The objectives of business intelligence (BI) initiatives remain fairly consistent over the years, with most organizations, across industries, leading BI business cases with the rather generic goal of “better decision making.” This vague objective does not specify:
- Which decisions will be made better
- What better means (i.e., in what ways will they be made better?)
- How much better those decisions will become (for example, two decisions, improved by 0.01 and 1,000 percent, respectively, both could be considered better)
As such, this goal for BI initiatives often fails to align well with strategic goals and business outcomes—a fundamental gap that hurts data leaders and their teams trying to sustain and grow their budgets. Organizations that emphasize the goal of better decision making tend to prioritize at a lower level more precise, external-facing, and outcome-driven objectives—which in turn better align to business value. Examples of such more-precise objectives include revenue growth, customer experience, and competitive advantage.
But organizations with data leadership (a chief data officer or equivalent) in place or planned for the future tend to have BI objectives and priorities that often focus at a higher level on more strategically aligned outcomes. Organizations with such vision—stewarded by data leadership—also report a higher level of achievement against those objectives than organizations with no existing or planned data leadership.
This represents the driving force for more business leaders and data leaders to elevate, formalize, and empower data leadership roles in their organizations. Data leadership allows more targeted and outcome-oriented objectives for BI, with a greater degree of frequency in achieving the goals of BI initiatives. This success translates to better perceived business value from data and analytics, improved Hyper-Decisive® maturity levels, and sustained BI programs and budgets.
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