Taking Kate into account

For most businesses, the majority of warehouse activity relates to order picking. Pick productivity has a major impact on overall warehouse performance and operational cost and it is therefore important to select the most efficient pick method for each product or product group. This article addresses the major inputs to this process and how current business trends affect these choices.

Product and order profile inputs
A classic measure used for product profiling is velocity, commonly expressed in units, cases, sales or other units of measure relevant to a business. The classic Pareto graph is used to group SKUs from fast to slow moving.

The number of times a product is accessed to fulfil orders can be expressed in either order lines or accessions. The latter measure is more closely related to the effort required to retrieve a specific SKU rather than volume alone; this distinction can be significant when comparing multiple demand profiles, for example store deliveries versus direct-to-consumer orders.

Physical characteristics such as cubic volume, weight, fragility, hazard levels, or temperature, often set hard constraints on what storage or pick method can be used. For uniform product ranges these factors are less influential than in businesses with a greater product variety.

Initiatives such as store friendly deliveries (picking product groups to specific areas of a store) can cluster products into smaller segments, which potentially cut across all of the above categorisation. As a result pick orders can be split into multiple smaller orders, which increases the pick effort required.

Short and medium term changes
The product life cycle stage of a SKU determines its relative velocity, levels of demand fluctuation, and likely change to both. This, along with seasonal demand, promotions, marketing campaigns and other external factors such as ‘the Kate Middleton effect’, mean that the choice of pick method needs to be dynamic, not static.

Part of the shorter-term product profile changes can be anticipated, and should be managed through sales and operational planning processes. More ad hoc requirements need to be absorbed through flexibility of pick operations, for example by reallocating SKUs between pick methods, using multiple pick locations for the same SKU, or a physical stock move. Alternatively, flexibility is built in by limiting the number of different methods and erring on the larger size for a pick slot.

In summary, a pick method allocation is not permanent and there needs be a clear process in place to adapt to changing needs.

Longer term developments
Historically, a warehouse would be a link in a chain, fulfilling demand from a single type of customer. Today however, a single warehouse can be required to fulfil both store and direct to consumer orders, leading to different demand profiles for the same products. To manage this, businesses can choose either to establish separate pick operations within the warehouse or to have a single, combined pick operation. While the former allows pick method allocation to be aligned more closely to the demand profile, it is less space efficient due to duplication of pick faces, and generates potentially conflicting demands on stock between the two pick operations, when stock runs low. A combined pick operation does not incur these issues, but can be less productive due to increased travel.

Along with channel proliferation, range expansion is another key trend, taking the form of more variations of the same product or supplementary products being offered. The resulting demand increase tends to be disproportional to the increase in SKUs. A steeper Pareto curve shows the greater difference between fast and slow moving items, potentially resulting in the need for additional pick methods.

The trend for shorter customer lead times is also resulting in later order cut off times, which condenses demand over a shorter time period. The associated increase in access speed constrains the suitability of some pick methods.

Throughout the economic cycle, business volumes will continue to change, either due to activity or mergers and acquisitions. Against this backdrop, warehouse and pick operations continually need to be updated.

Selection
There is a wide range of technologies available for order picking, each with various levels of complexity and automation. The preferred pick solution is a trade-off between capital investment and operational costs. To meet ongoing changes in product and demand profiles, flexibility is paramount.

The multiple measures that are used to make up demand profiles combined with SKU proliferation mean that decision making needs to be supported by quantitative analysis. Davies & Robson have extensive experience in extracting and analysing large quantities of data to quantify and evaluate the trade-offs between multiple pick method scenarios.