In this blog post we will discuss data culture at an organization, particularly the elements necessary to have a data culture. These elements include leadership, knowledgebase, access, tools, communication, engagement, training, stewardship, and continuous improvement.
A definition of culture we have seen is Shared Values + Beliefs + Norms + Behaviors, all of which are hard to quantify. The term “data culture” is also not particularly well defined and varies greatly from organization to organization. It is frequently used to describe a view about how an organization functions (or should function) with respect to its data. An organization cannot buy or force a data culture. It can only build one overtime, one step at a time. Building a data culture requires a mix of technology, training, and change management. A data culture involves people and possibilities and how an organization can make people better.
We love these culture-related quotes of "Culture eats strategy for breakfast." by Peter Drucker and “A culture is strong when people work with each other, for each other. A culture is weak when people work against each other, for themselves. Success is a team sport. Strong relationships are based on trust and communication.” by Simon Sinek.
Data Governance solutions (like the Data Cookbook) can assist with achieving a strong data culture. A data culture organization desires a staff that shares ideas, notifies others when errors or data quality issues are found, and is not afraid to express themselves. A solution like the Data Cookbook helps with this. A data culture allows for better decision making which gains organization efficiency, improves staff satisfaction, and increases profitability. To be able to look at the data for answers, the data must be readily available, trustworthy, and interpretable. A data culture provides this and promotes data-driven decision-making, data transparency, and the alignment of data and analytics to organization objectives. It prioritizes strategic data use and encourages sharing and collaboration around data. An organization with a data culture does not have messy data. The organization is focused on the creation of data-related content (specifications, business glossary entries, data system inventory entries, data quality rules, reference data, etc.) for the data governance knowledge base as well as the improvement and curation of existing content.
In our opinion here are our thoughts on elements necessary in having a data governance culture:
- Leadership and Oversight
- Central Data Governance Knowledgebase and Common Language for Staff
- Data Transparency and Access
- Data-related Tools in Place
- Communication
- Points of Engagement
- Training in Place
- Data Stewardship in Place
- Change Management and Continuous Improvement
Let’s go into more detail on these elements:
Leadership and Oversight
A data governance culture requires organization leaders to put a focus on data governance along with getting the necessary tools and training in place. Leadership must provide encouragement, and recognition for staff. The organization needs a data governance group or a data governance manager (VP, Director, CDO, etc.) in place who is responsible for the adoption and maintenance of data-related efforts.
Resources: Blog Post: Responsibilities of a Data Governance Leadership and Oversight Committee
Central Data Governance Knowledgebase and Common Language for Staff
A data governance culture needs a central knowledgebase where staff can find data-related content. Users need to know what the data fields and metrics mean. You need a data dictionary. This is an aspect that trips up many organizations. When you do not have a clear list of metrics and their definitions, people make assumptions, ones that may differ from colleagues. Then, arguments ensue. The organization’s subject matter experts need to agree on the data dictionary and what the data means.
An organization needs to generate a business glossary with clear, unambiguous, and agreed-upon definitions. This requires discussion with key stakeholders and organization domain experts. You need buy-in to those official definitions; you do not want teams going rogue with their secret version of a metric. It is often not the core definition where people’s understandings differ but how to handle the edge cases. For example, while everyone might have a common understanding of what an “orders placed” metric means, they may differ in how they want or expect to handle cancellations, split orders, or fraud.
Building a data culture requires an organization to have the capability of data search and discovery. Staff need to be able to find relevant data just in time as they try to make decisions. Additionally, the data systems are more likely to be organized, inventoried, and documented.
Resources: Blog resources posts for business glossary, data dictionary, reference data, data quality, and data system inventory
Data Transparency and Access
A data governance culture requires that staff have access to the data and the information about the data. Having clean, high-quality data, from a central source, and with clear metadata, is ineffective if staff cannot access it. Data-driven organizations tend to provide access wherever the data can help. This does not mean handing over the keys to all the data to all the staff. Instead, it means assessing the needs of staff members, not just the analysts and key decision makers, but across the whole organization, out to the front-line of operations.
It is the front-line staff, the customer service agent dealing with an angry customer on shipment, or a warehouse worker facing a pallet of damaged product, who can leverage data immediately to determine the best next steps. If suitably empowered, they are often also in the best position to resolve a situation, determine changes to workflow or handle a customer complaint. Data-driven organizations need to foster a culture whereby individuals know what data is available. Data is being used in day-to-day decision-making. The staff needs to be comfortable requesting access, if they have genuine a use case. Red tape should be cut so that while there is still an appropriate approval process and oversight, and systems in place such that access can easily be revoked, if necessary. The staff can get access without too many hoops to jump through and without too many delays. Finally, with broader access, and more users of analytical tools, the organization will need to commit to providing training and support.
Resource: Video-Value of Open Access to Data Catalog and the Data Knowledge Chasm
Data Tools in Place
A data governance culture requires some tools or technology (for example data governance, data quality, data catalog, and data requests) that is or are well implemented. The leadership of the organization must make the investment in these tools or technologies.
Resources: IData has the Data Cookbook solution that will aid in achieving a data culture with its data governance, data quality, data catalog and data requests features.
Communication
A data governance culture requires a great deal of communication. There are various communications necessary between the various stakeholders: data users, data stewards, and organization management. Data governance leadership should create a communications strategy which mentions communications goals and objectives, describes communication types, indicates frequency of distribution, and identifies stakeholders and audience groups. This strategy will aid staff to become engaged with data governance groups and individuals and ensure the success of new data-related policies and processes.
Regular communication to data users should include organizational goals for managing data, new or updated data-related policies, training availability, changes to data-related processes or resources, data quality improvements, updates on data-related initiatives, and who to contact regarding data-related issues.
Feedback, an important communication, from data users and data stewards, must be collected to improve effectiveness and efficiency in the organization.
Resource: Blog Post-Here's Some Data Intelligence Resources Regarding Communication and Training
Points of Engagement (Entry)
A data governance culture requires the organization’s staff knowing how to engage with the existing data-related knowledgebase for content they need. An organization with a data culture has staff that knows the answers to the following questions:
- What do I do when the information I am looking for in the data knowledge base is not there?
- What do I do when I feel the data is wrong?
- What do I do if the information in the data knowledge base seems wrong?
- What is the data request process for content, support, or correction?
We call these points of engagement or points of entry. We feel that points of engagement are part of a customer Service, just-in-time, and help desk approach to data intelligence and data governance. An organization needs to prioritize content creation based on data requests. The staff of a data culture organization has an expectation of timely and knowledgeable responses to their data requests. An organization needs clearly defined data request (and data quality) processes that are known to the staff. And that they feel comfortable in making requests. A data governance culture encourages questions and requests about data. For additional information about this then access our recorded webinar “Building a Data Culture of Questions and Requests”.
Resources: Blog Post-Understanding Data Governance Points of Engagement
Training and Internal Community
A data governance culture includes data-related staff training with specific training depending on their role in the organization. The organization needs to have training in place on introductory data principles and concepts available to everyone who touches data in their job function. And this should include training on any data-related tools in place. Managers need different training than what the data stewards require. The organization should consider what a new staff member would need regarding data and data governance.
Resources: Blog Post-Here's Some Data Intelligence Resources Regarding Communication and Training
Data Stewardship and Ownership
A data governance culture requires that the organization have data stewardship in place and that confirmed ownership of the data is known. There needs to be in place a workflow so that data requests are routed to the appropriate data steward.
Resources: Blog Post-Data Stewardship is Critical - Here are Some Resources
Change Management and Continuous Improvement
A data governance culture requires change as organization’s change. The market changes. The tools and processes change. Staff changes. And the data changes. New data-related content is created, and existing data-related content needs to be updated. A well-organized change management approach will enhance the likelihood of success for any data governance efforts.
Change management depends on an effective communications program, as well as foundational knowledge on the part of the audience, established by education. It requires participation from leadership, analysis of the organization's culture and consideration of the human factors related to change.
There is a marketing component to convey the benefits and advantages of changes such as a learning and growth opportunity. It can be managed successfully through planning, listening, communicating, using the right tools, and an emphasis on the benefits of the change for the individuals and the organization. The organizational reason for the change and the resulting benefits should be clearly communicated.
The organization’s change management plans should consider what needs to be accomplished to realize meaningful improvements from the proposed change including:
- Seek input from those affected by the change and determine what will be different and what the new requirements are.
- Describe a clear vision of the change e.g., a new data quality policy.
- Identify those affected by the change, including roles upstream and downstream from the change e.g., data domain owners, technical data stewards.
- Different audiences may require tailored materials and presentations.
- Determine the education and/or skills foundation that the varying audiences should complete prior to the change.
- Secure adequate funding and time commitments e.g., virtual meetings, budget for workbooks, modifications to web portal, etc.
- Select effective change leaders, including those now responsible for current processes.
- Executive advocacy for change should be encouraged and should provide positive recognition for each achievement of moving to the new policy or process.
- Capturing measurements are an integral aspect of the change management. For example, number of attendees at brown bag events, number of downloads for new documentation, post-rollout survey responses, etc.
Effective data governance and having a data governance culture in the organization requires a variety of elements: leadership and oversight, central data governance knowledgebase and common language for staff, data transparency and access, data-related tools in place, communication, points of engagement, training, data stewardship, as well as change management and continuous Improvement. We hope that you found this blog post useful.
If you would like to see additional resources on data governance culture at an organization then check out our resources located in our blog post titled “Resources on Achieving a Data Governance Culture".
IData has a solution, the Data Cookbook, that can aid the employees and the organization in its data governance and data intelligence efforts including data requests. IData also has experts that can assist with data governance, reporting, integration, and other technology services on an as needed basis. Feel free to contact us and let us know how we can assist.
(image credit StockSnap_FRU4Y0OBEY_GroupMeeting_DataCulture_BP #1204)
