COVID-19 Impact on Data & Analytics
Why Everyone's Data and Analytics Strategy Just Blew Up

The COVID-19 pandemic is impacting data and analytics strategies in profound ways.

Experts explain what your company should be doing right now.

Companies should be adjusting their data and analytics strategies to better align with market realities as they unfold.

Regardless of whether businesses have been shut down or they're operating above or below their normal capacity, every company's data and analytics strategy has been impacted because the underlying data has changed. Customer behavior has changed, supply chain behavior has changed, company operations have changed. If your data and analytics strategy isn't keeping up with what's happening, then you have important work to do, quickly.

Predictive analytics took a hit: "Data scientists like to talk about the concept of data drift, and typically that happens over time," said Brandon Purcell, principal analyst at Forrester. "That process just accelerated and now companies have to start collecting new data and creating new models based on the data from the point when folks started sheltering in place."

It's important to track how customer behavior is changing because it will continue to shift, perhaps radically, depending on several factors such as when the executive orders expire and whether those customers still have jobs or not.

Instead of relying on predictive models, Purcell said it's important to do descriptive analyses of customer journeys and the volume of customers going on different journeys. Pay close attention to whether a journey is functioning properly and if not, fix it quickly.

Big data has holes: Businesses have collected a lot of data on customers and their own internal operations, but the patterns of just a few weeks ago don't reflect what's happening now. Erick Brethenoux, VP analyst at Gartner said companies shouldn't overlook small data techniques.

"Because we have cloud and GPUs, people forgot there's a lot you can do with small data, so small data is coming to the forefront with a vengeance," said Brethenoux.

He also said knowledge graphs are making a comeback because they capture relationships in addition to facts.

Your own data isn't enough: "This crisis is drawing attention to the lack of external data that organizations have available to them in a consumable way. [Third-party data] can be used for input into the forecasting models to help them forecast, not just using their own ERP POS data like they always have and the historical data, but also looking at the external and exogenous kind of data and signals that are absolutely necessary in the kind of space we're in right now," said Traci Gusher, principal of Innovation and Enterprise Solutions, Data & Analytics at KPMG.

Your data pipeline may be incomplete: Businesses are discovering that they're ill prepared to deal with present circumstances because their data pipeline is incomplete. They lack data or the data they have is unreliable.

Up until recently, it might have been fine to build a data pipeline one section at a time using different data engineers for data connections, data accumulation, master data management, data enrichment, and data packaged for consumption. However, given the current state of rapid change, the need for speed will cause organizations to automate what was previously done manually using intelligent technologies.

Bottom line: Circumstances have changed radically, and they're going to continue to change, often, over the coming weeks and months. In response, data teams should endeavor to become more agile so they can adapt their data and analytics strategy faster and easier.