Data has become a valuable commodity. In recent years, headlines have referred to it as “the new oil.” So how can your organization treat data as the business asset it has become? Establish a data-driven culture.

Today, data is a valuable asset. It can be used to drive efficiencies and improve market intelligence. Data has become such a valuable asset that 87 percent of organizations have low BI and analytics maturity, and data/analytics, cloud, and IoT are predicted to have the biggest impact on businesses over the next three to five years, according to market research.

But while most organizations agree in theory that data is important, making data the foundation of business decisions is another story. It requires a data-driven culture — a shift in mindset and a commitment across the enterprise toward becoming more data driven.

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Building a data culture starts with a strong foundation. Here are three key elements that will help you lay the groundwork for a data-driven culture in your organization:

Executive sponsorship — Your data initiative must have an executive sponsor. Executive sponsorship demonstrates executive buy-in from the start and helps foster a commitment to a data culture across the business for the long-term.

Data ownership — To support a data culture, an organization should appoint a Chief Data Officer or Chief Analytics Officer (CAO) to oversee data governance for the enterprise, including data accuracy and consistency. According to Mike Rollings, research vice president at Gartner, “The Chief Data Officer (CDO) is the best role to maximize the data and analytics value in the organization. If your organization does not have this executive role, push for its creation. Not every company needs to adopt the CDO title, but every company does need someone to adopt the tasks of prioritizing or leading its data and analytics strategies.”

Here is an example from the real world: Neighborhood Health Plan of Rhode Island (Neighborhood), a not-for-profit health maintenance organization (HMO), grew from fewer than 1,500 members in 1994 to 50,000 members in 2000 and, by 2014, to 165,000 members. Today, Neighborhood serves approximately 195,000 members. With such growth, the organization recognized the need to create a centralized analytics department and bring on a Chief Analytics Officer. Doing so demonstrated that information was a key strategy for the organization and set the stage for Neighborhood to become more data driven.

Data governance policy and structure — Establish a team (led by the CDO or CAO) to create a data governance policy and structure that ensures data integrity. The policy and structure should include data definitions as well as documentation for how data is collected, processed, tested for accuracy, and reported on.

Data quality and integrity is critically important for establishing and maintaining a data culture. Data must be trusted by everyone using it. For people to trust data, it must be accurate, complete, and consistent. Just think: All it takes is one bad report for the entire enterprise to lose confidence in future information.


In addition, ensuring data quality is essential for compliance with regulatory guidelines (such as those of the Food and Drug Administration for the life sciences industry) that target computerized systems, electronic records, data integrity, and Computer Systems Assurance, as well as other guidelines and laws around data privacy and security.

TIP: Ensure your data governance structure is fit for purpose by aligning it with business outcomes. When data solves business problems, the entire enterprise is more likely to buy into the data culture.