Risk has always been part of supply chain. And as supply chains become even more global, risk factors increase too.
In this current environment of never normal, a strong risk management strategy provides businesses with a competitive advantage. Existing supply chain data enable us to take a closer look at risk factors.
How does supply chain risk management create value?
Effective risk management brings important benefits. It enables robust and flexible business operations while preventing costs and other negative effects, like damages to brand image. It provides greater transparency over dependencies and risks in networks. Additionally, businesses can react more quickly to risks when they have plans in place.
Despite the benefits, many businesses still don’t have risk management strategies. Especially medium-sized businesses tend to leave themselves vulnerable to potential risks.
Uncontrollable and inherent supply chain risks
Supply chain risks fall into two categories.
The first are uncontrollable risks, which generally have their source outside of the scope of supply chain operations. Examples include the energy crisis in Europe, strict lockdowns in China and the blockage of the Suez Canal a few years ago. These are often events with a global impact that are hard to predict and have low probability of happening.
The second category are inherent risks, which are related to normal supply chain operations. Inherent risks result from technical errors or market developments, for instance, and could include warehouse blackouts, lack of freight capacities or supplier defaults. These risks are common instances in supply chain management and much easier to predict, prepare for and mitigate.
Both categories must be reflected in a risk management strategy.
A four-step approach to risk management
Knowing the importance of risk management and the kinds of risk to watch out for, businesses can begin to develop a plan. 4flow recommends a four-step approach.
![[Translate to US – English:] 4flow recommends a continuous four-step approach to risk management](/fileadmin/_processed_/0/e/csm_4flow-risk-management_324f3588d5.png "[Translate to US – English:] 4flow recommends a continuous four-step approach to risk management")
Identify supply chain risks
By drawing on internal and external data sources, businesses can identify potential risks along the supply chain, both inherent and uncontrollable.
As a first step, businesses should use data from sources they already have access to, such as transportation data to identify shippers or shipping routes, or material data to determine countries of origin or manufacturers. 4flow also supports businesses with its own benchmarks, access to public databases, data crawling methods and more to enhance the data pool.
Analyze
This step involves analyzing and classifying identified risks in terms of probability and impact on the business.
Broadly speaking, risks are clustered into three areas. For high-impact, high-probability risks, businesses need to consider long-term investment strategies, for instance in specific risk management tools or insurance. For risks with moderate impact or moderate probability, businesses should improve their situation by weighing the costs and benefits of risk mitigation measures and prioritizing those with the greatest impact. Finally, low-impact, low-probability risks can be accepted if the potential threat is less than the expected benefits of risk prevention.
Interpret
It is key to mitigate potential risks by developing both proactive and reactive response strategies in line with the business’s risk tolerance.
Response strategies are based on the impact and probability determined in step two during the analysis. Investment strategies could include implementing real-time risk monitoring software or obtaining specified insurance. Improvement measures such as multisourcing, analyzing business intelligence data, creating capacity buffers or segmenting the supply chain for greater flexibility could be appropriate to mitigate certain risks.
Integrate
As a final step, integrate the identified measures in daily business and monitor their effectiveness against risks in your supply chain.
To ensure sustainable results, this four-step process must be performed continuously. As supply chain networks constantly change, businesses need to quickly identify and act on new potential risks and improve existing risk management strategies.
Data science adds value to risk management processes
Data gives a clear view of risk factors and enables risk forecasting. This is especially useful when working with inherent supply chain risks, which occur more frequently. Considering historical data, such as rates of on-time deliveries for each component or carrier, and external data like weather or traffic information, we can predict risks along the supply chain using machine learning. Historical market data and economic indexes, for instance, form a basis for demand forecasts and reveal risks related to market factors.
Even small amounts of data, such as lists of suppliers, can provide surprising insights. For example: many businesses have turned to multisourcing as a strategy to avoid becoming dependent on one supplier for critical components. Data can reveal a more complete picture. If all suppliers use the same hub, for instance, or all carriers go through a critical point like the Suez Canal, it is important to recognize your business’s reliance on given infrastructure early before an unexpected event puts production at risk.
Furthermore, data enables simulations. Particularly helpful when considering uncontrollable risks, simulations help businesses understand what could happen in a given risk scenario. Computers can model ripple effects based on data far more accurately than people can predict.
In turn, these data insights empower businesses to make their supply chains more agile – by adjusting their network structure, monitoring significant risks and creating plans for emergencies.
![[Translate to US – English:] Data science approaches support identification and mitigation of supply chain risks](/fileadmin/_processed_/0/b/csm_4flow-data-science-approaches_4fdc63ad17.png "[Translate to US – English:] Data science approaches support identification and mitigation of supply chain risks")
Authors
Maximilian Brüwer
Manager
4flow consulting
Holger Clasing
Vice President and Head of Strategy Practice
4flow consulting
Dr. Laura Gellert
Manager of the Data Science Team
4flow consulting