Circle K achieves an accurate forecast leading to a better prediction of stock levels

Retail

Industry

Over 12,000 worldwide

Fact

Supply chain

Use Case

Challenge

Before the Anaplan platform, Circle K managed its supply and demand planning in a disjointed combination of Excel® and enterprise resource planning (ERP) systems. This led to inaccurate forecasting, an unstructured approach to information gathering, and conflicting demand forecasts.

Solution

With the Anaplan platform, the supply chain planning team at Circle K built a connected and collaborative process for planning supply and demand for their European locations. Using intuitive forecasting and scenario-based planning, the planning teams at Circle K now have a dynamic capacity forecast per product and station so they know exactly where and when to send fuel.

Results

The supply chain planning team at Circle K now has an accurate 18-month rolling forecast of current and future stock levels, which has resulted in inventory reduction. They’re also finding benefits in lower distribution costs (because they know when to distribute product) and lower product costs (because they know how much product they’ll need at which times).

Why Anaplan

Circle K chose the Anaplan platform for its ability to get up and running quickly with an iterative development process. Other important factors were the platform’s scalability and intuitiveness, leading to high end-user acceptance.

Magnus Tagtstrom, Senior Director of Supply Chain Optimization, discusses Circle K’s journey to connect their end-to-end supply chain. Now with Anaplan, when Circle K updates their allocation, it automatically has an impact on the people doing the shipping plans.

I’m Magnus Tagtstrom, and I lead supply chain optimisation in Circle K. We have four to five products and around 2,500 sites. One of my objectives has been to try to connect the dots in the supply chain. I think we had good solutions, but people were doing forecasting in silos, so I wanted to connect that planning end to end. I looked into other point-specific solutions—the requirements from my side was that we need something flexible and we need something quick. Then I came across Anaplan, which for me is like a … I don’t know, I think people use the words “Excel on steroids.”

The approach that we’ve taken to the entire implementation is: I would like a solution that we can maintain in-house. We’ve trained model builders in my team to develop this in the future. But we were not used to Anaplan, and we were not used to quick development—and we were not really used to what you could do with it. So therefore we chose Executit, which is a local partner here in the Nordics. They’re quick in the development, and they can challenge me. So the solution that we built is replicating a lot of Excel’s, replicating a lot of ERP functionalities. But the nice thing is that we created a connector to the ERP systems, so we get daily updates on volumes and daily updates on sales across the entire field supply chain automatically integrated to the model.

Biodiesel is a big thing in the Nordics. We would like to sell as much as we can, but we have a shortage of it, so we need to allocate it to where our customers need it the most. So taking the Anaplan solution that we have now, it actually automatically had an impact; e.g., what products do we need to supply into our terminals? So I think, for me, that was the kind of, “Okay, when you put the plans in the same place, when you put the known things and when you do allocations, it automatically has an impact on the people doing the shipping plans.”

Some of the clear benefits that I see is the forecast accuracy—being specific in forecasting and then also having the BU inputs to plans into that—I think that will help us to have the right stock level throughout all our sites. That’s money that we have as a buffer in the supply chain now.

So when let’s say [we buy a] product that we got from the Anaplan solution, we have full visibility of our inventory levels and the inventory levels, as well as forward-looking inventory levels, because we know how much we will sell from our demand plans and we know when we can distribute it to sites. This makes us much more specific in being able to drive down both distribution costs and working capital. So what we utilized is taking analytics, in our case power BI on top of Anaplan, to be able to create a much better report to get the insights. With Anaplan, I think we have taken this low-tech industry into something more high tech, and we’re ready for the future.

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