Data-driven decision-making is good for business. Companies that successfully use data for decision-making speed time-to-market, better meet customer needs, and accelerate time-to-value through greater speed and agility.1 Data culture is a critical component of a data-driven enterprise. In fact, data culture is strongly predictive of whether enterprises achieve their revenue goals. The recent State of Data Culture Report found that almost all (90%) companies with the highest levels of data culture report meeting or exceeding their revenue goals over the past year.2
Just how do companies build a strong data culture? This blog explores the real-world successes and struggles of Alation customers as they strive to adopt an internal data culture that helps institutionalize data-driven decision-making. It is an opportunity for readers to learn from our customers who are on their own data culture journeys.
What is Data Culture and Why Does It Matter?
Alation defines data culture as an organizational culture where data is expected to drive decisions at all levels. In organizations with a strong data culture, people across the business understand how to find and leverage data to achieve overarching objectives. In other words, a strong data culture enables people to make data-driven decisions.
However, and somewhat depressingly, despite a decade of investment in Big Data and AI, only 24% of executives say that their organizations are truly data-driven. And only 24.4% said that they have created a data culture within their business.3
While technology solutions, like a data catalog, go a long way toward helping organizations become more data-driven, they are only part of the data culture equation. Building a data culture requires both the organizational will to adopt data best practices and the development of individual capabilities that will position the organization for success.
We will specifically address the critical factor of organizational will in building a data culture in a future blog. This blog and its sequel will focus on the critical organizational capabilities that our successful customers have implemented in their quest to build strong data cultures. We’ll explore how they are building on the three pillars that enable a data culture: data search & discovery, data literacy, and data governance.
Search & Discovery – The Basic Building Block of Data Culture
Self-service data search & discovery is the foundational building block of data culture. Organizations must enable users to find, understand, and trust the information they need for their own business purposes. If people cannot find or trust the organization’s data, they can’t derive insights from it. This is typically our customers’ starting point on their data journey.
We hear the same story from our customers time and again. They have too much data, usually spread across multiple business units, with multiple copies of data held in silos, and only a few experts know how or where to find data. Our customers are often large enterprises with vast and wild data landscapes. But increasingly, we’re seeing small-to-midsize businesses with their own share of big data problems.
Finding data in such an environment is extremely difficult. Typically, our customers report that their analysts spend 75% of their time trying to figure out where the data is, if they have access to it, and whether it’s the right data for their purposes – leaving only 25% of their time for analysis. Perhaps most critically, the lack of a unified system for finding, understanding, and using data effectively leads to executives receiving reports with conflicting data. This not only obstructs leaders’ ability to gain insight from the data for strategic decision-making – it erodes trust, both in the data itself and the teams charged with socializing it.
Siloed systems beget siloed processes – and disparate results.The first steps to building a data culture through data search & discovery is to create an inventory of existing data. From there, you can create shared data processes and begin fixing data quality issues.4
Access is important to consider. Who can access what, and how? Many of our customers enable data democratization alongside data self-service. This widens the aperture of access to more people, empowering them to explore the data independently. This is where a data catalog can become a catalyst for the entire data culture journey. In fact, most data leaders (87%) say that data catalogs are very important or essential to their efforts to establish a data culture.5
However, technology alone cannot create culture. “Software solutions are not the panacea; they are a tool to deliver an outcome,” points out Daniel Kasatchkow, Data Catalogue Enablement Specialist at Fortescue Metals Group. “The people and processes are what makes an organizational culture.”
Data Literacy – The People-First Pillar
People are at the heart of a strong data culture. In a data-driven organization, data permeates every aspect of the business, from the executive suite to the customer service desk. According to the Harvard Business Review, a successful data culture starts at the very top.
The Data Culture Survey results bear this out. The top obstacle to creating a data culture is a lack of executive buy-in or support of data and analytics initiatives. In fact, 71% of data leaders are less than very confident that their company’s business leadership sees the link between investing in data and analytics and staying ahead of the competition!6
And while executive support is important, a strong data culture requires data literacy at all levels of the organization, not just at the top. “You can’t just focus on the data experts,” says Jennifer Belissent, PhD, Principal Data Strategist at Snowflake. “Everyone has a role, whether it’s capturing the data, protecting the data, or eventually using the data.” According to Belissent, a successful data literacy program starts with raising basic awareness across the organization of the value of data and the need to protect it. It also focuses on expanding understanding and expertise by leveraging the experts to scale their knowledge across a broader data community.
Building data literacy goes beyond a one-time education program; consistent reinforcement is key. “Initiatives, programs, projects often have short-term impacts on organizations,” says Kasatchkow. “But people fall back into the old way of doing things without a consistent effort and investment in making data part of the organizational culture.”
Many customers have invested in building data into the organizational ecosystem, and this begins with data literacy. One customer is building a data foundations training program in partnership with a higher education institution. “We have a lot of people who are not used to looking to data for information,” says the Director of Strategy and Governance at a major IT Services Company. “They’re used to asking the experts. So as a first step, we’re really trying to get people more comfortable with looking at data for these things.”
Data literacy isn’t one-size-fits-all. Just as someone who is starting to learn English doesn’t start with Shakespeare, not everyone can, or is expected to, become a fully literate data analyst overnight. “We’re not trying to build data scientists out of the gate,” says the Director of Strategy and Governance. “We’re trying to get people to that point where they can say, ‘Hey, I know how to access the data, I know where it is. I know where to look to find what data we actually have. And I know who to ask if I can’t find the information that we have.’”
Finally, a data-literate organization can collaborate around data at all levels of the organization. As businesses move from making decisions based on gut feelings or individual expertise to data-driven decision-making, having a community of individuals that can come together to build and transfer knowledge becomes critical. Having a data intelligence platform like the Alation Data Catalog in place helps facilitate that collaboration, making it easier for people to find and consume the information and ultimately deliver value from the data. “Alation is democratizing our data,” says Sebastian Kaus, Data Governance Lead at Vattenfall. “It’s bringing people together to collaborate to solve our business problems.”
The next blog in this series explores the third and final pillar of Data Governance. Find out why so many organizations stumble on this pillar and read how our most successful customers have overcome the reluctance to even talk about governance. Finally, we’ll sum up with some final thoughts on how organizations can best build the will and capabilities to implement a strong data culture to support data-driven decision-making.
1. Randy Bean, Fail Fast, Learn Faster: Lessons in Data-Driven Leadership in an Age of Disruption, Big Data and AI. 2021. John Wiley & Sons, Inc., p.12.
2. State of Data Culture, p. 14.
3. Bean, p. 17.
4. State of Data Culture, p. 7.
5. State of Data Culture, p. 7.
6. State of Data Culture, p. 5.