It is common industry practice to delivery super fresh SKU such as fish or daily prepared meals on a very frequent basis. It is not unusual that supermarkets get delivered multiple times throughout a single day ensuring high freshness. Dry or frozen SKU on the other hand, typically get delivered less frequently. Especially convenience stores with lower demand receive less delivery attention.

On the left side of exhibit 2 an exemplary demand and supply pattern for dry goods for a convenience store is shown. The store gets delivered twice a week on Monday and Wednesday.

• The store shows an above average stock out ratio which is due to a misalignment of supply and demand. As described, for a convenience store, forecasting demand is more challenging than for a conventional supermarket. Big demand peaks are usually around the weekend. The Monday and Wednesday delivery leads to a window with less certainty, especially for the in times of higher demand. As convenience stores have only limited sales space, they are not fitted to have demand buffers, which are needed in case of problematic forecasting with long replenishment times.
• A second aspect is that the store can hardly handle the supply peaks Apart from grocery deliveries on Wednesday, the store has further deliveries from supplier direct delivery (beverages) and fresh goods on the same day. Convenience stores are run with very few personnel and have no backroom to temporarily store SKU. Delivered pallets are put directly into the sales zone. Sales personnel start to sort and refill the shelves directly from these pallets. As the three pallets might hinder each other, increased sorting, checking and refilling times are the norm. Furthermore, the customer experience is drastically reduced because part of the store is not accessible, and SKUs are not in shelf although they have been delivered.

From our perspective, the delivery patterns need to be changed to better match demand.

• A key element to achieve this target for convenience stores are combined deliveries for dry and cooled goods on the basis of the fresh delivery pattern. This not only reduces the uncertainty period for dry goods but also decreases the supply peaks. The store can directly refill the SKU into the shelf. A key requisite for combined goods is of course the ability to mix and match pallets in a crossdocking area for example.
• A second solution could be extending the delivery period towards off-store hours such as night or Sunday delivery, for stores which are not limited by noise regulations. This would save delivery time due to less congested roads giving extra time for a denser delivery pattern.
• The nightly delivery should also be the favorite replenishment model for dark stores. As dark stores are not directly in city centers, regulations should not be an issue. Non same day delivery orders could be delivered easily according to the specific customer demand at the night before customer delivery from the DC to the dark store. This option would allow to use non congested roads and utilize the transport network optimally.