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What The Data & Information Overload of COVID-19 Has Taught Me

As I am trying to keep up with the volume and complexity of data and information surrounding COVID-19, it dawned on me there might be a parallel to the challenge those who are less data savvy face when meeting many data and analytics professionals. This thought started, with all honesty, as a feeling – the feeling that I was failing to understand something so essential to me. I wondered, if some folks who know that data is essential to improving their understanding of their business, but not much more than that, might feel similarly overwhelmed.

My first thought is that not knowing something is scary and I don’t like it, at all. And while the consequences of not understanding COVID-19 are more frightening and consequential than, say not understanding what a random forest model does, not knowing anything is both scary and frustrating. This leads me to the first lesson that can be more strongly applied in the interaction between knowledgeable analytics professionals and less knowledgeable business leaders. Empathy – starting with an understanding that someone might lack the knowledge you have or have different knowledge, or feelings or experiences. I recall meeting an analytics leader further along in the journey of analytics than I was when I started my role leading analytics at IKEA. This wise leader encouraged me to get good at hugging people (at a time when that was ok) and letting them know that things might change, but it would be ok. Analytics did not need to frighten them. At the time, I found it endearing and useful, in retrospect it was amazingly good advice.

My second thought was surely this must not be as complicated as people are making it out to be, and this led me to look more toward images than text and numbers. Visualization can sometimes be short-changed in advanced analytics, as if, that’s a “BI thing.” This is wrong on a lot of levels, but my belief is that it’s wrong because it takes away a means to increase understanding, and that is a critical part of analytics. Even if you cannot explain the math behind the AI that is extrapolating what will happen with COVID-19, the visualization makes it clear what the outcome of the AI means to the viewer, in this case the value of social distancing.

Finally, in chaotic times especially, agreeing to and sticking to a common definition is essential for understanding. While coronavirus is commonly used, it’s not the agreed definition of the current pandemic. In this case so many new words are used, a dynamic glossary is needed. And when new analytics techniques or terms around data are launched into an organization, there’s no reason to assume you shouldn’t do the same.

I am happy for the chance to share these thoughts, and honored you took the chance to read them – a few last thoughts; be well, be kind, we’re in this together, and together we will get through it.

Drew Smith is the Executive Director for IIA’s Analytics Leadership Consortium (ALC) and has been with IIA since June 2019. The ALC is a closed network of senior analytics executives from diverse industries who meet to share and discuss best practices, as well as discover and develop analytics innovation, all for the purpose of improving the business impact of analytics at their firms. With close to 20 years of experience, Drew has worked on both the business side of analytics, leveraging insights for business performance, and on the delivery side of analytics driving the use of enterprise analytics. Before joining IIA, he led the Data Analytics and Governance team at IKEA’s global headquarters in Europe.

You can view more posts by Drew here.

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