I am often asked “how do we capture our data glossary assets” and “are we ready to engage with data stewards?” My response is always: if you can state the objective of your data governance program and have a sponsorship organization, then you are likely ready. You need to answer the Why, What, and Who questions before you should answer the How, When, and Where questions. I believe many DG teams make the mistake of spending too much time preparing to do data governance and then not enough doing. Now certainly “Just Do IT” is not the correct approach either. But taking a year or two to develop policies, standards, workflows, and processes before starting to capture assets is not the answer either. Let’s discuss what is necessary to get started.
While there are a few data governance maturity models published, those models are not very pragmatic to help answer this question. In fact, doesn’t it make sense that organizations start their data governance implementations at an immature level (level zero)? Another thought that leaders suggest is that you can only start after the data governance principles, policies, and operating models are approved. Great thought, but that generally takes too long for the business sponsors. Likewise doing the immediate critical project without a data strategy often delivers a one-hit-wonder. Quickly followed by no ability to achieve adoption. We believe the answer to this question depends upon the data governance strategy and business case priorities of your organization. Both are necessary and can be done in a few months.
A place to start may be to answer the question “Why do we need data governance, what is wrong with what we are doing today?” The objectives of Data Governance can be identified alone with a few Data Principles. Then answers are identified as specific business use cases generally grouped into a list such as:
- Definitional or language usage inconsistency – We have each team, line of business, region or country using different terminology for our data. This can produce erroneous reporting, communications problems, inconsistent management decisions, and additional training costs. This often drives the use case to start data governance by capturing the assets associated with a single data mart or small number of reports. The use case only needs a small set of governance processes and resources to get started.
- Authoritative source challenges – Our data consumers are unclear on what sources of data they should use for business processes or reporting and analytics. For this use case, we can select a small group of business processes or analytics to get started with.
- Business processes lacking – This could be stated as we do not have a common view of the processes used in the life-cycle of our data. We have duplicate processing, enhancing data downstream, making data quality fixes in multiple processes, and reporting with the wrong data. For this use case, we can establish data governance with a single business function in one business unit. Subsequent iterations will build upon the governance processes.
What is necessary to be “ready”?
Hopefully, you will agree with me that you are ready to conduct data governance implementations once you have a Data Strategy. You need at least a charter and sponsorship organization that provides the vision for your data governance program. You can then engage with business teams to identify use cases, prioritize the use cases, further define the stewardship organization, and create a roadmap for your implementations. The pragmatic question then becomes what is the detail of requirements that are needed for a specific use case in order to begin?
I would suggest that, based upon our many successful customers, it can be pretty minimal. Let’s recognize that businesses needs solutions to the challenges today. I see firms set expectations that the Data Governance program will measure and drive compliance to process outcomes, accountability and responsibility decisions, language and terminology alignment, technology alignment, data usage improvements, Reference and Master Data alignment, and quality metrics measurements. Most of those efforts can be achieved once you have started down the roadmap, not before you start. Actually, two steps are necessary before you are ready for implementations. First, a data strategy. Second, a business use case.
I advise data governance programs that it is optimal to start with just the following defined.
- Data Governance Charter, Objectives, Risks, Measure of Success (Why) – This is often considered as a component of the Data Strategy. It is critical to document the high level objectives of data governance, what are the risks of data and how the program may measure success. It is important for everyone in the organization to understand why the efforts around governance of assets is occurring to conceptualize how they contribute. Adoption of data governance starts with the Charter definition.
- Data Governance Leadership Organization (Who)– This is most often a 3 level organizational structure. At the top is a cross functional executive leadership committee. Next, a cross functional managerial working team. Finally, a functional operations level team of SME and data stewards. It is not important to identify individuals to get started.
- Basic Governance Processes and Operating procedures (Where) – Having a basic understanding of “what” governance processes, workflows, and operating procedures is helpful to establish expectations for actions and responsibilities needed from each business and technical unit. Don’t worry about the details of the operating model until you have selected a technology. The technology platform will speed your time to market and define the details of your processes.
- Governance Roadmap and Communications Processes (When) – One area that can be forgotten is planning the roll-out activities. Don’t let that happen. A Roadmap of the anticipated roll-outs is often necessary as it identifies priorities that have been agreed to by the leadership team. Many organizations build their roadmap iteratively from the first implementation.
- Communications and Education Plan (What) – The importance of the Communications Plan and Education Plan cannot be overstated. Both plans must be used to create awareness, understand, and engagement in the processes and practices for data governance and proper usage of governed data.
- Adaptive and Flexible Technology (How) – The Data Governance team can start building a business glossary very quickly. You may start with Excel or Wiki, but those tools do not scale well. You will require a highly flexible technology to scale in the future and be adaptable to meet changes very quickly. One thing you can depend upon will be the need to be agile and adaptive to changing business needs. Your technology cannot be an excuse that limits your ability to rapidly respond to change.
Data governance should enable the right people, use the right processes, on the right data, at the right time, with the right technology. To maximize the value of data governance that the business needs, you to start as soon as possible. Data Governance implementations must be iterative and agile so let’s start the program with those approaches in mind. Take a deep breath, stay calm, and allow your data governance program to prosper.