Over the past years, many organisations have jumped on the analytics bandwagon in a quest to become more data driven. Whether they promoted senior leaders to champion data across the company, or visibly embarked on the development of data science functions, this was undoubtedly a fertile domain. Yet tales of challenges have also been rife, with data professionals leaving organisations after less than a year not an uncommon sight.
Why is this the case? In particular data scientists have blogged their hearts out on this topic, but it often comes down to a fundamental disconnect between activity and action. You can recruit data specialists all you want, but unless you are able to focus their efforts and subsequently activate their work across the organisation, it all remains a bit academic. As following what the data says can be painful, it is not surprising many have historically failed to heed the data.
One of my former leaders used to quip that "revenue solves all known problems." The flip side of that is that revenue hides all known problems. Are you an insurer with bad policies? Who cares! Are you a retailer with unsellable inventory? Who cares! Are you a car manufacturer missing out on an entire segment? Who cares! As long as we make money, why change our ways? We are comfortable. COVID-19 has now shattered this convenient reality.
There are multiple reasons why this is the case. Firstly, due to the novel nature of the threat, relying on historical strategies does not work. This is not a temporary or localised disruption, or a known economic quantity. Data is therefore paramount to gain situational awareness and draw up plans to both survive the peak of the crisis as well as navigate your organisation into the brave new world post COVID-19. There is no existing reference or benchmark.
Secondly, when you are reacting to a situation that is rapidly evolving it is important to have the latest facts at hand. In some countries businesses have had only hours to adjust to local government policies regarding containment. Now monthly data sets are no longer enough and in some cases neither are daily views. Similarly, if you are looking to model your cash position, you cannot round to the nearest million and assume that everything will be fine.
Finally, forward looking planning with timely data is well and good, but putting anything into action will be difficult without granular analyses. For example, say you are a hotel chain trying to identify how to profitably reopen a group of properties. A spreadsheet alone will not cut it. Instead, sophisticated yield modeling is required looking both at the operational requirements coupled with customer insights and travel trends, not to mention external constraints.
Many organisations have invested in data capabilities the way consumers in January invest in gym memberships: all good intentions but limited followthrough. In today's troubled times this lack of commitment will not stand as without a mature data capability any organisation is severely handicapped both in their understanding of and ability to react to the crisis. As the joke goes, who transformed the organisation? a) CEO b) CSO c) CDO d) COVID-19