“If you pay attention to how many times you hear conference speakers use the word ‘culture,’ you’re going to be surprised,” remarked Mary Levins, founder of Sierra Creek Consulting, during her DATAVERSITY® Enterprise Data World Conference presentation titled The Culture-Centric Approach to Data Governance. She co-presented with Cassie Elder, the owner of DataCraft Partners. They discussed how to build a successful Data Governance Program by working within a specific organization’s culture type.

“What we hear a lot is that we need to create a ‘culture of Data Governance.’ We’re going to flip that around and show you how to build Data Governance for your culture,” said Elder.

Culture’s Relevance to Data Governance

Elder noted that Nobel Prize-winning political economist Elinor Ostrom, whose work focused on governance of the commons, said that governance is very specific to culture and argued that a culture-centric approach to governance is essential to success. Levins added that organizations that try to implement Data Governance by using tools and processes that don’t fit the company culture often wonder why they don’t succeed.

Data Governance is essentially a Data Strategy that supports the Business Strategy, said Levins. Business objectives may focus on increasing revenue, reducing risk, or focus on customer service, “But Data Governance is a Data Strategy that’s going to support those overall business goals.” Data Governance includes Data Quality, Data Standards Management, policies, procedures, and defining accountability.

Definition of Culture = Shared Values + Beliefs + Norms + Behaviors

Levins shared a quote from Execution: The Discipline of Getting Things Done by Larry Bossidy, CEO of GE and Ram Charan: “No worthwhile strategy can be planned without taking onto account the organization’s ability to execute it,” and the ability to execute is tied to shared values, beliefs, company norms, and behaviors. “A norm is how you do things in your organization, and behaviors are beliefs turned into action.”

Elder said that the concept of culture has been notoriously difficult for academics to define. One way to look at it is to consider that a fish doesn’t know it’s in water. Although the process of determining your company’s culture by looking for “shared values, beliefs, company norms, and behaviors,” works from an academic perspective, a simpler process is to ask, “How do we do things around here to succeed?” There are many organizational models to choose from, but Elder said they found that Organizational Psychologist William Schneider’s definition and model was simple and practical, and adapted it for Data Governance.

Phases of Data Governance

Levins said that there are three phases of Data Governance: Discovery, Operationalize, and Sustain. Discovery is for assessing the current state, aligning Data Governance requirements to the business objectives, and getting buy-in.

“The Operationalize phase is one of the most challenging phases of a Data Governance journey because that’s where you start to execute,” she remarked. Defining critical data elements, designing processes, and developing Data Governance solutions for meeting business objectives identified in the Discovery phase are all part of the Operationalize phase.

The Sustain phase is where “Data Governance just becomes part of how you do things in your company.” This phase includes measurement of results and identification of needed modifications. No matter where you are, Levins said, “Culture really needs to be the focus across the entire journey.”

How to Identify an Organization’s Core Culture

The first step is to observe. Places to look for indications of core culture are in the mission statement, in vision documents, and posters put up by the Human Resources department. Since culture is driven at the leadership level, observe what leadership values and rewards.

In a more formal process, surveys of staff and leadership, past and present, can provide knowledge useful for determining the company culture. Recognize that culture clash is a possibility with mergers and acquisitions. In those situations, “Make sure that you have those conversations at your executive level because you can’t really drive that through your Data Governance programs,” Levins said.

Four Types of Organizational Cultures: Cultivative, Collaboration, Control, and Competence

Although most companies have a predominant core culture, and there are often subcultures within that culture, Levins said, but for the purpose of the presentation, they would be focusing on the core culture for the organization as a whole. Each culture has strengths and pitfalls. Elder noted, “The things that we love about our partner also drive us crazy sometimes.”

Cultivative: Growth and Development

Cultivative culture is focused on people and possibility, said Elder. “How can we make the future better? How can we make people better?” Often found in religious organizations, nonprofits, and in mission-driven companies working for social justice or trying to “make the world a better place,” Cultivative culture is focused on personal growth, so promotion from within is an important value. Teams tend to be diverse, and ideas are considered from any team member. Self-expression, empowerment, growth, and adaptability are valued. “Individuals in organizations with a Cultivative culture wake up in the morning and say, ‘What’s going to change today?’ They are not expecting the status quo.”

• Strengths: The Cultivative culture encourages self-expression, creativity, freedom, and autonomy. Diversity and inclusion are important, as is the well-being, personal growth, and evolution of everyone in the company. Innovation is valued, and the environment is one of trust.
• Pitfalls: A common practice when creating a Data Governance program is to cut and paste policies, procedures, and controls, but that process will seem arbitrary and restrictive in a Cultivative culture, “So if you instill the principles of Data Governance tied to their mission, then they will just organically and naturally begin to follow.” Tools, such as a prioritized strategy map, can help move Cultivative cultures from discussion to implementation. “A Data Governance dashboard or scoreboard will keep them on track, as something to look toward in terms of achievement.” Most importantly, Data Governance efforts must be tied to helping execute their mission, Elder said.

Collaboration: Collaboration and Synergy

• Strengths: In a Collaborative culture, harmony and synergy are key values. Diversity is also valued in a Collaborative culture, but the focus is more on group cohesiveness and harmony, rather than focusing on the individual. Loyalty is valued, both within the company and from customers, and members of this culture take pride and ownership for their team’s work. “From a Data Governance perspective, the stakeholder analysis becomes very important, as well as building partnerships across different business units,” said Levins.
• Pitfalls: Collaborative culture is more focused on short-term needs, said Levins, and that can be a challenge from a Data Governance perspective. Another pitfall is that similar conversations occur over and over without a lot of action. To help avoid that pitfall, they both recommend a Data Governance dashboard, said Levins. “What we see a lot in collaborative cultures is almost ‘analysis paralysis.’” She suggests focusing on decision-making and ensuring that those decisions are documented in meeting minutes.

Control: Order and Structure

• Strengths: Control culture values efficiency, practicality, predictability, measured outcomes, and financial stability. Planning is done by designated leaders, with clearly defined roles. Organizations that provide resources to sustain life, like clean water, energy, food, or national defense need a Control-based culture, said Elder. “You’re not going to have any problem getting an organization like this to create a planning committee,” she said, although usually the authority figures are doing the planning. Roles are based on a specific functional ability and individuals become highly evolved in that role.
• Pitfalls: Elder suggests mitigating pitfalls by examining a different culture that succeeds in that area and then translating that strength into the language of the existing culture. For example, in Control culture, employees fear taking on responsibility outside of their job title, and are not likely to do a lot of creative problem-solving.

People in a Control culture may see data issues and know the process is broken but hesitate to report it because they fear disciplinary action, Elder said. In order to succeed with a Control culture, strive to achieve balance: “The best way to do that is to look to the other side of the diagonal, to Cultivation.”

To get employees to share ideas or expose errors, use the Cultivative culture’s support of self-expression, but create teams and authorities and give them the task to report errors within that structure, she said. Change has to be mandated from the top level to be successful. “When business teams are not able to fulfill their business objectives, they will either find a way around it or they just won’t meet their objectives,” she said. “Finding a way around” can put critical data into jeopardy and lead to serious consequences.

Competence: High Performance

• Strengths: Expertise, personal achievement, and innovation are the focus in a Competence culture. Advancements in science and technology, superior execution, and craftsmanship are highly valued. With a Competence-based culture, the focus is on being exceptional. There is pride in the work that they deliver, and this culture sees institutional wisdom as a competitive advantage in the marketplace. Strategy and planning are key strengths, as is long-range thinking, so a Data Governance road map works well in this kind of a culture.
• Pitfalls: “Even though they love planning, one of the key pitfalls is over-planning,” so that plans don’t come to fruition. Levins suggests taking an agile approach, but with slower iterations to shift the focus to shorter term deliverables, which will bring value and align with business needs. Employee recognition is also important in a Competence based culture, so it’s necessary to find creative ways to build that in. “I’ve seen organizations do fun things, like customized M&Ms with their Data Governance program logo,” she said.

Should You Change Your Culture?

Both speakers emphasized that Data Governance should not be driving culture change in your organization. Instead, the existing culture should drive how you govern your data. “If you truly feel that you need to change your culture, focus on a higher level across the organization and get people in that can help with that,” said Levins.

The same is true if you discover that significant culture clash is present—address this with leadership and not through the Data Governance program. Also understand that culture definitions are not discrete, mutually exclusive categories, and collaboration can occur in every culture, not just the Collaborative.

Methods from other cultures can be used to have success with subcultures as well. Most importantly, said Levins, “Strive for simplicity. It’s so much easier once you know your company’s core culture, and it doesn’t feel like you’re forcing it across the organization.”

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Here is the video of the Enterprise Data World Presentation:

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