Hope For The Best And Plan For The Worst should be a consistent and shared mantra for all businesses as a means to focus on strategic risk management. The importance of this has increased to the highest level as a result of the COVID-19 pandemic and the activities to both recover and prepare for the next disruption. This requires a significant investment in strategic risk mitigation definition and development and must include partner risk management in the scenario development and risk mitigation strategy. This includes all partners and integrations in the extended supply chain. The weakest link in the supply chain will continuously change depending on the type of disruption and your strategic risk scenarios must be developed to define a response for all scenarios.
One critical activity, or requirement, is implementing a regular risk scenario review process that evaluates the likelihood of scenarios and most importantly, new scenarios. As we have seen from the many disruptions experienced so far this year risk scenarios and potential changes continuously with new risks rising and other risks declining and disappearing. You will never in a million years be able to identify all risks, and the point is that a regular review process provides the means to review so that you can add and remove scenarios as necessary.
The next activity is developing and implementing the appropriate data analytics capabilities that will support the ability to sense the reactions to disruptions and most importantly, the reaction to combinations of disruptions. The risk scenarios must identify the reactions to combinations of disruptions and then you must have a means to measure the responses. This is where data analytics comes into play, along with a healthy helping of imagination. Different disruptions and combinations of disruptions will cause different reactions in the supply chain and these reactions must be identified quickly in order to determine the appropriate response. The risk scenario identification and evaluation is important but it is based on assumptions and personal viewpoints of the team that developed the scenarios. Data analytics brings the facts to the table to help to determine the appropriate response.
The glue that connects these processes and activities is imagination. Risk scenarios require imagination to create, risk response exercises require imagination to develop, data analytics requires imagination to develop the queries and identify the appropriate data and source to identify the reaction to the disruption and then to validate the effectiveness of the response. As you can imagine, this is not a ‘once-and-done’ exercise. This requires continuous review and evaluation in order to grow and evolve with the market and the supply chain. Each disruption and reaction to the disruption creates a new reality stream that changes scenarios and potential for disruption and it is important to continuously evaluate and develop new scenarios.
Data analytics is a very nebulous practice that requires continuous experimentation and evaluation to validate assumptions. The data analytics initially produces the outcome reaction to disruption and combinations. This is only the start, however, because after identification of the outcome you must then try to trace back the results through the responses and combination of responses if you want to tie them back to a particular disruption. I’m not sure that it is critical to tie everything back to a specific disruption though. The point of this whole exercise is to identify a reaction to mitigate the specific business disruption that has occurred and this should be the initial focus. After the mitigation exercise you will need to go back and evaluate the actions that resulted in the disruption on another day.
Tom Brouillette
Contact: tbrouillette@ncspartners.com
@ncspartners
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