The COVID-19 pandemic’s rapid global spread brought business as usual to a screeching halt. Social distancing measures, essential to slowing the spread of the disease, compelled many organizations to alter their operations and/or rethink how they do business.
The pandemic’s velocity initially caused many businesses to transition into reactionary response mode as new information and government actions materialized. The immediate need for changes, including the introduction or scaling up of remote working, posed a time-sensitive challenge for effective strategic planning.
As the pandemic continues, senior leaders face growing uncertainty, and the volume of information and decisions they must make complicates the most pressing risks. This is compounded by complex questions — including about the length of the crisis, whether there will be a lull during the summer, the economic impact, and the threat of a second wave — that remain insufficiently answered.
Simply put, the pandemic demands that corporate leaders use a data-based strategy to rethink the ways in which we define, measure, and manage enterprise risk.
Moving From Anecdotal Evidence to Data-Based Decision-Making
Although compounding events and limited data drove many organizations’ early pandemic decisions, it is now possible to take a step back and think more strategically about the path forward using data-based insights.
With the availability of pandemic related data and modeling tools, data-based insights can replace anecdotal evidence to determine the next steps in an organization’s pandemic response, recovery, and resilience. Data-based insights are instrumental in formulating the questions that senior leaders will need to answer to build an effective organizational roadmap and anticipating – and overcoming – potential hurdles along the way.
A variety of tools and models can help businesses monitor the current situation and create forward-looking forecasts to support decision-making on multiple issues, including worker safety and well-being, the ability to serve clients, and changes within the supply chain. To optimize their decision-making capacity within various parameters, organizations should look at a number of metrics, including:
- Measurement of risk aggregation and interdependencies across the value chain, which can help risk professionals and others understand the degree of contingent business interruption risk present across the enterprise.
- Resilience metrics, specifically those that will help determine how much stress an organization can withstand and at what points in the value chain.
- Early warnings crisis event metrics can provide barometers for early decision paths, and provide guidance for navigating a crisis during its initial days.
- Metrics on essential supply chain partners to help evaluate counterparty risk.
Businesses should remain vigilant by identifying scenarios that will require action while creating a clear path forward for each eventuality. That way, when data indicates a potential problem, the organization’s preplanned decision can lead to swift action.
Data-Based Insights in Action
One area in which organizations can benefit from data-based insights is in making return-to-work decisions, which should be built on a thorough understanding of probable and potential risks. The decision to bring employees back to a physical workplace hinges largely on when and how individual states lift restrictions. Still, businesses should build timelines based on their needs. Organizations whose employees can effectively work remotely might want to continue this practice, but the decision will be more complicated for businesses that require workers to be on site. These organizations will need to weigh the risk they may assume by allowing employees to resume working in close proximity.
Data can be instrumental to quickly identifying potential infection trends within the workforce, allowing some agility in taking action. For example, a business leader might need to flag an increase in sick days among a cohort of employees, especially ones that work closely together, to determine whether to take steps to protect others.
Consider All Possibilities
It can be overwhelming to think of all the paths the pandemic might take moving forward, and how each may affect the business. During such an unprecedented time, it can be tempting to focus on near-term decisions, but extra thought should be dedicated to long-term solutions.
Recovery will depend on the peak period of the pandemic in varying locations, and decisions will need to consider operational risks, brand reputation, and potential legal liabilities, among other challenges. Risk professionals and others should leverage data to shape their long-term strategic decisions in a prioritized and organized manner.
As different parts of the country start their journey to recovery, businesses will need to analyze the pandemic’s effect on several variables. For example, even after restrictions are lifted, will clients need or want a particular product or service? How will client confidence differ across geographic regions? What will supply chains look like at various points during the recovery process and beyond?
Pandemic modeling data should be integrated with client sentiment analysis to understand critical decision paths and create a clearer picture of short- and long-term operating needs. For example, a manufacturer might recognize the need to ramp up the production of specific goods while slowing the production of others.
Balance Efficiency and Resilience
Recovering from the effects of the pandemic will require a shift from traditional resilience measures that focus on enduring and/or evolving risks. For many organizations, the ability to identify, access, run, and use the data from models and databases may not exist in-house. The starting point is to determine what is essential to resilience: Is it a specific product, employee or team, supplier, business function, client or group of clients, geography, or something else? Although tackling multiple risks can be challenging, organizations should ensure that they are considering all possible options.
Additionally, organizations will need to analyze their operating models and consider potential changes that concentrate on resilience in the face of unexpected challenges. Many organizations have historically focused on building efficient processes, but should transition adopting these actions to withstand effects of the pandemic. As part of their long-term plans, it’s essential for businesses to think through scenarios and stress test both the resilience and efficiency of their operations.
Forecasting Enables Agility
Forecasting mechanisms can help organizations map out when to raise alarms and enact changes. As they start the road back to normality, organizations should keep in mind epidemiologists’ warnings that a second wave of the coronavirus — along with seasonal influenza — will likely hit later in the year, possibly leading to the reinstatement of social distancing measures.
Without a clear picture of the future, businesses must prepare for different scenarios, ranging from best-case to worst-case outcomes and multiple points in between. Scenario-based stress testing methodologies allow organizations to evaluate different response plans and potential shocks across their value chain. These exercises should focus on an organization’s most at-risk areas and on non-correlated factors that can create disruptive forces and complicate recovery. Organizations can use these tests to evaluate risk capital investments — including the tradeoff between resilience and efficiency — to determine the potential return on investment for various measures and activities.
The growing complexity and accelerating nature of the COVID-19 pandemic highlights the need for businesses to learn from each other to avoid the same mistakes while emulating successes. Sharing data and insights, either directly or through a common partner, can help organizations become more agile in their decision-making and aid in the recovery process.
