COVID-19 Effects the Data Analytics Strategies
- May 16, 2021
- Posted by: Aanchal Iyer
- Category: Big Data Analytics
Times of crisis and doubt create unique opportunities and options for those who are pragmatic and open-minded. The COVID-19 effects strengthened and reinforced the value proposition for data, as the realization that we were flying in the dark set in and the need to become insights- and data-driven became apparent. Since the world is in recovery and reset mode, it is now time to put aside conventional thinking, reflect and understand the recent challenges and transformations, and chalk out a detailed strategy that makes data work as an organizational asset.
COVID-19 Effects on Organizations
With organizations now increasingly dependent on models/analytics to frame their course through an ever-changing world, these sudden shifts have highlighted a key reality – models/analytics and the data that organizations depend on are “perishable.” Rigidity needs to be replaced by flexibility. Thus, organizations have to constantly update models, get access to modern and new data, and adjust quickly and efficiently to the changing events. If not done, these organizations are at risk of making decisions based on outdated and invalid projections. The breath-taking speed and scale of the COVID-19 pandemic have put incredible levels of stress on models/analytics. They have also created challenges to the process of ensuring that the data models/analytics to be applied are updated, safe, and secure. This has become more problematic as organizations need to examine a growing range of data to keep track of fluctuating business conditions, and also safeguard data that is being created and shared by a large number of employees working remotely.
Outside factors are now instigating and triggering a significant disruption and internal data about previous activities are no longer a good indicator about the future. Thus, organizations are now turning outside to understand what is going on, specifically with respect to consumer behaviour and demand. This is a lasting and a positive change as it is important for an organization to be connected with the outside world. However, organizations need to quickly and efficiently adapt to incorporating external data.
Another major impact of the COVID-19 pandemic has been analytics professionals being asked to predict the impact of the pandemic on the business and to do that, one has to understand what is happening with the pandemic. This is what an epidemiologist does; thus, data professionals are actually behaving as epidemiologists.
Companies are also now trying to generate disaster models. While last year has produced a lot of unusual information, organizations should not erase this data. There will be pandemics and disasters of other kinds, so this data will be useful then.
Updating Models and Data for a Post-COVID-19 World
A significant number of organizations have initiated steps to redesign their approach towards analytics. In a changing world, these types of efforts pay off – and often do so quickly. For example, a popular convenience store chain adjusted its data and analytics to precisely identify the products which sold the fastest in its stores during the pandemic. This enabled the retailer to proactively take steps to ensure that it had those fastest-selling goods in stock; thus, enabling customers to purchase them easily. Eventually, there was an increase in per-customer purchases of those products of about 25%.
Conclusion
Data professionals in some industries were hit hard by the pandemic, but hiring in organizations and industries that are now prospering has made up for the downtime. An organization’s probability of solidifying its data analytics program in spite of the recession depends on whether the organization has already seen a Return on Investment (ROI) in its analytics programs. In uncertain times analytics and data science are probably the most stable.