Recent technological trends and business decisions have driven complexity, but also created new opportunities regarding demand and supply alignment. Three areas are especially impacted:

1. Minimum order quantities
2. Forecasting
3. Promotions

1. Minimum order quantities

Due to their particularities, convenience as well as dark stores are more likely to have a problem with the minimum order quantity (MOQ) than conventional supermarkets, for which the MOQ was initially defined.

• Convenience stores offer a wide variety of products on a very limited sales space. Usually, each product in a convenience store should receive only one shelf space. However, it is possible that a conventional MOQ needs more than one shelf space for a product. This means lost sales for the convenience store, as another product cannot be listed.
• Furthermore, certain low-running, high-value, but strategic products such as certain whiskeys or razor blades might drive capital costs for the store. We have seen cases with > 360 days on hand in a store for single products due to very low demand and high minimum order quantities.
• By far the most important challenge regarding MOQ for dark as well as convenience stores is shrinkage. Convenience stores have a problem, especially with dairy and deli products. In many cases, due to the limited shelf life and low demand, products are at constant risk of being thrown away or sold only with rebates. While the demand in a dark store will likely exceed the demand in a convenience store, it might have also slow-running items with limited shelf life with constant demand such as milk. Our experience shows that in a dark store, demand for slow-running products with constant demand cannot be directed through rebates or product promotions as it is possible in offline sales channels. It is therefore even harder for the dark store to sell such products through rebates, and the risk of shrinkage even higher.

Different options exist to better align demand with supply:

• It should be verified whether the smallest possible package size is offered as MOQ. In many cases supplier outer packaging consists of inner packages with only a fraction of stock-keeping units (SKU). It should not be a problem to break the supplier packages and add inner packages towards a delivery pallet.
• If inner packages are not available or do not solve the problem, a discussion between procurement and supplier can be an option. If the product is strategic for the supplier or the supplier has, for other reasons, little power in the negotiation, they might be willing to deliver inner packages with fewer items.
• It might also be useful to think about SKU piece picking. In this case, a picker (manual or automated) opens the supplier packaging, picks a single item, and adds it to a delivery box which can be stacked on a pallet. The additional cost for piece picking can be covered in >99% of the cases through the normal SKU margin.
• In case the SKU is not strategic and the other options won’t work, delisting can be a final option.

2. Forecasting

The addition of differentiated store formats and channels creates immense problems regarding time-based forecasting methods such as exponential smoothing. On the one hand, convenience stores have less demand per SKU. Therefore, some SKUs switch from being products with constant demand towards a product with sporadic demand, decreasing forecasting predictability. E-commerce is a different story regarding the way of forecasting. The acceptable level of stock out is well below the acceptable level of stock out in a store. This is because an online customer does not have the chance to switch a product himself. Packing alternative articles compromises customer experience. On the other hand, there are different types of demand and expected service in e-commerce. One market is same-day delivery, accepting delivery charges and being more in competition with food delivery companies such as pizza delivery. Another market is weekly customers, who order well upfront. There is usually enough time to ship SKU from the distribution center to the point of delivery so that there is not really a need for short-term forecasting. Finally, the demand from the different sales channels is strongly related. Customers switching between the formats are the norm, which again increases complexity.

As a common industry practice, advanced forecasting methods which consider more variables than just time and real-time information are used. These methods combine multiple customer touchpoints such as e-commerce, call center, or the store itself, with further information like on-shelf availability to predict an individual sale for a customer. A typical example of such a tool is the SAP customer activity repository.

3. Promotions

In the area of promotions, there are on the one hand more customer individual offers enabled through tools like Payback. These individual offers are, in our view, more related to the pricing and have not so much an impact on the supply chain. On the other hand, as outlined in this article, shortened product lifecycles, which are often run through promotions and new direct-to-consumer channels which act as real-life marketing laboratories competing for customers, emerged.

In the past, supply chains had 20 weeks or more to adapt to promotions and marketing campaigns. Today, the supply chain needs to react much quicker. We see two options to align the supply chain:

1. Manage supply: The demand is not as manageable as it was in the past. Get rid of old promotional push habits to create sales and start aligning supply with specific, short-term, and geographically dispersed demand.
2. Increase short-term responsiveness: It is important to adapt the supply chain towards smaller volumes with more frequent reactions to support upcoming product trends and align with rapidly evolving and diminishing promotions. Prerequisites are absorbed customer data to understand demand streams and the ability to piece pick, to allow small delivery sizes.