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Analytics has been a key enabler for businesses in the past few years. We have seen the entire world shift from process-driven to data-driven decision-making. And now that we are standing at the brink of a new normal amidst these unprecedented times, the usage of data and analytics should act as our guide to the post-COVID-19 era.
As businesses have started opening up after months of rigorous lockdown, the early trends show an increased use of data and insights in monitoring and planning for a post-pandemic environment. From determining the markets and stress testing business models to planning supplies, organizations are leveraging data in more and more ways.
While the adoption of data-based decisions was expected to pick up, the current crisis has pushed it to another level. One significant trend that has emerged is the usage of analytics by governments across the globe to monitor and manage the COVID-19 situation by collating data from hospitals and patients. Data Science has enabled real-time monitoring of all the active cases in a particular country/area, which helps citizens locate their nearest hotspots. On the other side, this also helps patients locate their nearest hospital/medical center where testing/treatment is available.
Governments are using analytics to create heat maps for the spread of COVID-19 in different areas in order to plan for the reopening of counties and cities. These same heat maps are being used by organizations worldwide to assess the situation of different markets for reopening. The healthcare industry is using analytics to manage and maintain the supplies of masks, PPE kits, and ventilators, while the retail sector is using analytics to categorize essential and non-essential products and using forecast studios to predict demand, inventory, etc.
In reviewing the reopening journey of multiple businesses, there are a few factors that stand out as being the most important.
First and foremost, the primary goal of businesses as they reopen should be to continue in a manner of business as usual (BAU). Businesses need to be aware of the following implications:
- Operations strategy needs to be as agile as possible in the new normal which will require real-time data on virus spread
- Employee safety needs to be of utmost importance — safety measures should be put into place in the office environment, and this should include face mask requirements, temperature measurement, and maintaining the appropriate social distancing — all areas where data and analytics will play a major role again
Stress testing could serve as a make or break strategy for organizations in the near future as businesses endeavor to keep the lights on during these difficult times. It will require a lot of data and insights to stress test business models in various markets. COVID-19 has been the black swan event that has put the sustainability of many organizations at risk, and there are numerous organizations that are undergoing financial stress due to high leverage. Analytics models have already been around for stress testing, but the adoption remained a challenge. In a post-crisis world, the adoption of these models will increase by leaps and bounds.
- Resilience: As per IMF projections, the global economy will contract by 3 percent in 2020, a bigger downturn than in the 2008–2009 financial crisis. In such a scenario, organizations have to come up with new models to sustain this economic contraction. In this new normal, manufacturers will not only focus on their supply chain but also on their supplier’s supply chain to assure robust fulfillment. In a post-pandemic world, organizations will require a lot of data crunching in order to provide forecasts, predictions, and simulations.
Within the new normal, organizations will have to be very agile with their offerings as most of them will be digitized. Feedback data will play a very vital role in getting their finger on the pulse of the consumer around them.
Organizations must ensure their approach is agile, so they’re capable of responding to change. Organizations need to get down to the SKUs level and focus on demand and profitability. Products with high demand and high profitability will stand out in these times.
C-suite executives will require data to identify which markets are impacted the most and the level of impact in those areas. They will also need to see different scenarios of what this new normal will look like. Rigorous stress testing would be required to be confident in the way the business will run moving forward. Machine learning (ML) models could also play a significant role in stress testing.
Review Business Models
With a new normal to adjust to, organizations need to review their business models. They can use the following steps (outlined in the image below) to assess their current models and develop new ones.
In each of these steps, data and insights play a vital role. Whether it is about creating simulations, looking at different opportunities, or simulating the right business models with those opportunities, all of these steps will require the right data.