the inventory. These reveal processes that require optimization, whether through automation, additional workforce or equipment, or improved quality control.

  • Putaway performance: As this is a labor-intensive process, poor putaway performance could suggest the need for automation that will help personnel process more lines.

  • Putaway operation time: Slowdowns in processing orders could point to bottlenecks (i.e., not enough staff to process orders) or inefficient processes that could benefit from automation.

  • Putaway cost per line: Manual labor is typically costly. If the putaway costs are too high, consider automating processes where applicable.

  • Equipment usage: For example, not having enough forklifts and carts to processes orders or constantly having equipment breakdowns and malfunctions will slow down the putaway process and could have a knock-on effect on subsequent processes.

  • Putaway score: This specifies the accuracy of receiving and storing items and adding them to the inventory. A poor score might indicate a need for improving the putaway process, such as investing in training or using new tools that will minimize errors.


Storage KPIs: Utilizing space effectively

Storage is critical to any warehouse since items spend most of their time here until they’re ready for delivery. This means ensuring that storage space is sufficient and utilized effectively as well as understanding the cost of maintaining it. These KPIs also help validate the need, if there’s any, to expand storage or speed up the processing of items.

  • Storage productivity: This is an inventory’s volume per pallet space and shows how the warehouse maximizes space. Warehouses experiencing low productivity might consider using automated storage and retrieval systems to complement manual pickers.

  • Utilization: This shows how much storage space is free. High utilization rates could mean that there isn’t enough storage available, like during surges in orders. It could also suggest the need for more efficient putaway and picking and packing processes to get items out of storage as quickly as possible.

  • Inventory costs: This includes labor costs, the cost of the inventory, and damage to inventory. High costs could suggest inefficiencies in the putaway process, which better training or automation could remedy. It could also mean that the product is spending too much time in storage, which could then indicate weak demand.

  • Turnover: A high turnover could suggest strong demand for the product, so additional orders can be made in advance. A low turnover could point to weak demand or overstocking.

  • Stock levels: This indicates if there is enough or excess stock of a product by comparing it with sales figures. In case of overstocking, consider ordering fewer items to minimize inventory costs.


Picking and packing KPIs: Improving operational productivity

Some metrics can overlap between picking, packing, and putting away materials, components, and goods. Looking more closely at picking and packing performance helps ensure the speedy, accurate, and cost-effective delivery of items.

  • Picking and packing performance: Poor performance will affect timely delivery and indicates a need to streamline or automate the process.

  • Picking and packing operation time: Taking too long to process a picking order could suggest inefficiencies and bottlenecks, such as pickers who can’t locate items quickly due to a disorganized storage process or an inadequate workforce.

  • Cost per line: This includes all value-added processes. Labor costs can drive this metric upwards, so consider partial or complete automation.

  • Equipment usage: Having ample equipment will speed up the process and provide a buffer in case of breakdowns or failures in machineries.

  • Picking and packing score: This demonstrates accuracy in picking and packing orders. A low score could indicate the need for improvements in areas such as quality control and personnel training. Consider implementing more stringent predelivery checks and standardizing best practices to the workforce.


Tracking warehouse KPIs more effectively with analytics

Today’s businesses face a more complex landscape that requires them to constantly adapt to the market’s ever-changing needs and events that disrupt the global supply chain. Analytics empowers warehouse managers to respond to these challenges with speed and confidence by making it simple to aggregate, filter, and analyze their warehouse data.

A warehouse KPI dashboard, for example, visualizes data to help decision-makers quickly make sense of the numbers so they can respond immediately to demand, allocate resources where necessary, and forecast trends. However, building a dashboard that is tailor-fit to the unique needs of a warehouse goes beyond just the visuals. Other considerations also include data storage and management technologies and back-end architectures that process data as well as business and technical specialists who can expertly navigate them.

Lingaro Group’s supply chain analytics practice provides data engineering and advanced analytics services for logistics, warehousing, and transportation that enable enterprises to drive cost efficiencies and enhance service levels and operational efficiency. Lingaro helps organizations use data to gain end-to-end visibility in their supply chain that, in turn, enables them to accurately forecast demand, enhance resilience and responsiveness, maximize inventories, optimize resource allocation, streamline routes, minimize waste, and generate savings.

Best Practices for Tracking Warehouse KPIs

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