Generally speaking, to be successful today — a decade after “big data” entered the business lexicon — a company must make data-informed decisions.
So, why are corporate executives hesitant to “get their hands dirty” by learning how to manipulate data themselves, as opposed to relying only on data scientists, IT managers, or those team members who do have an affinity for data?
In a new Deloitte survey of 1,048 executives at companies with more than 500 employees, two-thirds (67%) of respondents said they weren’t comfortable accessing or using data from their tools and resources.
“The fact that two-thirds of executives at large organizations are not comfortable navigating what is now the lifeblood of every business is a gap that could yield huge dividends if addressed,” Deloitte wrote in its survey report.
Such executive reluctance is all the more curious considering the outperformance of companies with the strongest cultural orientation toward data-driven insights and decision-making. Among executives at those companies, 48% said they outperformed their business targets, compared with just 22% among companies with a more diluted data analytics culture.
Stating the obvious, Deloitte observed that “a twofold difference in not just meeting but exceeding business goals is a significant difference.”
Of course, as Deloitte noted, creating any form of desired culture is a challenge for most organizations. Only 39% of survey participants said their companies had a strong cultural orientation toward data-driven insights and decision-making.
Another survey result that cast executives’ hesitation to get more personally involved with data in a poor light: Among the approximately one-fourth of companies where all employees were trained on analytics, 88% exceeded business goals. Among the approximately two-thirds of companies where only select employees were so trained, just 61% did the same.
Furthermore, Deloitte said, “Concomitant with the need to involve all employees in the use of analytics for decision-making is the need for user-centered design and stakeholder analysis. Decision-makers, data scientists, and business analysts all must care about the business outcomes and be consulted frequently on analytics projects.”
“Instead of relying on siloed teams of highly technical quantitative experts,” Deloitte advised, “companies would do well to cultivate a wide variety of people throughout the organization who are curious, numerate, and capable of translating between analytics/data science methods and business requirements.”