Maybe you’ve heard that KPIs (key performance indicators) are the answer to your problems, but you just don’t know how to properly implement them. That’s understandable. Warehouse management challenges can be overwhelming.
But the truth is that supply chain executives and managers can simplify the process by tracking warehouse management KPIs and improving with those guideposts.
You’re about to discover how to improve efficiency and productivity at your warehouse with a proven strategy. No guessing. No trial and error. Just a method that gets results.
Read on to get the top warehouse management KPIs…
The role of data logging
You have to have data available in order to use KPIs. And that means having methods to collect the data. Data logging is one method that works well for supply chains. Here’s an example of how it works.
Damaged goods are a real issue when it comes to warehouse management. You’ve probably seen items damaged in transit many times. But data logging is a strategy that can actually help to prevent the damage from happening in the first place.
A data logger is software that collects and records data in a particular environment--in this case, in the freight vehicle.
All you need to start collecting this data is a device with a sensor to track the environmental conditions. Then you can see, for instance, if factors of the environment (such as temperature or movement) are outside safe parameters for the items being carried.
Of course, there are plenty of different ways to log data because all that means is to take a measurement and record it. But there are types of data (and ways of collecting it) that are more efficient than others.
For instance, you could have drivers manually check the temperature of freight compartments in their vehicles for temperature-sensitive items and write down their readings. But that takes a lot more time than digital readings, and things written on paper are not as easily shared between the individuals who need access to the data.
That’s an extreme example, but it shows you how the method you choose can make a real difference in your results when logging data.
How do you know which data you should be logging? The data collected should be used to verify your processes or correct issues. If it can’t do that, then it’s not useful data.
Top data to track for warehouse management
And that leads us to the KPIs that you should be collecting and monitoring:
How is the accuracy and timeliness of your freight deliveries? This may not be something you have immediate control over, but it’s definitely something you want to be monitoring. It helps you to determine strategies for working with vendors, as well as strengthening your relationships with vendors and the best carriers.
Backorder rate is one of the most important measurements to take for the success of your business. If you’ve got a lot of backorders, then customers want items that are not in stock. Your backorder KPI should not be consistently high, and if it is, then changes need to be made to your inventory planning.
Backorder rate equals the number of orders unfulfilled at the time of purchase divided by the total number of orders.
What is happening with incoming freight is definitely something you want to track. That means collecting data on the volume of items put away per employee per hour. Having this information can help you to plan large freight deliveries and track inefficiencies in employee methods. You’ll also be able to see if employees are improving over time.
These are fairly easy to monitor. Storage KPIs include:
- Average inventory value.
- Inventory turnover, which is the total goods sold divided by the average inventory value in a given period.
- Carrying cost of inventory, which is the amount of time a product stays in the warehouse times the average inventory value.
Inventory accuracy can also be calculated with a number. You take the count of items in the database inventory and divide it by the count of the physical inventory (yes, you do have to take the physical count manually).
You want to get a result of 1 when you take this measurement. If the number is not 1, then it indicates either an inaccuracy in the database or the manual counting, or some other issue, such as lost inventory.
These are measurements for items exiting the warehouse. They include the average number of items picked per employee, the total value of all the picks in a given timeframe, and the average value of the total number of picks.
In addition to tracking the items leaving shelves, you’ll want to track data about packing the items. This includes labor costs, the cost of packaging, and order cycle times.
These numbers are not the same as picking and packing KPIs. Instead, they are the total number of items shipped divided by the projected number of items to be shipped. Ideally, the number should equal 1.
If you are shipping fewer items than projected, then you have a deficit. And this may indicate inefficiencies in your warehouse. By tracking how this number changes, you can see whether the productivity level of your warehouse operations are improving or getting worse.
Reverse logistics KPIs
These are the numbers regarding returned items that come back from consumers. Your rate of return equals the number of units returned divided by the total number of units sold. It’s normal to have some returns. But if one particular product is seeing a high or increasing rate of return, it’s time to check for possible problems with that product.
The equipment your operations team uses is not part of the inventory, but it’s still an important piece of data to measure. Log the maintenance times and uptime until the next scheduled maintenance to make sure all your equipment is in good working order. This will give you a heads up as to when a piece of equipment is reaching end of life and needs to be replaced.
Tracking the data will also help you have a better idea of ideal maintenance schedules, and gives a realistic expectation for equipment uptime.
If you haven’t set up a plan for data logging at your warehouse, now is the time to start. You’ll begin to see greater efficiency and more opportunities for improvement once you have the right data in front of you.