Value Creation: Crisis-proof strategies

For several months now, many people have been experiencing just how vulnerable the global economic system is to disruptions. Whether it’s large furniture, a PlayStation 5 or a new car, there are delivery problems with many items and, in some cases, waiting times of several months. For many companies, the global shortage of chips has been particularly drastic. In numerous industries, sales fell in 2021, and things are not expected to improve any time soon. The current year will also be one of fits and starts according to the forecast of the industrial association BDI. “Despite the full order books, the lack of microchips, components and raw materials will continue to impair production for a relatively long period of time,” says BDI President Siegfried Russwurm. These bottlenecks reduced industrial value creation in Germany by over €50 billion in 2021, and a similar impact is expected for 2022. The economic losses also have medium and long-term consequences on various levels. The realms of business, science and politics are all analyzing the fragility of supply chains and drawing corresponding consequences. Companies are discussing measures such as near-shoring, multi-sourcing and redundancy capacities. The political debate about technological sovereignty continues to pick up steam. Scientists, meanwhile, are developing platforms for resilient supply networks, as well as other methods for making supply chains less vulnerable.

Scrutinizing processes, simulating crisis scenarios

Until these activities bring some relief, however, companies need to take other measures to secure supplies for their production processes. VDE also offers general support in purchasing and procurement: through VDE Global Services, supply chain management assistance ranging from reviews of possible suppliers in Asia to outgoing goods checks are available. Here, VDE Renewables focuses on companies and project managers in the field of renewable energies. “Our approach consists of a detailed, customized service concept that’s geared toward all stakeholders in the energy industry,” explains Burkhard Holder, CEO of VDE Renewables. In normal times, the experts at VDE Global Supply Chain Services aim to ensure that ordered goods can be delivered in the required quality on the agreed schedule. However, regional lockdowns and travel restrictions are also making corresponding audits more difficult. “Our inspectors haven’t been able to visit factories without making various arrangements,” says Michael Wenzel, key account manager for supply chain services at the VDE Testing and Certification Institute. This was another chance for digital communication channels to shine as a means of performing virtual inspections, for example. “Pre-shipping inspections also had to be transferred to a hybrid process in some cases,” says Wenzel. In such instances, seals are now sent to factories, and sealed samples are then sent from there to the laboratory on site where the inspection is carried out.

Balancing efficiency and resilience

Many companies are currently putting their processes and supply chains under the microscope. This includes determining stock turnover, optimizing stock management and figuring out which components are critical and where they are produced. “It makes sense to do more dual sourcing – that is, build relationships with alternative suppliers – for strategically critical components,” advises Sylvia Trage, director of the consulting division at KPMG. According to a McKinsey study, one in four medium-sized companies plans to regionalize its supply chain. Bringing back certain areas of production (reshoring) or relocating them to more cost-effective places closer to home (near-shoring) are now on the agenda. However, companies face a difficult choice: should they prioritize efficiency or resilience? For many years, the paradigm was to remove unnecessary structures for cost reasons. Tools such as resilience engineering are now helping to recalibrate the relationship between these two aims. “With a performance-time curve, we can calculate how a company’s performance will suffer in the presence of various conditions or measures during a crisis,” explains Alexander Stolz, head of the safety technology department at the Fraunhofer Institute for High-Speed Dynamics. Comparing the results will then show which of two options is more resilient. The process also includes simulating crisis scenarios. Here, it’s not particularly important exactly how problematic situations are predicted. Instead, companies should make deductions on this basis and, for example, develop plans for a scenario where half of their workforce cannot work on site. Whether this is due to a pandemic, a natural catastrophe or a system failure is ultimately irrelevant. Work is also progressing on new technical solutions. Since last summer, the German Federal Ministry for Economic Affairs and Climate Action has been providing a total of about €44 million in the context of the Artificial Intelligence innovation competition to support four projects in the area of crisis prevention and management.

In the PAIRS (Privacy-Aware, Intelligent and Resilient Crisis Management) project, Advaneo GmbH is working with partners to develop a learning AI platform for managing crises. The German Research Center for Artificial Intelligence (DFKI) is leading a similar undertaking and working on a semantic platform for intelligent decision and operations support in control and situation centers (SPELL). Another project aims to identify and predict bottlenecks in the supply chains of companies and public authorities more quickly in crisis situations. In this case, digital twins are being used to simulate supply networks and make it easier to predict the effects of various events on the supply chains at hand. The focus is on crisis-relevant goods such as disinfectants, protective equipment or blood reserves. This communication and information platform for resilient, crisis-relevant supply networks (ResKriVer) is being led by the Fraunhofer Institute for Open Communication Systems (FOKUS), whose partners include the Berlin fire department and Charité university hospital. The CoyPu (Cognitive Economy Intelligence Platform for the Resilience of Economic Ecosystems) project is also developing an AI-based platform for efficient crisis management with a focus on improved prognoses of product demand. This is intended to help medium-sized companies in particular make their production and supply chains more crisis-proof.

Although these four projects differ in terms of their target groups and their focus, there are also a few common denominators. “That’s why we compare notes with the other projects,” says Michael Martin, who heads both the CoyPu project and the Efficient Technology Integration Competence Center at the Institute for Applied Informatics (InfAI) in Leipzig. “There are synergies in the collection or preparation of data, for instance,” he explains. Acquiring data was the project’s first major task – and something of a legal challenge – in the six months after it started. Major companies such as Infineon and Siemens are involved and providing data from their own supply chains. “However, we intend to expand our partner network even further,” Martin declares. At the end of the day, the platform is intended to provide support for small and medium-sized companies in particular. “After all, what medium-sized company knows all about its entire supply chain?” Martin continues. While major companies can afford consulting on this subject, it’s much more difficult for SMEs. This is why the project’s partners also include DATEV, which wants to offer consulting services related to handling crisis situations to its medium-sized customers in the future. Data from the WHO, the OSCE and the DIW is also being used in the development of the platform. The DIW, an economic research institute that was founded in 1925, possesses extensive data records from historical crises, which are to be used to train the algorithms. “The idea is to merge various data sets and build up a large knowledge network which can be examined with AI-based approaches,” Martin says. This should make it possible to predict future demand or delays in logistics – for example, if borders are closed. “Preparing the data so that people can understand it is crucial, of course,” Martin points out. Warnings might take the form of a traffic light system, for instance; the first drafts for corresponding dashboards are already in progress. In addition, there is the challenge of finding and defining the right parameters for the models and then integrating them into the relevant rule sets.

The CoyPu project is to run for a total of three years. Even if the COVID-19 pandemic will hopefully be over by then, Martin is convinced that there will still be a need for such tools. “Logistical problems are a constant danger which will go on causing us difficulties even after the pandemic,” the IT engineer predicts. From natural events like volcanic eruptions that cause flight cancellations to major accidents (or even wars) that can hinder the delivery of scarce raw materials and other goods, there will always be crises on different levels. Research into measures for building up resilient supply chains was also the focus of ResiLike, a cooperative project between the Fraunhofer Institutes for Industrial Engineering (IAO) and for Factory Operation and Automation (IFF). A central question in this endeavor, which was completed in December 2021, was how to recognize early on that a supply chain is faltering. Indeed, companies often have deficiencies in terms of overarching corporate foresight, the continuity of data and process chains, and the availability and deployment of simulation models. They thus often fail to respond appropriately even to foreseeable problems, as was shown by the discussions and feedback in the ResiLike project. “It should have been possible to predict the consequences of the chip shortage, but many companies simply shut their eyes to the problem,” says Michael Hertwig from the digital engineering team at Fraunhofer IAO. On the other hand, when the Suez Canal was blocked for several days after the freighter Ever Given ran aground, it took much longer than expected for numerous consequences to become evident. Containers, for example, were still missing at ports several months later. Many companies can respond if they receive information about supply chain disruptions at an earlier stage, Hertwig explains. Thanks to the New Silk Road, for instance, it’s easier to switch logistics carriers and use a train line instead of a ship from central China. “Here, it would be helpful to have digital models that link information and help you derive appropriate decisions,” Hertwig suggests. A new approach to the integral mapping and optimization of logistics processes involves digital value creation twins. Similar to digital twins in production, the aim here is to map organizational relationships along the value creation chain.

Complex technical questions and fundamental challenges

"We’ve played it all through as a concept,” Hertwig says. There are now discussions about consortium projects to develop the idea of digital value creation twins further.  However, apart from the complex technical questions they entail, there are some very fundamental challenges, as well. Digital simulations of supply chains require a high degree of cooperation between the various stakeholders in order to create sufficient transparency. In too many cases, that is what has been lacking thus far. “The problem we’ve encountered relates to the willingness to share information,” Hertwig says about the findings of his research team. And even when the data is actually available, there are issues with automation and digitalization. This is evident in logistics, for instance, where standardized labels are now in use. “However, the logistics labels aren’t standardized to such an extent that you can simply scan them to get all the information that you need in your system,” continues Hertwig.

Costs often outweigh benefits in data preparation

QR codes are used in some cases, but according to Hertwig, automatic readouts by cameras and scanners are difficult in practice because the labels are often positioned very differently. Variance in fonts and print quality also causes problems, he says, which is why information is generally still read out and transferred manually. For this reason, several members of the Association of the Automotive Industry are working together on AI image recognition software that should make such data readable. These sorts of difficulties are also arising at other points along supply chains. “The data quality often isn’t sufficient to digitalize the process from end to end,” states Hertwig, who also points to the lack of a single, shared language throughout long processes. He says this is why things like standardized exchange formats and interfaces are necessary. “We also need a clever way to structure data and make it readable and presentable for subsequent processes,” Hertwig continues.

It was therefore also difficult for the experts at Fraunhofer to create forecast models for supply chain disruptions in the context of ResiLike. “It was a huge effort to aggregate the information and use it to make predictions,” Hertwig reports. “In cases like these, the cost-benefit ratio in data preparation is often negative.” Exactly how this can be optimized and which findings from ResiLike can be useful to companies in practice are the subjects of various transfer projects that are currently being planned. The results of ResiLike will also be presented in various webinars in the spring. However, it seems evident that companies should make more of an effort to tackle these issues, regardless of the COVID pandemic. “I’m convinced that climate change, for instance, will influence the supply chain structures of our industry far more than this pandemic in the medium to long term,” says Julia Arlinghaus, head of Fraunhofer IFF in Magdeburg. “As soon as we actually quantify environmental costs and transport costs increase as a result, the supply chains will change dramatically.”

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