Is your company driven by data? If so, you may be in the minority. Data from multiple surveys of Fortune 1000 executives show that only around 20-25% companies report successfully establishing a data-driven culture.

The lack of progress is not a reflection of a lack of investment. New leadership roles – Chief Analytics Officer, Chief Data Officer – have emerged to facilitate value creation through better insights. A lot of industry attention is being directed on data literacy and self-service enablement as key to unlocking a more data-driven workforce. And company executives are frequently communicating to their investors that their strategies and investments reflect data- and insight-driven opportunities (e.g., AI).

So where is the gap?

Though corporate priorities may reflect data-oriented offerings and business processes, organizational plans often do not reflect the basic reality that building a data-driven culture is a change management challenge. Senior leaders need to agree on (and appropriately resource) an effective approach for transforming the culture, helping employees transition their activities and responsibilities from the “as-is” state to “to-be” state.

For example, is the organization approaching this transition through a specific program that addresses Kotter’s change management components (e.g., creating urgency, building change teams, maintaining change progress, etc.)? Or is the organization pursuing a more iterative, opportunistic approach such as nudge theory? The approach can be big or small, but being intentional about change management enables leaders to adequately address the most common barriers to adoption.

One way to think about the change management dimension is through the lens of trust. Trust is the cornerstone of any successful change management program. So what would it look like for an employee to trust a new data-driven insight enough to confidently change their behavior and/or mindset? In senior executive education courses I sometimes teach, we explore six areas where trust contributes to the development of data-driven cultures:

  • Trust with Leadership – does this insight have executive attention and support? Employees tend to embrace insights that their leaders visibly value (i.e., model as important and safe). In a sense, there is a transfer of trust.
  • Trust with Impact – does this insight matter? When insights are strongly aligned to actionable decisions and behaviors, they more reliably produce trustworthy results.
  • Trust with People – is the insight driven by experts? Employees want to know that the people who best understand the problem space contributed to the insight and interpretations.
  • Trust with Data – is this insight based on good information? If employees don’t have confidence in the underlying data source, they are much less likely to trust and embrace the insight.
  • Trust with Development – are the data and its insights created using best practices? Employees know that data can sometimes be misleading; they want confidence that the process used to create the insight was well designed and well executed.
  • Trust with Communications – is the insight clearly visible and understood? Employees cannot embrace an insight they don’t see or cannot interpret.

A few of these areas tend to receive more “airtime” in discussions than others; for example, the majority of executives do not trust their data today. The irony is that shortcomings within one area such as “trust in data” is often a downstream effect of deficits in other areas such as “trust in development.”

Where in your organization do you see problems with trust inhibiting the development of a more data-driven business and culture?