SKF

Company Overview

SKF has been a leading global technology provider since 1907 and is the world’s largest bearings producer. Their fundamental strength is the ability to continuously develop new technologies – then use them to create products that offer competitive advantages to their customers. They achieve this by combining hands-on experience in over 40 industries with their knowledge across the SKF technology platforms: bearings and units, seals, motion technologies, services and lubrication systems.

Project & Objectives
SKF set out to create a global planning approach with the goals of improving both effectiveness and efficiency. Besides wanting to move to more centralized planning and optimization, it also sought to plan “dependent flows” together – that is planning all the globally interrelated end-to-end activities associated with each item. SKF saw potential to improve efficiency through a high level of automation across the demand chain.

SKF chose Optilon as a partner to implement ToolsGroup’s SO99+ for demand planning andinventory optimization. The implementation followed a four-phase process; Feasibility, Proof of Concept, Pilot, and Deployment. Joerg Schlager, Business Transformation Manager at SKF, calls this approach “first trust, then thrust”.

The new approach supported by Optilon and SO99+ prompted SKF to make a major shift in its demand planning organization. Rather than planners being organized by local territories, they now have global product responsibility. Each product has “one global forecast, one planning method, one responsibility, and true end-to-end accountability,” says Jörg.

Each planner owns the forecast and inventory globally and an end-to-end plan that is responsible for achieving external customer service targets, as opposed to multiple independent organizations, often with more internally focused targets. Deviations are handled globally, even though execution is addressed locally.

With the new model, each planner is responsible for multiple roles including procurement, master scheduling, distribution and demand planning. In their new roles, these “global planners” handle inquiries from all regions. “With great power comes great responsibility”, Jörg half-jokingly quotes Ben Parker, uncle to Spider-Man.

As in any large project, SKF has faced many challenges along the way. A “digital twin” of the entire distribution network was required for planners to make global decisions based on full data visibility and full control of their reference data. As Jörg says, “If you are going to travel safely on autopilot, take care of your input.” This required a significant amount of master data cleansing and master data management for 800,000+ SKUs across 40 installations of 5 different systems.

Each product now has “one global forecast, one planning method, one responsibility, and true end-to-end accountability,”

Joerg Schlager, Business Transformation Manager at SKF

Results & Benefits

SKF has achieved a 12% stock reduction in the factories and warehouses deployed so far, with less planning resources—all while keeping service levels stable.

The new approach has also significantly improved SKF’s ability to handle exceptions and inquiries. While multiple time zones present a challenge, it can still respond faster than before because it eliminated process latency.

The evolving organization also aligns better to the Supply Chain Council’s SCOR model – a diagnostic tool for benchmarking performance. Whereas previously functional groups had been managing multiple roles, the new approach allows, for example, the sales team to focus on selling. Planning moves to the factories, consolidating the Source, Plan and Make functions into one organization, with Logistics focused on Deliver. It makes end-to-end optimization possible, empowers the team, and reduces internal competition.

Jörg is already looking ahead to the next transformation in the context of what some are calling “Industry 4.0”. This next step involves increasing the “clock speed” of the planning cycle by taking advantage of real-time data from MES, logistics systems and possibly even smart data from sources such as sensors or the web. This type of data could further reduce latency, allowing for even faster optimization and response. He foresees a new highly automated approach that includes increasing customer response speed and reducing internal waste.

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