13 Aug Measuring Warehouse KPIs: Pick Performance
This is the fourth in a seven-part series looking at measuring KPIs for warehouse operations. We recently outlined the 7 KPIs to track for warehouse improvement. This series takes each KPI and examines it in more detail.
What does pick performance measure?
Pick performance is an outbound measure that calculates the number of lines or quantities picked per person per hour.
It expresses the degree of outbound productivity of a warehouse, allowing distributors to benchmark themselves to gauge how well they are doing as an operation. It can also be used to compare the performance of individual operatives against each other. Some distributors use the pick performance data to help set labour standards. They do this by undertaking an internal benchmarking and using it to set their expected performance levels. They then publish these as targets for their staff to perform against.
The pick performance KPI therefore identifies performance issues and where process improvements might be made. And it allows warehouse operations to figure out how long certain picking operations will take.
How is pick performance measured?
Pick performance can be measured in a variety of ways. It can be tracked at the order level, showing how long it takes to pick an entire order. Or it can be measured by lines, units or individual items.
The choice of which to measure will depend on the operation and its type of stock. Small items at a low level will be faster to pick than large items stored high up and needing a forklift to retrieve them, for example. So considering the usual make up of orders will allow the best way to measure to be identified.
What is a good pick performance score?
Again, an optimum KPI score for pick performance will depend very much on the type of operation. For example, picking small items like jewellery might see as many as 200 lines or picks per hour per person. But when picking pallets or packaging or timber, or where manual handling equipment is are necessary, an operative might only manage 15 picks an hour. And for some companies, it may take hours or days to pick one order.
It is possible to benchmark against similar companies – and when Balloon helps companies to benchmark, we will always choose comparative industries or operations – otherwise the data can be meaningless – but this KPI is best used as an internal measure for comparing operatives against each other. Or companies can carry out an internal assessment of how long picking might take on a “good day”, with someone who is known to be proficient and productive, in order to give a good benchmark level to aspire to.
How can you improve your pick performance score?
There are a variety of ways that pick performance can be improved.
Benchmark to identify improvements between operations. When Balloon helps companies to benchmark, we will always choose comparative industries or operations – otherwise the data can be meaningless.
Cluster picking can be employed. This is where a picker will travel around the warehouse picking multiple orders simultaneously. For example, they might be instructed to take five products out of a certain bin and place three in one box and two in another.
The pick and pass – or zone picking – method sees pickers allocated their own zone. They pick their orders within their area and then if required pass the order to another picker in another zone. This keeps operatives working in one particular area and limits time-consuming movement around the warehouse. In sizeable warehouses, a staged pick can be added to this process to improve performance further. This is where components of the order are simultaneously picked by different staff and are then brought together in one location.
Another improvement method would be to make sure that products are located in the most efficient positions in the warehouse on receipt. Usually this is achieved by calculating the “velocity” of products through the warehouse, that is, how regularly they are picked, or what velocity is used. From this, products can be graded as to whether they are fast or slow moving goods and can be positioned accordingly. This allows picking to become far more efficient as it avoids warehouse workers having to travel too far for the popular products.
The way that orders are distributed is also important. Ordinarily, picking orders that include slow moving products, where those items might be placed high up in the racking, would mean interrupting the pick to fetch a forklift. Sometimes it may be more productive to separate the orders or lines, segregating them into different types. So, one person can pick the products that are at height and needing a forklift, while another concentrates on the ground level picks. This doesn’t spoil the flow of order picking in the warehouse.
Some warehouse management systems (WMS) have the ability to store product dimensions, and from this calculate the number of boxes required. This cartonisation method informs pickers how many boxes and labels they need to take with them before going out to pick. In this way, pickers don’t have to return to a packing desk to get more packaging if the products don’t precisely fit the packaging they took with them. In addition, when integrated with a carrier system, cartonisation allows the carrier label to be printed as the picking label, removing the further step of labelling with a carrier label once picked.
Significant pick performance improvements are very possible with incremental changes over time. One Balloon One customer improved their picking performance by more than five times over the course of about two years. Typically, the implementation of a WMS brings a 20-30% improvement in overall warehouse as well.
If you would like to explore the options for improving your technology, or would like to discuss how to measure pick performance, we can help. Our supply chain consultants can analyse your distribution operation and advise on KPI metrics, as well as recommend technology to help boost your supply chain performance. Call us on 020 8819 9071 or get in touch.
Full list of articles in this measuring KPIs series: