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Risk Management in Logistics: Secure Supply Chain by Data

Risikomanagement in der Logistik: Sichere Lieferkette durch Daten

Identifying risks, opportunities, and crises before they arise – futurologists, market and trend researchers, and pollsters are aware of the future's potential and the way to deal with it. Predicting the future precisely, which may seem impossible, is nonetheless achievable if given the right tools. This allows for long-term planning – and unforeseeable events are also anticipated. That is what we call resilience.

Logistics is a unique industry: for example, a six-day blockade of a canal in Egypt – the Suez Canal – can lead to a global disruption of freight traffic worth more than nine billion US dollars – per day! Like interlocking gears, the dependence of individual supply chains on specific events in the world is immense. A transport of goods within Germany, for instance, can be obstructed only by a simple port closure in China. Due to this sensitive dependency on external factors, it is essential to keep a watchful eye on risks and events in the world and to provide plans for unexpected crises in order to minimize their impact on supply chains.

Risk Management in Logistics: What's the Need?

The current situation for logistics is critical: after reducing capacities and resources during the past pandemic lockdowns, we have now been experiencing a renewed increase in demand on the world markets for some time. However, companies are presently unable to meet this demand to any great extent. The lack of truck drivers, limited container capacity, and congestion at international ports are just three of the many reasons currently causing a standstill in production and transportation of goods. Temporary closures of companies along the supply chain due to the pandemic further complicate the situation.

Even though the present global crisis may be exceptional, temporary and/or local shortages and disruptions in the supply chain can happen again and again – after all, this was already occurring before the pandemic and will continue to do so in the future. Those who detect critical situations at an early stage, carry out risk planning, and are thus able to respond with appropriate measures, can not only keep losses low, but can also plan for the long term with a sense of security.

Supply Chain Risk Management

Back in 2012, Deutsche Post DHL Group developed and launched an innovative cloud-based solution called "Resilience360". It visualizes the global supply chain of companies and thus enables real-time monitoring and assessment of risks. The solution integrates with customers’ procurement, logistics and business continuity platforms to provide global end-to-end-visibility into supply chains.

The uniqueness of the solution is the combination of Data Science, proprietary intelligence paired with human brain power to monitor global risks in real-time, which empowers customers to take informed supply chain decisions to be prepared for or actively avert potential disruptions.

With an average more than 1.000 global relevant (validated and risk impact assessed by humans) supply chain disruptive incidents identified daily, the solution ensures continuity in day-to-day business to keep the supply chain stable, and hence to stay one step ahead of the competition.

Therefore, the topics of transformation and crisis management were already of great significance for the Group well before the Corona pandemic, and thus also for DHL Freight. Resilience is the very foundation of establishing reliable logistics for businesses of all kinds and one of the mainstays of supply chain design. “Resilience360” operates today under the name Everstream Analytics – more than 250 companies with global supply chains trust this innovative company.

Logistics Data for Greater Stability in the Supply Chain

By analyzing the historical and current market and by considering future scenarios, you can develop concrete visions of the future – and in doing so identify potentials and risks early on. Although such assessments are never 100 percent reliable, they do increase planning security. Thus, the key to the future and its prediction is to be found in data and facts from the past and present. 

With the help of such data, conclusions can be drawn about various future opportunities – which can be further developed into specific measures to influence the future positively. Today, the most prominent example for predicting future events is probably climate change and its impact on our planet. Just like in this meteorological scenario, risk management in logistics can also be conducted by collecting and evaluating data. The relevant data is first collated in data mining, and then, in data mapping, it is allocated to the different subject areas, reconciled, and further processed into reliable findings. On this foundation, the next operational steps can be taken.

Supply Chain Management with Machine Learning

Based on the data collected, risks to the company's supply chain are now being determined. This makes it possible to identify the links in the supply chain whose resilience needs to be increased. How can the company react if the risk turns into an actual disruption? Which backup plan can be prepared beforehand to enable the company to respond quickly and maintain the supply chain if the worst comes to the worst? 

Algorithms for machine learning, using millions of pieces of data to learn from and make forecasts for the future, can support risk detection. These algorithms are constantly screening countless data streams from every country in the world and tracking just about every logistically relevant event on our planet. Everstream Analytics, for example, as the world's largest network for identifying supply chain risks, reduces response times and costs for companies to prevent and manage supply chain issues. From all this data and insight, concrete recommendations for action are derived. These include automated workflows triggered by specific events, connections to internal and external collaboration tools, and finally direct coordination with the company – here, all intuitive processes come together, resulting from decades of experience in solving logistical crises.

Conclusion

Experience and foresight are crucial for reliable logistics. Only by this, the correct decision can be made quickly in case of deviations in the delivery process. Companies such as Everstream Analytics create the necessary data basis and, with the help of machine learning algorithms, advice can be given that companies can rely on at any time – not only in times of crisis.

As a dependable partner and pioneer, DHL Freight has for years consistently relied on cooperation with specialists who help minimize risks for companies, optimize the predictability of their logistics, and prepare them for critical situations.

For more information about Everstream Analytics, please contact the following e-mail address: DHLrequest@everstream.ai

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