Every week, trucks from Aarhus, Denmark, distribute new products to about 250 Søstrene Grene retailers in Europe. The distribution of the quantities per item and per store is based on the intelligent allocation system from AGR. The system significantly improves precision, which means higher turnover, less lost sales, and lower inventory throughout the supply chain with less hassle.

The majority of Søstrene Grene stores receive about 100 new items each week. It is a central part of their business model to always offer customers a new experience with new product offerings, encouraging customers to visit the shop frequently. But how does the Head of Supply Chain, Jakob Skytt Gregersen, and his colleagues determine just how many items to deliver to each store when 60 percent of the weekly shipment is comprised of new items? Previously, the allocation was determined as a perecentaage of the overall sales budget. “We previously had one-size-fits-all solution, where the primary driver for the distribution of goods was our sales budget, so a high-turnover store got high quantities and a low-turnover store received lower quantities.”

Distribution Based on Forecast

That has now changed. Today, the successful retail chain has introduced an allocation system developed in collaboration with AGR, which distributes products to store with higher precision. This means that stores today receive the correct quantity for all items to match their real numbers and needs. This is a great advantage for both stores, the central warehouse in Aarslev, west of Aarhus, and the purchasing department.

But howcan that be possible? “Today, we can more accurately estimate the sales volumes of stores because we base the distribution of goods on sales histoy and forecast,” Jakob Skytt Gergersen explains, adding: “The majority of items are new, but we operate with a categorization of items in three levels. For example, the levels for a dining room chair may be: Level 1 Furniture, Level 2 Seating, and Level 3 Dining Chair. The sales history of a new product is then based on the history of a number of comparable goods in Level 3.”

Painless Implementation

According to Jakob Skytt Gregersen, this is a big improvement because the stores have different sales profiles, and therefore forecast based on sales history is a more accurate basis than the overall sales budget. He emphasizes that there are many nuances that play into sales, such as region, country, local conditions, location (street or shopping centre), etc.

The retail chain started working with the AGR solution in 2019 and has spent a lot of time preparing for its implementation. The software went live in late 2019 and was largely painless. The biggest challenge is data quality and lack of data. We have therefore invested in a Product Data Management system to ensure consistency in the creation of product master data and to ensure high quality data, explains.