What is Data Culture and Why Do You Want One? By Aaron Kalb
Data culture is top of mind for data leaders, so we wrote a multi-part blog series on it. Read the first in this series where we define just what it is.
The post What is Data Culture and Why Do You Want One? appeared first on Alation.
Data culture is top of mind for nearly every data leader. According to a recent Gartner survey, data culture was the #1 priority for chief data officers (CDOs). McKinsey, the management consulting firm known for its deep knowledge of the C-suite, is writing about data culture and why it matters. According to a recent survey by Alation, 78% of organizations have a strategic initiative to become more data-driven, and Alation customers routinely report that fostering a data culture is their core objective.
Since everyone seems to want a data culture, we decided to write a multi-part blog series defining data culture, reviewing its benefits, and explaining how your organization can go about getting one.
What is Data Culture?
Data culture is an organizational culture of data-driven decision making. As McKinsey says, “data culture is decision culture.” Organizations build a data culture because they want to make better decisions. How does a data culture differ from other organizational cultures? Well, let’s consider some common alternatives—consensus culture and hierarchical culture:
In consensus cultures, achieving agreement is valued above all else. Consensus culture can feel warm and fuzzy on a day-to-day basis because everyone has a say. Unfortunately, consensus cultures move slowly and struggle to innovate over time, because in a large organization, invariably somebody won’t be comfortable with a novel idea that rocks the boat.
On the opposite end, hierarchical cultures value status or seniority above all else, and everyone defers to the “HiPPO”—the highest-paid-person’s opinion. When the ability to generate ideas and make choices is limited to a select few, the experience is demoralizing for everyone else. Ultimately, these cultures end up crushing creativity and missing big opportunities. And since no one can be right all the time—and often the folks “at the top” are insulated from the realities “on the ground”—the HiPPO is frequently wrong.
In a data culture, by contrast, evidence and reason are valued above all else. It doesn’t matter who’s talking or what tone they’re using—what matters is whether the argument makes sense given the data.
Consensus and hierarchical cultures generally aren’t intentionally selected as preferred alternatives to data culture. Rather, they emerge because they’re easy. You can always turn to your peers in a meeting room to solicit their opinions, or turn to the boss. But to be able to look at the data for answers, the data must be readily available, trustworthy, and interpretable.
Why Do You Want A Data Culture?
Organizations with a data culture win out against slower-moving consensus cultures and myopic hierarchical cultures. According to Forrester research, organizations with an insights-driven culture are nearly three times more likely to have double digit growth.*
How does a data culture do this? Data cultures help organizations make better decisions and make them faster. Per a recent write-up on the 2020 MIT CDO and Information Quality Symposium, companies with data-driven cultures “enjoy increased revenue, improved customer service, best-in-class operating efficiencies, and improved profitability.” What’s more, a data-driven culture can help you attract and retain the best employees. After all, would you rather work in a culture that’s dominated by politics or bogged down by consensus-seeking, or in a place where the most logical argument wins the day?
Finally, data-driven cultures increase the commitment to organizational decisions. How many times do corporate initiatives fail due to a lack of employee buy-in, particularly in power cultures where the initiatives come down as dictates? How often are opportunities lost because it takes too long to come to consensus? By demonstrating the data and analysis behind decisions, employees in data-driven cultures are not only happier but more committed to executing on company plans — and commitment alone can dramatically increase the odds of a strategic initiative’s success.
You Can’t Buy a Data Culture, But You Can Buy Software To Help Build One
Imagine a naïve organization with a corporate initiative to “foster Customer Intimacy.” If that organization merely buys Customer Relationship Management (CRM) software and expects magic to happen, they’ll be disappointed. Now imagine trying to infuse Customer Intimacy into an organization where each customer interaction is only known to the lone employee who was there. Even with great training programs and change management techniques, that’s a tall order. CRM software alone doesn’t cause cultural change, but it certainly makes that change more achievable.
Similarly, an organization can’t buy a data culture; it can only build one. But it’s exponentially easier to build one with the right technology. Building a data culture requires a mix of software, education, and change management.
Ultimately, building a data culture requires an organization to enable three capabilities:
- Data search & discovery – Employees need to be able to find relevant data just-in-time as they try to make decisions.
- Data literacy – Employees need to be able to correctly interpret and analyze data to draw logical conclusions.
- Data governance – The organization must be able to ensure that data is appropriately managed, so employees use the right data in the right ways.
The Three Pillars of Data Culture
We call these capabilities the three pillars of data culture. In the remaining three parts of this multi-post blog series, we’ll take a closer look at each of the three pillars – data search & discovery, data literacy, and data governance – to explore what they are, why they matter, and how to deliver them.
Spoiler alert: building up each pillar in your organization requires foundational investments in data intelligence technology (like a data catalog and data governance software) and shifts with people and processes—although the ratio varies: good search & discovery technology is almost sufficient (just as people don’t need much training to use Google search), while data literacy initiatives necessarily require more human effort (at least until we can download statistics knowledge into our brains the way Neo learned kung fu). Ideally, the technology is entwined in people’s work days leading to a virtuous cycle of engagement.
*Forrester: Insights-Driven Business Set the Pace for Global Growth. October 2018
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