Though most decision makers with buying power agree data-driven decision-making is a moderate priority at their company, 41% of business leaders find the process "very or extremely challenging," according to a Forrester report.
Key hurdles to data-driven decision-making include lack of data, lack of access to the data, and an inability to deploy the appropriate tools to gather relevant insights, according to the report.
Companies that overcome the deadlock spot data literacy gaps, institute a role-driven data literacy program, and ensure data producers within the company take user needs into account. Data literacy efforts should turn focus beyond business analysts, data scientists and other power uses and include front-line workers, according to Forrester.
To outlast competitors, companies can rely on data to gain a more precise business perspective.
Valuable data insights aren't likely to come from plugging in a tool, or deploying a specific data architecture and hoping for the best. Data literacy at an organizational level is unlikely if staff is ill-equipped to meet that goal.
An organization which leans on data literacy will want to sit at the "intersection between data, tools, and individual skills and expertise," according to Forrester.
But data analytics talent is scarce. It's one of the sectors where unemployment is virtually non-existent, according to Robert Half. That's why companies such as Microsoft, Amazon and Salesforce pump millions into workforce development programs that feed their internal talent needs and expand the broader talent pool.
Companies with successful digital transformation projects make talent a key part of their approach, retooling workforce development strategies to better suit business needs.
The push from data-driven decision making often comes from the top. C-suites are expanding to give those leading data initiatives clearer insight into business decisions, with chief data officers tied closer to revenue and product development.