Peter Drucker famously said that “culture eats strategy for breakfast.” Well, he didn’t really say that. Sort of the same way that Humphrey Bogart never said “Play it again Sam” in Casablanca. Drucker actually said, “Culture, no matter how defined, is singularly persistent.” Not nearly as catchy. But either way, the point is that a misaligned culture will undermine your strategy.
This especially applies to Data Culture. A misaligned Data Culture will undermine your Data Strategy. Having trouble gaining traction with your Data Strategy, or finding that it is not sustainable? The problem isn’t the strategy. It’s your culture.
The Data Management Book of Knowledge (DMBOK) does not provide a specific definition for Data Culture, but it seems that every other information management organization and vendor does. I like this one from Tableau:
A Data Culture is the collective behaviors and beliefs of people who value, practice, and encourage the use of data to improve decision-making. As a result, data is woven into the operations, mindset, and identity of an organization.
It then goes on in a way that wanders in the direction of product marketing so I’ll just stop there.
Notice that at its core, Data Culture is behaviors and beliefs. Not strategy and certainly not technology. Technology can be used to enhance and empower culture, but it shouldn’t be the starting point for creating it. I guess you could say that culture eats technology for breakfast, too.
I think most companies believe that their people value, practice, and encourage the use of data to improve decision-making. After all, if they’re not doing that then they’re making decisions by the seats of their collective pants in the absence of data. That’s a hard one to sell to the board.
Similarly, they want to believe that data is woven into the operations, mindset, and identity of their organization. I’ve found that at many companies that’s simply not true, regardless of what they tell themselves. Nearly all pre-dotcom boom companies are application oriented. Delivering business capabilities through software development is their priority. Data is viewed as a byproduct of the application. Something that the application needs and that is created to serve the application. As a result, information management is an afterthought, if it’s done at all.
You cannot have a healthy Data Culture if you don’t understand your data.
Companies with more mature Data Cultures recognize that applications exist to serve the data, not the other way around. They have a deep understanding of their data, its meaning, contents, and semantics. It’s not that information management is a priority, rather it is integrated into and integral to their standard operating procedures. As a result, they are more flexible, reacting to competitive pressures and changing market conditions much more quickly.
The importance of data culture has been recognized for a long time. Here are a few recent data points:
- In 2017, McKinsey recognized that “organizational culture can accelerate the application of analytics, amplify its power, and steer companies away from risky outcomes.”
- In 2020, the Gartner CDO survey found that data culture was the #1 priority for Chief Data Officers.
- And in 2023, nearly half of the CDOs surveyed by Wakefield Research for Informatica cited “improve data-driven culture and data literacy” as their top strategy priority, ranking behind only governance improvement.
It seems we have the same “priorities” and “focus” year after year after year, but broadly nothing seems to be changing. Companies have prioritized wanting a data-driven culture and saying that they have a data-driven culture, but they haven’t prioritized creating a data-driven culture. That requires the difficult work of doing something differently.
Establishing a data-focused culture requires intention and discipline. It’s not something that’s going to develop organically or overnight. It’s definitely a journey.
A Harvard Business Review article lists 10 steps to creating a data-driven culture. Number one is that data culture starts at the top, with management leading by example.
Set the expectation that decisions be anchored in data that is well understood.
Ask yourself: What is your company’s data culture? Do you have one? Is it intentional or accidental? Does it drive prioritization across the enterprise, or is it just words on employee town hall slides and marketing emails? And is it driving quantifiable value?
If you find that your data culture is a little weak or a little fictional, start raising your own awareness. Notice whether your enterprise is application-oriented or data-oriented. Notice whether information management drives development or is an afterthought. This may lead you to start thinking about your company’s Data Culture, and what you want it to be by design instead of what it has evolved into by default.
