During peak sales periods, warehouses of all sizes – from a dedicated fulfilment centres down to the metaphoric ‘garage’ – can suffer from a lack of capacity to pick, pack and ship customer orders fast enough to meet customer expectations. Speedy and timely picking is a key element to ensuring on timely parcel despatch and is one of the key milestones in the journey to meet customer delivery expectations.
Now that we are in the middle of the year, it is time to plan now for the coming peak season and to make any changes to prepare your warehouse operation.
Understand your order profile
Firstly, it is essential to understand the types and the volumes of orders that the warehouse is expected to deal with. For example: Number of orders? What volumes of single line orders or multiple lines per order? Number of shipments by delivery service (such as same day, next day, or standard delivery). How many require special packaging or processing? And when are orders being placed by customers and how does this vary by day or even by time of day?
Reviewing this data, to understand the different permutations of the order profile, will help to define what processes are the best for your business and when they need to be implemented.
Also look to forecast what the order profile could be over the peak period, including expected sales up lift and timing of promotional activities. Also check with your buying team to consider whether there will be a change in the product mix, and also with your commercial or trading teams about whether product based promotions will be on offer, such as promotional bundles or free products, or services such as gift wrap. Examples such as these will change the order profile and therefore the level of activities within the warehouse.
Analysis of the order profile will also enable you to prioritise picking activities and also to identify whether there is any flex in the process, such as where order picking can be delayed because the customer has chosen a slower shipping speed.
Use picking processes that suit your order profile
Order picking can become a significant bottleneck in the warehouse, particularly where there are a wide range of products, delivery methods, and additional services being provided.
There are a number of different approaches to picking that can be used, including: pick to order, pick to cart, zone pick, wave picks,and others. However which will work best will depend on the overall structure of your warehouse, product mix and order profile.
To get started, conduct a benchmarking exercise of the current pick processes in order to understand how much time order picking currently takes and the corresponding pick accuracy in order to ascertain the overall effectiveness and efficiency of order picking. Identify what and where there are bottlenecks and also analyse the causes to establish what can be done to alleviate them. Where picking simply takes longer than expected, review with your picking team to understand what could help them to work faster and greater accuracy.
Set KPIs to measure performance
Measuring overall picking performance will enable identification of whether the picking processes are meeting the overall objectives. Measure whether: entire orders can be fulfilled (stock management), orders are being shipped by estimated despatch data (capacity, efficiency), pick accuracy (efficiency, effectiveness). By continuously measuring the picking activity, it not only provides warehouse staff with a target to achieve but can identify whether processes are working or whether operational improvements need to be made.
Also ensure that the returns process captures any incidences of mis-picks or damaged products. Both of these may be a result of picking processes within the warehouse.
Review, refine, review again
Online customer ordering patterns can vary significantly. Regularly analyse the customer order data to appreciate whether the quantity of what is being order have varied. Review KPIs together with this data to identify
What do you do to anticipate peak demands in the warehouse? How do you mix and match pick approaches to deal with capacity constraints?