Store inventory replenishment is an essential yet surprisingly complex task for any retail business. Successful replenishment strategies maintain high levels of on shelf availability whilst optimising the cost of providing the replenishment service. Get it wrong and not only will sales suffer but both DC costs and stock levels could be higher than necessary.
Why is store inventory replenishment so difficult?
Firstly, there is the complexity of products and stores. A typical retail store may have thousands of products each with many unique attributes. In turn, a retail chain could include dozens or hundreds of stores of various sizes across a wide geographic area, each carrying different ranges. A popular product in one store may not be in another. A large store close to the DC might get daily deliveries whereas a remote, local store would only justify weekly deliveries.
And then there are other factors to consider:
- Store shelf capacity and backroom space;
- Too little stock on the shelf might give a store too lean an appearance and put shoppers off;
- Whether to pick in packs or cases or singles and the consequences for stock preparation and picking both in the DC and stores;
- Packaging waste handling in DC and store;
- Automated order system capability. Can the system manage different replenishment rules for every combination of store and product?
Custom and practice can often result in businesses operating sub optimally. Growth in sales and range, for example, can mean that what was an appropriate case quantity some years ago may not be so today. As retailers continually work to maximise the revenue from every part of their stores, the decision whether to pick in singles or cases or a combination of the two can change. And even if a case quantity is deemed the best replenishment unit, what size cases are optimal for each product? What is the most appropriate replenishment order trigger point? How often should the stores be replenished?
Instead deficiencies in ordering systems or the way they have been configured often lead to Store Managers being given considerable freedom to adjust order quantities in ways that may not be best for the business.
These appear such simple questions and yet the answers are not easy to get at. So, in response to a number of requests, The Logistics Business has developed a new module – Replenishment Strategy Simulator (RSS) – to add to its suite of modelling tools.
The RSS model takes into account all of the key factors that influence store replenishment. They fall into three categories:-
- Stores – shelf replenishment effort and store stock holding;
- Distribution centre – stock levels, pickface preparation and picker productivity;
- Supply chain – inbound costs (suppliers delivering in the required format), waste returns from stores, store delivery equipment.
The model takes a range of data inputs from the existing operation such as :-
- Actual stock level snapshots;
- Point-of-sale (POS) transaction history;
- Product attributes such as pack sizes;
- Order trigger points at the product-store level for sample stores and sample periods;
- Polling and delivery schedules;
- Minimum order quantities.
Different replenishment strategies can be modelled and the main outputs from the modelling are:-
- The number of order lines generated. This is the main driver of the picking workload;
- The number of pick face accessions and pick units removed from the pick faces;
- Comparative net costs of alternative strategies;
- The store stockholding and on-shelf availability.
The following figures generated by the RSS model show visual examples of the impacts of different strategies on the replenishment pattern of a sample product using the “Min” logic.
Figure 1: this product is always replenished in case multiples. A replenishment order of 1 case (6 singles) is triggered on the stock polling day when stock level drops below the Minimum setting, which brings the stock level above Minimum when the delivery arrives in two days.
Figure 2: single item replenishment is allowed in this scenario. As a result, the average stock level is reduced and now never exceeds the Minimum setting (apart from the initial starting stock level used in the model). Replenishment frequency increases dramatically which will result in a significant increase in order lines.
Figure 3: the Minimum setting is reduced while single item replenishment still applies. As a result the average stock level is lower and replenishment frequency remains very high. Compared with case picking, a single item replenishment strategy reduces stock level fluctuation and keeps it close to the Minimum level, which may in turn provide the opportunity to reduce safety stock.
Figure 4: This last scenario halves the replenishment frequency, which results in a reduction in order lines.
The RSS model automatically repeats the same simulation illustrated above for all sample products from all sample stores, aggregates and translates the results into workload (man-hours), total operational cost and overall stock level.
Using this tool, we have already helped a number of retailers ensure that they are picking and replenishing in the most appropriate pack quantities and frequency, thus maximising on shelf availability and optimising overall operating costs.
If you would like to find out more about how the RSS model could help your business, please contact The Logistics Business through our website www.logistics.co.uk or telephone 01527 889060.