Every business and organisation in the world is currently assessing the impacts of coronavirus (COVID-19) on their operations and as they do, common questions are being raised.
In so much of our business world and reporting we still only look at each risk individually and in the traditional two dimensions of likelihood and severity of a risk impact. We should however recognise, model and consider various scenarios that the cumulative effects of interconnected risks or an event may have on our businesses – with a far greater consequence in aggregate.
The current COVID-19 challenges, apart from the obvious and serious health impacts, have at a high level clearly shown how social distancing rules have impacted revenue and supply chains. The ability to be agile and work digitally and, in many cases, remotely has a direct flow-on to the success with which a business may be able to manage through, and recover from, the current crisis. Understanding how the various risks connect to an event that businesses manage is inherently understood – but not how those risks are reported on, and then managed. The traditional approach also ignores the critical factor of the speed or velocity with which each risk or connected risks (the event) may impact businesses and the operating environment.
The four dimensions of risk should be considered – likelihood, impact, velocity and connectivity, not just the traditional two. By taking a four, rather than two, dimensional approach it’s easier to assess the ‘contagion’ effect of risk and identify the events that are most likely, and the scenarios to be preparing to mitigate, manage and recover from. Utilising tools such as network theory allows businesses to bring connected risks together to identify the relevant events.
In a period of exceptional volatility, like the current one, seemingly disparate events can become inextricably linked.
Network theory, put simply is the study of the representation of the relationship between discrete objects. Network optimisation, as a tool, allows for businesses to understand these relationships and as a result, manage a range of complex problems across networks of risks and opportunities, ranging from social spread of news and rumours, innovation and electrical networks as examples. Network theory/optimisation helps in identifying the shortest path across these networks, understanding the strength of contagion across risks, the most centrally connected risk and the velocity of these risks. It identifies the way businesses have to move. And fast.
Consider the current COVID-19 situation as an example. A business should try to understand the:
In understanding these impacts, business can be in a place to make better decisions and identify areas of prioritisation in terms of further risk mitigation and the opportunities for recovery that can be made. Understanding the most likely events that would impact the business and modelling the risk events in advance is obviously the preferred approach. Those that do this best will no doubt have a competitive advantage and be the more sustainable entities.
These network theory/optimisation tools are relevant right now – connecting the dots of the risks facing a business is key to working out what should be focused on. This will help mitigate further risk. Businesses should be looking at all aspects of their operations from a connected network perspective.
Understanding the answers to these questions and defining scenarios based upon connected risk events, allows for stress testing business resilience and risk mitigation within the COVID-19 environment. It will allow leaders to proactively challenge strategic responses using the insights generated from network theory.
As we all progress through this crisis, this approach can be used to understand what the new risks and challenges are. And finally these tools can be used to look at what are the longer-term trends facing a business, post-crisis.
It is not too late to better understand the continuing coronavirus challenges, connectivity and impact of COVID-19 risks to your business.
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