The COVID-19 pandemic has changed a lot of things in business, producing a new normal in which we all operate now and data analytics is no exception.
David Tareen, director of AI and analytics at SAS, announced, as businesses adjust to the new normal created by COVID, one of the main questions asked in the analysis is, how to recycle artificial intelligence (AI) models with a set of data more diverse.
Tareen said the pandemic had altered the integrity of the analytical data models that many companies had put in place. This has forced companies to redefine and recycle these models so that the analysis can take into account the new business and environmental conditions that the pandemic has brought.
In some cases, existing data models that were so reliable suddenly began to become so weak that they needed to be optimized. In other cases, companies lacked the data and applications to tackle the COVID crisis and had to find ways to get results. the required data and quickly develop new analysis models.
In one case, airports used predictive models to understand and improve aircraft traffic flow. What they found with the pandemic was that these models had to be retrained and additional data sources added before the models could begin to accurately predict the new normal traffic pattern that resulted from COVID.
In some cases, dealing with the COVID crisis had to quickly create new types of data and analytics applications. The city-state of Odisha in eastern India was in this situation.
Odisha wanted tools to measure the aggressiveness of the pandemic and determine how the pandemic was spreading. It also wanted analytics that could help it assess patient exposure in healthcare facilities like hospitals and clinics and how it could better manage quarantines, and other necessary measures to combat the advance of COVID-19.
The problem was that Odisha didn’t have the data or the tools to get the job done.
The problems on the pitch facing Odisha were critical. There were bottlenecks in mobilizing people and implementing infrastructure due to the strict rules in place to block the country. Logistics, road transport, trains, availability of police personnel and resources in many government departments were some of the main obstacles.
To help meet the challenge, Odisha hired SAS for a “ground floor” analysis project. Kunal Aman, Marketing Director at SAS India, confirmed, while the overall delivery of the project took four to six months, Odisha’s dashboard was built in just six weeks. Odisha used the scan to monitor virus transmission, infection rate and the availability of health infrastructure in the state.
What were the lessons from Odisha and the airports?
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You have to adapt to change
In every crisis (in this case COVID) the underlying assumptions and fundamentals of analytics can change radically and render them ineffective. Analytics keeps up with what is happening on site.
2. You may need to seek help
You may find yourself in a situation where you do not have the internal analytical tools or the experience to respond quickly to a crisis. In these cases, the assistance of an informed vendor or Advisor help.
3. Analytics is essential to the functioning of organizations
After all, the COVID crisis could well be the turning point that turned analytics into a business-critical skill. Without up-to-date analyzes that can report and update the response to incidents, there are few opportunities for companies to know at all times what is happening in their environment, how to assess risks or what to do.
In this way, COVID Analytics has transformed from a “nice to have” business capability into a “must have”.
