When the topic is data, today’s CEOs are apparently feeling much the same about it as the sailor immortalized in Samuel Taylor Coleridge’s “Rime of the Ancient Mariner” felt about water. In the 2019 PwC Annual Global CEO Survey, CEOs were quite clear about how dissatisfied they are with how data is used in their organizations. And this, with the explosion of data that we’ve seen across all industries, and in all regions.
The survey — using the same language as the one fielded in 2009 — asked about, first, the importance of certain categories of data, and second, the comprehensiveness of that data. PwC measured the responses across nine categories of data, and as you can see in the graphic below, with the exception of one (financial forecasting), there’s been no significant movement in the past decade. Even more disheartening, the gap for the category CEOs deem to be most important of all, Customer Preferences and Needs, has actually widened in the past decade.
The second most important category of data, Financial, is the sole category that saw an increase in its comprehensiveness in the past 10 years. That makes business sense, since the bottom line is an organization’s ultimate focus. But other categories are similarly important, and they saw decreases. Brand and Reputation, for example, was ranked as one of the top five important categories, but its comprehensiveness figures dropped 7pp since 2009. And as mentioned above, Customer Preferences and Needs remained in the top spot, and its comprehensiveness figures also dropped, by 6pp.
The most-cited reason for this disparity was the lack of analytical talent in their organizations. There’s no silver bullet solution to this — you can’t simply hire more specialized data scientists and expect this to be solved, because in today’s organizations, analytics is part of everyone’s job. Employees across every functional area, and at every level, are being called upon to work on a regular basis with data, from CRMs to dashboards, and to incorporate data and analytics into their work on a daily basis. Analytics is no longer the bailiwick of a highly-specialized data science team.
One way to address this need is to partner with educational institutions to offer programs tailored to the types and levels of skills that an organization needs. Not every employee needs to be able to build a machine learning algorithm, but every employee does need to know how to critically look at data, at trends, at the output of a forecast or projection and interpret what it means for the question at hand. Cultivating these skills will need the involvement of educational organizations, be they four-year or two-year colleges, or online learning options.
A final note: just because the respondents in this survey are global CEOs doesn’t mean that these findings are only applicable to large organizations with global reach. In my conversations with business owners here in New Hampshire, I’m finding that these same results hold. No matter the size of the business, the amount of data available to them has grown exponentially, but their capacity to analyze that data and use it for business decisions hasn’t kept pace. In fact, I’m often hearing that the capacity has stagnated, or has been de-prioritized in favor of “more pressing” short-term initiatives. I’ll have some suggestions for tackling that challenge in the coming weeks.