Mathematical model offers solution for conflicting KPIs


Reduce costs, improve service levels, cut emissions and minimize risks – companies would ideally like to do all these things, but they struggle to make the right trade-offs. During a recent Webinar Wednesday, AIMMS explained how a mathematical model of the supply chain can help managers to make the right decisions when faced with conflicting KPIs: “It’s not about which stakeholder wins or loses, but what’s best for the company.”

By Marcel te Lindert

For one in five supply chain professionals, their main challenge is not analysing disruptions or visualizing the supply chain, but dealing with conflicting KPIs. Catalina Perez, Senior Supply Chain Consultant at AIMMS, can relate to this. “In the past, supply chain was mainly focused on costs, but many more factors play a role nowadays,” she stated. “Companies want to maintain or even improve their service levels, but without holding too much stock. Meanwhile, the number of disruptions is increasing. Companies are keen to reduce their risks, but what does that mean for inventory levels? And then there’s the topic of sustainability. A carbon-neutral operation will result in more costs, and it might even cause a drop in service levels.”

So how can a company strike the right balance between all those different factors? A chief financial officer looks primarily at costs and working capital, while a chief commercial officer only cares about maximizing revenue. A chief supply chain officer is focused on service levels, whereas a chief sustainability officer’s aim is to reduce emissions. Research shows that just 15-20% of companies have succeeded in aligning all those different interests. Scenario planning can help, Perez said: “It’s not about who wins or loses. The fact that one stakeholder has more power than another shouldn’t be an issue. What does matter is finding the optimal balance between conflicting interests, such as costs and CO2 emissions for example. It’s about taking all the interests into account to find the best outcome for the organization.”

Translating KPIs into objectives

AIMMS supplies a tool that allows companies to model and mathematically optimize their supply chain based on scenario analysis. “First of all, we translate KPIs into objectives. Does the company want to minimize costs, minimize risks, minimize emissions or all three at once? It’s about making the right trade-offs,” explained Paul van Nierop, Product Owner Network Design at AIMMS. Next, AIMMS looks at the decisions the company needs to make, such as which products should be manufactured where and which transport modality should be used. For this, data is required. “You need some insight into demand. You need insight into the costs of the various modes of transport, for example. And lastly, you need insight into any restrictions that have to be taken into account – such as the maximum transport capacity on a particular route or suppliers’ contractual conditions. Our tool uses all this information to optimize the supply chain.”

Sound decisions

When ocean freight carrier Wilhelmsen planned to open a new office in Asia as a way of reducing risks, AIMMS used the tool to explore the trade-off between costs and emissions. “We built a model to analyse where the office should be located,” Perez said. “Then we used existing data to calculate how costs and emissions would change. As a result, our customer was able to make a sound decision. By providing upfront insight into costs and emissions, they were able to convince the senior executives and address the various stakeholders’ concerns.”

Meanwhile, computer chip manufacturer Intel wanted to improve its service levels by reducing lead times in the supply chain. This came down to a trade-off between cost and service level. AIMMS built a digital twin of the supply chain for Intel visualizing, among other things, how changes in lead times would impact on costs. “Right now they are working to add emissions to this digital twin so that they can improve service levels while controlling both costs and emissions,” Van Nierop continued.

Shortening response times

For British Telecom, optimizing service levels meant something else: shortening service engineers’ response times. “Because service engineers had to pick up the right parts first, their journey times were longer than necessary. British Telecom managed to shorten the journey times to 15 minutes while reducing costs. They are now using the model we built for them for other issues, such as determining the optimal locations for spare parts and calculating inventory levels at those locations.”

Another example given was furniture manufacturer La-Z-Boy, which has modelled its supply chain to explore nearshoring options. This has reduced the company’s risk while increasing its production capacity and cutting costs. Van Nierop: “The technology allows you to optimize the whole supply chain from start to finish. Some customers are more focused on the upstream part of the chain and others more on the downstream part, but we also have customers who look at the end-to-end supply chain.”