2020 bashing has become the latest craze on TV and social media. Our Facebook, Twitter and even LinkedIn feeds are full of memes, quotes, and inspirational posts waving a happy goodbye to 2020 and happily welcoming 2021. 2020, in fact, was not a great year for the world. The COVID-19 pandemic ran wild, “stay at home” has become the most common pastime, face masks have become fashion and unemployment went to all-time highs.

It was an even stranger year for the tech world. The start of the pandemic stopped everything else. Investments were halted, corporate travel went down to zero, sales slowed down and the end of Q1 and beginning of Q2 left the business, finance, and tech world at a standstill.

Then, something extraordinary happened. Mid-pandemic, tech investments started to pick up again. IPOs continued trending and VCs ended up spending more in 2020 than they did in 2019 (according to research by CB Insights). This was mirrored within the businesses too. Even though trends shifted, and complete industries came to a halt, money was still being spent. Out went travel and retail; in went remote working tools, eCommerce, digital health and – most interestingly – data.

Setting the scene

In practice, data, and more specifically externally collected data (“alternative” or “3rd party”), is used for two major reasons.

BI (aka learning from the past) – Every aspect of the business uses external data to build charts, analyze trends, identify opportunities, and understand gaps and white spaces. Analytics platforms and BI tools offer off-the-shelf or ad hoc solutions that analyze large datasets to track anything from consumer and buyer behavior to drug use adherence or disease spread. These visualizations are used to extract insights and take actions.

Machine learning and advanced analytics (aka predicting the future) – Data scientists use data from the past in order to build complex models that help predict future behavior across a multitude of use cases.

Except – the past became irrelevant.

Imagine waking up at night and needing a glass of water. Your apartment is dark, and you don’t want to turn on the lights to avoid waking anyone up (especially yourself). You get out of bed, walk past the living room and into the kitchen, take a glass and pour yourself a cup. 5% vision, 95% visual memory.

Now, imagine that when you go to sleep, someone rearranges your furniture and swaps the glasses and plates around. Suddenly, you can’t trust your visual memory. You have to turn on the lights and reassess the situation. With the new input, you will be able to retrain your visual memory, and get back to sleep-walking in a matter of days.

COVID-19 put the whole world of data at a crossroads. ML models instantly stopped working, and BI and analytics stopped making sense. The world has changed overnight, industries collapsed against all odds and no past conclusions could have been used in an actionable way.

Large retailers, for example, have used ML models to predict sales and stock shortages based on date, time, day of week, previous purchases and many other parameters. Suddenly, their whole supply chain plan is halted because we don’t know what type of stay-at-home orders are in each specific state or region, and which stores can remain open.

Turning on the lights – Broad is the new deep

What do you do when you can’t count on your memory? You make assumptions based on every bit of information you can from the present. You turn on the lights, gather as much as possible, and use the new information to navigate through the new world.

On the wings of the COVID-19 crisis, companies have began expanding their horizons to collect and acquire as much data as possible to help them make sense of the situation. Financial institutions have expanded the search for alternative data, CPG and retail companies went on a hunt for any data that will help them decide when to open and how to deliver, and governments, institutes (academia, NGOs and others) and healthcare companies started sharing and collecting as much data as possible about the virus, its spread and government and personal reaction. Companies offering alternative data types such as foot traffic, web traffic, and live company and industry data were well positioned to help the business world understand how to react, and solutions for processing, enriching and translating this data to actionability are often sought out.

What’s next

Companies that made the right investment in data starting early on in the COVID-19 Crisis will come out of it with a much broader, better, and more accurate set of data to analyze in the future. As a data professional, how often have you looked at your company’s’ data and said to yourself: “This data is terrible, I wish I could go back and build the whole thing from scratch the way I want it”. Well, COVID is your reset button, and now is the time to start rebuilding. If you spent 2020 building up your data infrastructure and pairing it with the right external data, you will be winning 2021 and pioneering the way as the world goes COVID-free. If you haven’t – it’s not too late.