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World’s Fifth Fastest Growing Retailer Automates Replenishment Planning

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Replenishment Planning
Erkan Ceritoğlu, the Director of Sales Operations and Supply Chain at A101

A101 is the fifth fastest growing retail company in the world. Their convenience stores – whose average footprint is 250 square meters – offer everyday low prices; customers don’t have to pay a premium for convenience. This has proven to be a successful strategy for Lidl and Aldi as well. A101 is the largest retailer in Turkey with over 10,000 company owned stores and 48 regional distribution centers and one E-commerce fulfillment center.

Erkan Ceritoğlu, the Director of Sales Operations and Supply Chain at A101, explains that, they don’t keep prices down by relying only on private labeling. A significant portion of A101’s selection is based on products from well-known consumer product companies. They can offer discounted pricing based upon rigorously managing the operating costs and then using their size to get the best prices.

Supporting Growth Requires Automated Replenishment Planning

How fast has A101 grown? In the last ten years they have opened more than 10,000 stores! That growth, Mr. Ceritoğlu asserts, would not have been possible or profitable without automated replenishment. “To support this massive speed, we needed a solid replenishment solution in place.” The company’s supply chain planning and automated replenishment solution comes from Solvoyo.

SAP/HANA is used as their key enterprise application. At the end of the day, when the stores close, the sales are posted to SAP. Solvoyo uses this store-level sell-through data to automate the replenishment calculations. The next morning, store managers look at their hand-held terminals to see their recommended purchases. The store manager can – within strict limits – override an automated purchasing recommendation. The typical store holds more than 1,500 stock keeping units (SKUs) – an SKU is a distinct product/packaging configuration. A manager can only change the order for less than 20  SKUs. The overrides are also tracked in the system, and A101 has achieved 99% acceptance rate for these recommendations.

Mr. Ceritoğlu explained that fruit and vegetable is harder to plan because spoilage and write-offs lead to lower inventory accuracy in these categories.

By noon the same day, the store orders then flow to one of 48 regional warehouses for replenishment. Many stores get daily deliveries.  Most of the stores receive 7 shipments per week but some only receive four or five shipments per week because of transportation infrastructure challenges or lower sales.

The Solvoyo solution is not just a forecasting and replenishment solution. Accurate fulfillment requires that Solvoyo also understand a number of replenishment constraints. The solution needs to understand what days stores get shipments and the store planogram – how many items of a SKU are allowed on the shelf. Further, Solvoyo’s planning is also dependent on the shipment packaging hierarchy – this SKU ships in a carton containing 4 items, or perhaps, the SKU cartons make up a layer on a pallet with 16 items.

Solvoyo is an end-to-end planning solution. It does not just generate replenishment at the store level, it understands the cumulative demand regional stores are placing on a warehouse and also generates warehouse-level replenishment orders to the suppliers. In this case, the solution needs to understand supplier lead times and delivery frequencies. Big suppliers can deliver to an A101 warehouse every day. Smaller suppliers, operating out of just one national distribution center (DC), can’t achieve this level of service.

Warehouse dock scheduling is not a constraint. “Our DCs work 24 hours a day/7 days a week, there is no labor constraint” Mr. Ceritoğlu explained: “The main constraint is the minimum order quantity.” A product’s minimum order quantity is stored in the SAP application.

Over time, the Solvoyo planning footprint has gotten bigger. Currently, Solvoyo is only used to plan the replenishment of nonpromotional items. A101 has been testing the forecast accuracy of Solvoyo around promotional items; this is a much more difficult forecasting challenge. The solution looks at how similar products in the same product category have sold. What kind of results is A101 getting here? “So far so good,” Mr. Ceritoğlu said.

The Solvoyo solution really showed its power when COVID hit. “When everything is normal, the system is bullet-proof.” With COVID, the retailer saw demand spikes for 900 items out of the 1600 the retailer carries.  Within a week, the Solvoyo solution was automatically adjusting safety stocks to accommodate the demand surges.

“We established a diagnostic managerial dashboard,” Mr. Ceritoğlu went on to explain. A team member could enter demand inputs manually where there were sudden peaks in demand.  “We secured replenishments to our DCs in large quantities within a week. Solvoyo really supported an agile response during COVID. From April to May, our sales were up more than 50%. Our out-of-stocks only increased 3%, and they were mainly related to supplier issues. There were no empty shelves.”

What advice would Mr. Ceritoğlu have for other retailers considering a similar journey? “Solvoyo as a platform is great, but it can not operate as a stand-alone application. You need to design the backbone first.” For A101 that backbone consists of SAP/HANA, their warehouse management system, and Solvoyo. “These solutions work simultaneously and seamlessly together.”

COVID Is an Opportunity, Not a Threat

What comes next? “Currently I and my team are working on online groceries.” COVID has increased the trend to online ordering and A101, with its large number of stores located close to customers, has a “big opportunity.”  Main goals is to use current store footprint for lower last mile delivery costs. The company would need transportation partners andthere are ecommerce logistics companies in Turkey with as many as 2,000 vehicles.

In addition, the retailer could explore different options; convert some of their stores to dark stores – stores that are not open to the public but which become solely focused on fulfilling local orders.

They also recognize that ecommerce orders are more expensive. “Some grocery chains lose money on every order,” Mr. Ceritoğlu asserted. A101 will charge a delivery fee. But the company will also work to reduce their costs so that they can lower the delivery fees over time. To do this, the company will “have to invest in technology and automate the picking process in the store.”.

A101 is constantly testing new technologies at its dark store where they are examining whether a shelf-level image recognition solution could improve store level inventory accuracy. A solution would have cameras on the shelves and understand the store’s planogram. Shelf-level image recognition solutions do not insure perfect inventory accuracy; the solution can see whether a slot is empty or not, but often cannot determine how many items of an SKU are on the shelf – the solutions can’t peer around items on a shelf and see if there are other items behind the items at the front of the shelf

The retailer can also look to put limits on what inventory can be used to fulfill an order. “If an item on the shelf drops to 5, we can just choose to not list it” as available for purchase. Solvoyo, which forecasts the velocity of sales, will be able to implement this as a business rule.  In addition, the current inventory management solution has the flexibility to quickly accommodate these types of changes in business operations and can adjust the store safety stocks to account for the consumptions due to fulfillment

While the outlook for the global economy and the retail industry in 2020 is uncertain, the outlook for omnichannel retailers that can profitably deliver last mile food & beverage orders looks far brighter. A101 looks to be perfectly positioned.

Mr. Ceritoğlu will be speaking on this topic in greater depth at ARC’s Supply Chain Forum on February 16th and 17th. Registration is free for end users.

The post World’s Fifth Fastest Growing Retailer Automates Replenishment Planning appeared first on Logistics Viewpoints.


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