We're all data experts now, aren't we?

But what will be the impact on the C-Suite?

The all-enveloping response to this pandemic has thrown up a range of unforeseen consequences. And one of the ones we’ve been pondering is how the widespread use and commentary on data will affect business decisions at board level.

One glance at social media will tell you that we’re all data experts now, with ‘flattening the curve’ and log scales entering our everyday lexicon. It’s been a five week crash course in data analysis for us all, with everyone on our Zoom Happy Hour offering up their view of what the latest charts, graphs and data mean for us.

Great news if you’re seeking investment for your next project?

For those in the data community, this is both brilliant and frustrating. Senior leaders who have previously not got the importance of data, suddenly have a reference point and can see in fairly bleak terms, how the Government’s scientific advisors are relying on data collection and modelling to chart their way through everything from how many face masks to order to why coronavirus seems to attack different populations disproportionately. Where data is not being collected, there is now outrage rather than a shrug of indifference.

So great news if you’ve been banging the drum for your next big IT or data project, and the investment it will need, right? You’ll be able to use examples from the pandemic to create comparisons that non-data speakers will suddenly understand.

Before you hit send on the business case, let’s just consider some of the potential challenges of our newfound data enlightenment.

Data can be quickly discredited

At the time of writing, the daily death toll in the UK is now reported with a long list of caveats. As we’ve grown to understand that the data is only for hospital deaths, that there are differences in how doctors are determining cause of death, that many people who’ve died haven’t been tested for coronavirus and that deaths in care homes have been understated, it’s reinforced a view that data can’t be trusted.

This means that in a business context, you’ll need to be able to:

• Defend your data sources
• Be transparent about gaps
• Deflect pressure to report quickly
• Be ready to argue for investment in better data collection practices

Modelling is filled with uncertainty

When the US based Institute for Health Metrics and Evaluation (IHME) reported in early April that they expected the UK death toll from Covid-19 to be the highest in Europe at 66,000, we were all deeply shocked and saddened. Two days later, and the figure was revised to 37,000, illustrating the huge variances that can appear in even the most sophisticated modelling.

Back in the boardroom, does this mean you can expect more challenge around anticipated sales figures, customer behaviour patterns and any other metric you’re asked to predict? Modelling becomes harder, the more sparse the data set or where comparisons are not valid. Will we see more trust placed in experience and gut feel? Perhaps we’ll reach a more nuanced understanding of the role of predictive models, and how they can create a useful context for decision making eg ‘we think the final figure will be between x and y, so let’s plan on that basis.’

Cause and effect may be more hotly disputed

We’re so early in the stages of the pandemic, that we can only begin to see some of ways in which we might describe an outcome as a success or failure. For instance, there have been controversial arguments about the benefit of the excess deaths we’re preventing through social distancing compared to the spike in cancer deaths we might expect in two years’ time as people with symptoms choose to stay away from their GP.

Listening to these arguments reminded me of how difficult it is to combat theories that tie in with people’s pre-conceived notions or area of personal responsibility. If your data is going to contradict the world view of the person signing off your budget, and you’re unlucky enough to work in an organisation where the egos aren’t quite left at the door, be prepared that evidence and logic might not be enough to help you win the argument. You might need to practice some of the softer skills that build trust, and show your own vulnerability, in order to remove bias from your organisation’s decision making.

At KDR, we have to believe that a societal shift in the understanding and application of data will be a good thing for our clients and candidates. We’d love to hear your theories on the impacts in your business when we emerge from lockdown.

This article was first published here on the blog page at www.kdrrecruitment.com