(6) Ways to Sanitize Your Data Product, Dashboard Visuals or Analytics due to Covid-19

A few weeks ago when the Covid-19 non-pharmaceutical interventions like social distancing kicked into full swing hard (at least here in the US), I had asked on a webinar whether attendees’ software data products or analytics projects had been asked to incorporate Covid-19 related changes into their UI/UX. Most said no. I was surprised.

I can think of several ways that Covid-19 could impact the value a data product delivers to its users and many possible UX/design changes you may need to make (or could make to provide unexpected delight/extra value):

Plotting significant calendar events on timelines:

Historical data presentations like standard line charts should indicate important events on the timeline to provide context. Yes, like literally, draw some little dots or stars on long the X-axis (date axis) and illuminate any business-critical or relevant happenings. Adding the ability to provide date events and event ranges can help turn a bland display into something with more powerful context. What dates need to be plotted? That’s for you to decide. Did you cut 80% of the advertising in the company, and you’re designing a marketing ad-spend dashboard for the CMO? Well, putting the dates of these major changes on the charts will help people better understand the information and what they might do next.

Re-Training/Adjusting AI/ML Models:

If your customers are interacting with AI solutions that have now learned from historical data that is almost certainly influenced for Covid-19 related reasons, is that actually desirable? Do the models need to be adjusted given the magnitude of impact the virus has had on many businesses? Does your model interpretability factor in Covid-19 as a cause for a prediction and actually display that to users?

New Comparison Data Needed for Users to Gain Insights from your Visualizations:

Does Covid-19 introduce new types of comparison data that need to be incorporated into your solution? A basic example: in the past, you only offered quarterly time periods. However, right now, 2 quarters ago is like 100 years ago. Users actually want to start tracking from some date in, say, March, that is “off quarter.” “Show me the world, as if it started on the day we saw revenue drop 50%. That’s my new ‘start date’ for the foreseeable future.”

Model Predictions / Predictive Analytics Need to be Further Out to be Useful:

continue reading about this strategy and several more at Designing for Analytics…

Photo by Kelly Sikkema on Unsplash



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Brian O'Neill

Brian O'Neill


Brian T. O’Neill is a consulting product designer who helps companies create innovative ML and analytics solutions. Host of Experiencing Data podcast. #UX