COVID-19 is a rare bird – in many ways a black swan. Scholar Nassim Nicholas Taleb in his book The Black Swan described these types of unpredictable global occurrences that shatter and then reshape society. When we review these events in hindsight, we try to rationalize and assert that the pandemic was wholly predictable – if only we had the relevant data, we tell ourselves.
We don’t want to believe in the unpredictability of these events. But they happen regularly, and we are almost always caught off guard. As we have been by this pandemic. But there is something we can do and that is build resilience.
Resilience is about being prepared for the future in whatever form it might take. Organizations, public and private, routinely do this by creating business continuity and disaster recovery plans. These plans can range in scope and complexity, but their primary goal is to keep the organization functioning (at some level) until the crisis passes. Hopefully, the current crisis passes quickly even though it may take weeks or months for operations to return to normal.
And sometimes your resiliency will be tested not by a black swan event, but by things such as economic downturns, technology disruptions, or societal upheavals that happen on a more regular basis. Maintaining situational awareness is an important way in which organizations can become more attuned to the precursors for these types of events. But this is just one way that organizations can build resiliency.
What being resilient means
To be truly resilient an organization must have the ability and the capabilities to carry on despite unpredictable events. Bad things will happen, but it’s how we react to them that makes the difference.
Resilience requires a capacity to move with speed and agility and to marshal resources including people, operational processes and your organizational infrastructure.
One important way to weather a crisis is by embedding data and analytics in your decision-making processes so they become a natural part of your resiliency-building efforts. Analytics can be used in a variety of ways from predicting demand for goods, materials and services to quickly assessing multiple risk factors to maintain financial solvency to keep your supply chain moving.
Most organizations have an abundance of data that can help shape and target their crisis response. Your data will play a big role in enabling you to resume operations as quickly as possible. Without data, you cannot determine what is needed, where you should focus your efforts nor be alert to the indicators that a crisis is waning.
The decisions you make during a crisis event help or hurt your organization. Using your analytical resources to make fast, insightful decisions gives you the confidence that you’re making the right ones. To bolster your stress-hardiness with analytics just makes good sense.
Find COVID-19 answers with data and analytics
Read more about how SAS has helped all types of organizations respond with agility, recover effectively and reimagine the future with analytics and AI.
Build resilience from experience
Your trove of historical data can be sourced among insights into your recovery speed from different events. These insights can help identify weak points in processes, teams that need additional resources, missing strategy and the list goes on.
Resilience in the moment
An important attribute of a resilient organization is understanding the normal ebb and flow, growth and shrinkage or the demands on your organization whether you’re a government agency, a health care provider, a retailer or a manufacturer.AI models built with machine-learning algorithms can be your canary in the coal mine, the early warning system to help identify looming crises or at least their early stages. You can build and maintain machine- learning models that can look for signals of disruption in your data can trigger alerts that a situation needs to be monitored more closely.
The potential of using analytics to help organization-building resiliency is enormous. For example, a bank might use an AI model to monitor current data and compare it to historical data on an ongoing basis and automatically send an alert when conditions mimic a past crisis.
Another key measure of resilience is how quickly an organization can recover from a significant event. The speed at which you can bounce back from disruptions, big and small, is an important metric for your organization because duration correlates with magnitude of negative impact.
And with solutions in place to clean, govern and safeguard your data for analytical processes, every strategic or tactical decision made in your organization can be made with the kind of confidence that builds resilience.
Analytics can guide you to a more resilient future
Determining how to better prepare for the next crisis is likely at top of mind for leaders of all organizations right now. Some of the most important answers will be found in your data because data is what all digital processes produce. And with solutions in place to clean, govern and safeguard your data for analytical processes, every strategic or tactical decision made in your organization can be made with the kind of confidence that builds resilience.
Scenario analysis is just one way that organizations can start creating agile, anticipatory strategies for dealing with upheavals. There are many types of scenario analyses, but the most effective ones are grounded in analytics because analytics and AI models give you more accurate foresight in your crisis-strategy planning and the evaluation speed you also need in the moments following the landing of the next black swan.
This article originally appeared on the Global Business Barometer, published by The Economist Group.
- Unemployment fraud meets analytics: Battle lines are clearly drawnMany fraudsters seized opportunities presented by the COVID-19 pandemic. During the crisis, unemployment fraud became a battleground between international criminal networks and government agencies. Learn how analytics can save billions – and deliver benefits to those truly in need.
- AI in government: The path to adoption and deploymentThe government sector is lagging in AI adoption, but awareness of the importance of AI in the public sector is increasing. Our survey indicates that operational issues are requiring governments to turn their attention to AI projects as a way to address important public issues.
- AI in manufacturing: New opportunities for IT and operationsAn AI survey reveals that leaders and early adopters in AI are making important advances and are identifying and expanding on what works as they use AI in more ways and more parts of their organizations.