Kick-Start Your Data Governance Program
Many companies aren't seeing the full benefits of their data governance program. What contributes to an ineffective governance program, and how can it be revived?
- By Wes Flores
- September 22, 2016
Many companies aren't receiving the full benefits of their data governance program. They have some of the components of a data governance program -- the charter, the council members, the workgroups -- but something seems amiss. They're not seeing the fruit of their program. What contributes to an ineffective data governance program, and how can it be revived?
Common Signs of Ineffective Data Governance
Missing Passion: The value of the data management program is not evident to the average employee and even data governance members question the value of the program and their time invested. When management grows impatient to see benefits, funding and support soon wane and leadership loses its passion for the program.
Cause: Relaxed ownership or commitment.
Corporate Politics: Data governance leadership becomes focused on a specific domain, department, or single project rather than keeping a holistic view of the organization's data assets.
Cause: Enterprise priorities and objectives aren't aligned; different groups are lobbying for their own interests.
Missing Knowledge: Working teams don't have access to the right training in business and system processes or there isn't effective education on data management best practices.
Cause: Lack of meaningful training or education.
Missing Internal Marketing: Perceived past failures of the data governance program left a stigma, and there is no data advocate to repair the damage or promote the tangible value of the program.
Cause: Lack of governance advocacy.
Missing Program Management: Data governance requires a shift in corporate culture and this takes time. When management does not effectively set expectations, disappointment follows.
Cause: Expectations not set effectively.
5 Changes to Make Now
Regardless of why your data governance program needs a jump-start, rest assured that help is available. Here are five changes that can help you improve a floundering governance program.
#1: Find external resources: External resources such as technology partners and consultants can help you get out of a rut and move to the next phase in data governance program maturity. Fresh eyes can help you see beyond the current challenges to the horizon.
#2: Employ the right tools and technology: Data governance-centric software helps data stewards easily manage their daily processes around data definitions, lineage, and ownership. Data profiling software gives valuable insight into the status of your data sets. Data quality software helps keep your data healthy through business and cleansing rules.
#3: Use a data advocate: Introduce a data advocate into the data management mix to promote and drive the charter of your data governance program.
#4: Focus on training and education: Ongoing training and education are core values of a data management program and should be kept at the forefront. Provide training on internal data, systems, and business processes. Create incentive-based education programs on data management best practices.
#5: Adopt agile methodologies: Use agile methodologies to manage your data governance program. Keep your program on target with a story map laid out in strategic epics, epics, and sprints.
Strategic epics cover the major areas of data management such as data governance, data quality, data operations, and master data management. Epics represent milestones within each of these areas. Use sprints to keep work groups focused on small, incremental deliveries -- bite-size chunks of the overall enterprise initiative. Use lessons learned from each sprint deliverable to enhance your sprint backlog.
Agile Principles Driving Data Governance
- Agile data governance does not lack processes, form, or structure
- Agile data governance is not a mini version of traditional data governance
- Agile is the best way to quickly derive tangible business value for your data management program
- Agile builds momentum for the data governance program as teams, stakeholders, and decision makers see the fruits of their labor in sprint deliverables
- Agile data governance helps break down strategic enterprise projects into more manageable units
Agile Data Governance Practical Examples
The following user stories are practical examples of agile data governance in action.
- As a data steward, I would like to create a data dictionary for our billing system. (Run a sprint for each source system.)
- As a data steward, I would like to profile MDM source data.
- As a sales manager, I would like to implement a CRM/MDM integration strategy.
- As a BI developer, I would like to build a prototype executive dashboard for sales.
- As a data owner, I would like to gather requirements and build business process workflows to manage master data.
- As a data owner, I would like to analyze new data sources for sales leads.
- As a data governance council member, I would like to define data governance processes for my workgroups.
- As an MDM test lead, I would like to have requirements to test group one of our MDM system.
No matter the reason for your data governance program's problems, there are many ways to recoup the losses and rise to the next level of program maturity.
Wes Flores of McKnight Consulting Group has over 20 years of experience in the data management field. Specializing in the areas of enterprise data warehousing, MDM, analytics and BI programs, he has worked mid-sized to Fortune 15 companies with a passion in promoting data as an asset. You can contact the author at Wflores@mcknightcg.com.