We have all experienced significant challenges affecting our personal lives, our businesses and even our planet. Some of these challenges blow over quickly and without much thought, while others—including unexpected pandemics, natural disasters, recessions and more—present major obstacles and outcomes that we struggle to cope with and overcome.
We rely on ourselves and one another to face the challenge, solve the problem and come out on the other side stronger and smarter than before.
Throughout history, analytics—or the practice of using data to gain insights—has been a key tool to guide us through turbulent times and present us with needed solutions.
When we consider the coronavirus, it’s important to reflect on how analytics has historically helped humans solve the world’s greatest challenges, spanning across countries, businesses, industries, and professions.
In the early days of modern medicine and epidemiology, data science was at the forefront of battling epidemics. Rewinding the clock back to the 1850s, epidemiology became a major field of study thanks to John Snow, who many consider to be the father of the profession. Snow was an obstetrician in London when the cholera pandemic struck, and the mortality rate rose to 23,000 individuals in London alone. At that time, no one knew the source of the disease and what was causing it to spread.
Snow geospatially analyzed where each infected person lived, and he quickly isolated the source of the issue to the Broad Street pump, a well that provided water to many residents. Presenting his analysis, he convinced the government to remove the handle of the pump, ending the spread of cholera in London.
Snow successfully used data science and careful analysis to get to the source of a pandemic—an extraordinary feat that ended up saving many lives. While it’s not up to any one of us as individuals to resolve the current pandemic we are facing, together, our collective and smart use of data science and analytics can help us get to more answers faster. Healthcare companies and government organizations are already using analytics to solve the challenges posed by COVID-19, as seen in the below scenarios:
Artificial Intelligence (AI) Powered Drug Discovery
Many pharmaceutical companies use AI technologies to analyze the chemical structure of drugs. This same technology is currently being used to identify existing drugs that could potentially be used to treat COVID-19, as well as to create new molecules for new vaccines.
This has even expanded to open-sourced hackathons, sponsored by health companies. As a result of competitions like these, several identified, potential treatments are now being evaluated.
GPS Tracking of Cellphones
Several countries have implemented smartphone applications to help manage the quarantine of individuals. In the case of China, cellphone data is reportedly being used to predict where potential outbreaks might happen next. By understanding who has contracted COVID-19 and looking at their prior movement based on their phone’s location services, it is possible to identify areas they have traveled to and more importantly, who else may have been exposed. Modeling this data, the Chinese government was able to predict which neighborhoods and cities would be at high risk, as well as who would benefit the most from a proactive quarantine. There is now discussion in the U.S. about leveraging this type of data as well.
In the business world, we see companies using data science and analytics platforms to quickly pivot and stabilize their routine business procedures as a response to the implications of COVID-19. Through their findings, they are shifting their priorities and reinventing processes, particularly in the below areas:
Supply Chain Optimization
While medical supply companies and government agencies use population density information along with current incident rates to predict which hospitals will have the highest demand, companies in other unrelated sectors are looking at their supply chains in a similar matter.
Analytically savvy businesses are analyzing the goods supplied from high-risk or quarantined areas to quickly identify pre-approved parts or material substitutions. From there, they can activate product or material redesigns. This is occurring in nearly every industry segment, specifically when it comes to analyzing food supply and parts for manufacturing companies.
Demand Shaping & Financial Forecasting
As inventory risks are identified, demand can be shaped with changes to offerings or discounts to help balance inventory. Combined with marketing optimization efforts, this strategy can be a powerful response to keep businesses moving forward during difficult times. Many companies have transitioned to analytically driven financial forecasting, with some leveraging broad top-of-funnel and economic indicators to help provide early warning of significant changes in their sales cycles. These can be challenging when historic precedents do not exist, but analytics can facilitate more informed decisions and prepare companies for the future.
Changing the Forecast
You may notice that in nearly all these examples, companies are using data science to make forecasts and predictions. However, the purpose of the forecast or prediction isn’t to simply understand the future—instead, it is to help change it.
Businesses that implement analytic solutions can change their trajectories going forward, rather than simply trying to make predictions about the future.
These are just a few ways that demonstrate how analytics can drive change, from determining the source of a pandemic to meeting business demands in the wake of a global crisis. History has shown how analytics can solve in a time of disruption, and today we have even more advanced data science and analytics technologies to accelerate our journey in getting to actionable insights.
The pandemic we face today is forcing us—as people and as businesses—to respond to major changes in our day-to-day lives, and analytics is at the heart of efficient and effective reaction. I challenge everyone to use data science to solve the personal, business and societal issues we are all up against.
Editor’s note: Alan Jacobson last May joined Irvine-based Alteryx Inc. (NYSE: AYX) as chief data and analytics officer. Jacobson was the former director of global analytics at Ford Motor Co.