These use cases share a common feature: to complement or even replace the traditional way of solely considering costs and service levels when preparing management decisions. Even though 90% of the S&P 500 companies report on their sustainability performance (see The G&A’s 2020 Russell 1000 Flash Report), most lack the data or capabilities to integrate these considerations into the decision-making processes related to supply chain and logistics, where the majority of influenceable GHG emissions typically originate.

Unfortunately, many companies so far only reduce their emissions through isolated initiatives such as changing packaging, consolidating orders and the change of transportation modes. Although this should have a positive impact on their carbon footprint, the true levers to substantially reduce GHG emissions lie somewhere else. Optimizing end-to-end supply and distribution networks – from sourcing over production to delivery – has a much higher and more sustainable impact. This is especially true for companies that could partially regionalize their supply chain.

This is where our digital twin comes into play. This digital replica of your supply chain is not only capable of optimizing costs but include CO2 emissions as part of the decision framework. Consequently, this kind of analytics and related decisions made on top management level need to be supported systemically by organizational design, the right metrics, and incentives as well as more than a pure cost-reduction objective.

Multi-Objective Decision-Making with the Digital Twin

When companies approach us regarding potential sustainability improvements in their network, the key questions usually are: Where are potential sources to reduce my emissions and what impacts do they have on costs? What is the right balance of CO2 reduction and supply chain cost? What changes would I have to make in my supply chain if I were to reduce my CO2 footprint by 10, 20 and 30 percent?

The goal for supply chain leaders should be to better understand the potential trade-offs between costs and CO2 footprint. A digital twin helps to create transparency and support decision-making. To achieve this goal, we usually employ a field-tested method, starting with the traditional cost-based analytics and given service levels. By using a digital twin, we can change the target base and redesign the network based on the objective to reduce CO2 emissions. In multiple iterations, we combine the cost and CO2 trade-offs based on your given cost and CO2 reduction goals and illustrate the complex and multi-dimensional findings (Fig. 2). Furthermore, the digital twin illustrates with geographical maps how your future supply chain might change considering the combined targets of low(er) costs and emissions.

This way, our digital twin solution helps you to narrow down your options faster and support decision-making when you evaluate the right supply chain strategy for your company based on goals such as climate neutrality.

The digital twin also helps with other tactical and strategic decisions. The holistic approach and the many use cases show the unlocked potential to e.g., save costs and emissions at the same time.

We love to be challenged – please contact us to jointly find out, how we can support you on your supply chain transformation journey. Let us validate, how we can bring your decision-making processes to the next level, while making your supply chain greener.

We would like to thank Dominik Hartung and Tim Wäger for their valuable contribution to this article.