Sustainability in the digitized supply chain

Sustainability as the basis for a secure supply of people is no longer a niche topic, but has become a global consensus in recent years. At the same time, the definition of the term as a triad of economy, ecology and sociology has shifted in terms of values and goals.

Thus, in addition to the economic aspect, companies are increasingly focusing ontheir ecological and social mission. For example, how can individual companies act in a way that maximizes resource conservation with a circular economy approach? How can employees be integrated and motivatedto support the transformation towards a sustainable organization? Politicians are also reacting to this change with corresponding initiatives, laws and subsidies.

Companies are not only encouraged by social pressure and changing values as well as the resulting customer requirements to operate sustainably, but are also increasingly obliged to do so by legal requirements.

Our Center for Applied Research on Supply Chain Services believes that circular value creation is needed, with data playing an enabling role, In order to increase environmental and social sustainability in a way that meets the needs of people and businesses today,. Data can be used to design and control processes, organizations and systems in such an efficient, resource-conserving and social way that many of the current challenges can be solved in the sense of changed sustainability approach; especially if they are organized in a circular system that is geared towards as few losses as possible.

Digitization as a prerequisite for an efficient data value chain

Thus, a value creation is needed that covers the entire data value chain, commencing the acquisition and structuring of data, to processing through analytics methods, to new data-driven business models and services, with dedicated integration and consideration of people.

Digitalization plays an enabling role in this context, as it guarantees the necessary connectivity and comprehensive analysis for relevant data to successfully operate circular value creation systems. With IoT technologies, for example, manufacturing companies have sufficient enablers at their disposal with which they can establish not only efficient but also sustainable procurement, production and distribution processes in the future.

In the EU Green Deal, the circular economy is not only seen as an enabler of a sustainable economy, but also stands for securing competitiveness. It is considered to have the potential to halve today's emissions and thus conserve economic and ecological resources. Circular Economy encompasses the so-called R-strategies as an umbrella concept, which, depending on the interpretation, include inter alia re-use, remanufacture or recycling. In order to  trace and close the loops within a supply network and thereby dissolve information asymmetries, it is essential to collect data along the lifecycle of products. IoT technologies enable to evaluate Dataand make them available to the relevant stakeholders within the network, i.e. to design the Circular Economy in a digitized and data-driven way. The data analytics methods developed at our working group, such as Forecasting for Remanufacturing and Inventory Control for Manufacturing, and new business models such as smart Product Service Systems (sPSS) make a significant contribution to the implementation of smart circular economy.

We are researching how text-mining approaches can be used to determine a truthful picture of the sustainability maturity of companies, specifically in the context of logistics. One research focus is the development of metrics for objective assessment. The generation of distorted images of reality (keyword "greenwashing") is to be methodically solved by linking different data sources. Central considerations here are the appropriate selection of necessary indicators/key figures that are based on common sustainability standards and enable a comprehensive assessment of sustainability. Individual sources are critically reviewed with regard to their relevance for an objective, truthful representation as well as their timeliness and availability.

New sustainable processes in companies, triggered by technologies or changed organizational goals, initiate a change process for employees. Using data-based methods, we analyze and optimize processes and work environments from an employee-centered perspective in order to realize a sustainable change into a green and social corporate culture.

With the enactment of the Supply Chain Act and the ESG reporting obligation of the EU, the importance of transparent supply chains is growing. Automated collection for supply chain transparency is conceivable. Moreover, research on transparency/visibility is possible not only in the context of entire supply chains, but also with a view to individual aspects of such chains. The quality and traceability of supply chain data plays an important role. With the help of data-driven methods, the database of supply chains can be improved, and possible risks of missing information can be assessed.

The increasing diversification of the energy market poses fundamental challenges for our society, the responsible grid operators, as well as the state. In order not to overload the energy infrastructure and to use it in an energy-efficient manner, we are researching on procedures that can be used to predict the demand for electricity and heat in Germany as accurately as possible at different levels and over different time horizons. Furthermore, we are working on mathematical optimization methods to efficiently control the use of different energy sources in industrial operations.

The continuing strong growth of road freight transport is a major contributor to infrastructure and environmental pollution as well as traffic problems. Transport logistics could be organized more sustainable by reducing the approximately 151 million empty runs per year. That is why we use mathematical optimization, transport volume forecasts and process analyses to research the consolidation of orders and existing transport networks as well as the shift of freight flows to rail through more efficient process handling in combined transport (CT) terminals.