Case Study: Supply Chain Planning at Thule

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Case Study: Supply Chain Planning at Thule

By Path to Purchase Institute Staff - 08/09/2019
Thule Group’s Rickard Andersson

Swedish outdoor equipment manufacturer Thule, most famous for its car roof racks, had been struggling with its demand forecasting effectiveness. The process was hampered by seasonal spikes in some of the company’s top-selling products on one end of the spectrum, and the intermittent demand of many slow-moving items on the other.

CGT recently interviewed Rickard Andersson, Thule Group’s vice president of supply chain, to learn how the company implemented new tools to overcome the challenges it was facing.

Tell us about your responsibilities at Thule.

In my role, I cover one of two geographic business areas within Thule Group, the geographical area Europe and the rest of the world. I'm responsible for purchasing, manufacturing, warehouse and transport, and also demand planning and IT (for business software applications, not hardware). I have nine people directly reporting to me.

Can you provide some background on the company as it relates to supply chain planning? How large is your extended supply chain? How many customers do you serve? How many SKUs does your system handle?

We serve approximately 28,000 customers across 20 locations and have up to to five network levels or tiers (locations supplying other locations).

The “customer” varies depending on the market. Some countries are best served by distributors because we distribute to 140 countries globally. For example, in South America and Asia, many countries are served by distributors that take full responsibility for the market. In other countries, we sell to retailers and e-tailers, and in other countries we also sell directly to consumers. 

To make things even more complex, we have a mix depending on product assortment in some countries, so we can have a distributor for bags but use retailers for rooftop boxes in the same country. It all depends on what best serves the customer in the market.

We have approximately 22,000 items, 12,000 of them active, and about 75,000 SKU/locations. Thule aims for an average 92% service level across the SKU portfolio. Popular, fast-moving products have a higher target of, say, 99%.

And then there are a large number of “long tail” items, slow-moving, intermittent items — to a big extent, spare parts — that are assigned much lower targets. We have almost a thousand different part numbers with unique fittings for different car roofs.

Thule’s business is also very seasonal, with different products for winter and summer. For example, we sell more ski carriers in winter and bike carriers in the summer.

What were the drivers – or pain points – that prompted Thule to pursue an inventory optimization tool? What are the goals?

We knew for a while that we needed to centralize our demand planning. We had reached a point where the demand planners were spending too much time filling out reports instead of drawing conclusions and making decisions to improve, for example, service or inventory reduction. At the same time, because we were growing a lot as a company, our SKUs were proliferating and this was adding to our planning complexity.

How has technology been leveraged in this project? More specifically, how has Thule achieved its goals through better use of data?

In addition to wanting to centralize demand planning and improve productivity, we also wanted to raise our service levels. We delivered below 80% service and set a target of 92% through the implementation of [solution provider] ToolsGroup’s SO99+ platform. We also aimed to reduce inventories by 15%.

Today, we have a strong connection between the service level and the inventory and this provides a basis for good decision-making. [The new software] comes with strong reporting tools so it’s easier for us to do “what-if” scenario planning. Being able to analyze assortments is very important for us because we're investing money to be able to sell much more. So we’re using the system to help us analyze, for example: if we increase the service level in an assortment, will it drive sales? And what impact will it have on inventories?

What system were you using before ToolsGroup and why did you want to change?

We used Infor’s M3 Demand Planner as a manual forecasting tool to support a decentralized demand planning process. As we moved to a more centralized process, it made sense for us to move to ToolsGroup’s more automated system. We also used, and continue to use, Infor’s M3 ERP system.

What was the timeline for the project?

The total implementation consisted of three roll-outs:

  • Start in Fall 2010 with go-live in summer 2011 for outdoor products/sport and cargo produced and sourced to Europe.
  • Start in Fall 2013 with go-live in spring 2014 for globally purchased packs, bags and luggage products from mainly Asia and sold globally.
  • Start in early 2015 with go-live in summer 2015 for outdoor products/sport and cargo produced and sourced to the U.S.

We assigned one Thule project manager and one IT person to drive this project. Our consultant, Optilon is a ToolsGroup specialist and led the software implementation, and also taught us how to model the data and use the system.

We started with the supply chain in Europe with production in five countries, and then rolled out to China and U.S. Approximately 20 users have access to the system, and around 10 to 15 are active users.

How many planners do you employ? How do they like the new system?

Nine of the 20 system users are planners. They have reacted very positive everywhere we’ve implemented. Fortunately, Thule is a relatively easy company in which to make changes it’s in our culture to continuously improve.

How have business processes changed as a result of this project?

We’ve moved from a decentralized, mostly manual, collaborative planning process to one that is centralized and highly automated.

What are some of the challenges you encountered during this change initiative?

We definitely experienced some delays in the beginning that were primarily related to issues with master data. Different sites had different information, and there were some legacy data problems dating back years. And then there were challenges integrating multiple sites and different ERP systems.

What are some of the benefits you’ve gained?

Definitely higher service levels. We took it from below 80% to 92% in two year’s time. That's a very good improvement. And we actually lowered inventories on quite a few SKUs. We achieved those higher service levels with lower inventories — and are moving to our goal of 15% reduction. And we achieved all that during a period of considerable sales and SKU growth using our existing team.

I also believe it’s generally positive to make these kinds of changes and continually question the status quo. In my experience, when you improve your processes, you get to put your best practices into action.

What best practices can you offer other consumer goods companies who are looking to meet service or inventory goals and improve planning accuracy?

The results we’ve achieved prove the merits of an automated, centralized planning approach rather than a manual, decentralized process. We are managing successfully during a period of high growth and still have control over our inventories. This is a big problem for many companies.

For companies centralizing and automating, it’s really important to keep a high level of communication going. We still communicate regularly with sales and product managers about, for example, phase-in, phase-out and campaigns.

What’s next? How can the fine-tuning of data analysis improve outcomes over time?

We are looking at introducing a promotion mapping capability. Campaigns and promotions are areas that we still mostly handle manually today. We want be able to use the system to calculate the impact of promotions on our inventory and service levels.

We also see potential in using the system more to help decide whether to make items to stock or to order. There is functionality in SO99+ that can support this. There are other capabilities as well, such as working with lot and batch sizes that we can exploit further.

As our assortment continues to grow, we are moving into new categories and I am confident that our current demand planning team will be able to manage it successfully now.