10 ways to become the MacGyver of Data Governance

MacGyver is one of North America’s biggest pop-culture heroes. With a can-do attitude, MacGyver was the problem solver we all wanted to be, overcoming challenges and successfully resolving any dire situation he was thrown in. Here are 10 ways you came become the MacGyver of data governance in your organization.

#1 Understand the drivers

Why does your organization need a data governance program? What needs to be done to support the goals of the organization? This topic is covered in the “3 most common data governance drivers” article and video, but it can be summed up by the following:

  • Regulatory compliance – your organization needs to comply with an external regulatory body (ex: HIPAA, FIPPA, CRA, PCI, CASL, GDPR, etc.), or internal institutional policies
  • Business intelligence program/initiative – your organization wants to streamline, or centralize reporting capabilities, both strategic and operational. It wants to roll out a data warehouse or introduce data analytics capabilities and get a better hold of data hindsights, insights, and foresights.
  • Data quality – the overall quality of the data needs to be improved. This could also be tied to a specific project where data quality would ensure its success.

#2 Understand the main pain points

What is your organization struggling with the most? Try and determine this from a data acquisition, maintenance, and dissemination perspective.

#3 Secure an executive sponsor

Any program will fail without proper sponsorship. You need someone at a higher level to endorse and sponsor your program. This individual will ultimately help you to achieve a higher buy-in rate from your colleagues

#4 Give the decision power to the business

Create a data governance body with equal representation from the different facets of the business which will define and decide on the priorities of the program, approve policies, procedures, and resources, and act as a communication vehicle towards their units. – Read more about the role of the data governance council and why you need one.

#5 Define roles and responsibilities

Without having to secure further resources, you need to determine what existing roles and what people already have data stewardship and  data custodianship responsibilities. Also, flag those that act as data brokers and data consumers. – Read about the different types of a data steward.

#6 Identify your data champions

They are already out there taking great pride in their work and the data they are managing, with or without guidance. Who creates the data, who is maintaining it, who is ensuring its quality, who is benefiting from its outputs? Find out who lives and breathes data, who named their pet “Data” (true story), and who stares at numbers the whole day and care about its quality. One of them will be bound to be your champion that would gladly assist you in your efforts.

#7 Take a baseline measurement

Most often we are so eager to implementing a new process or improving the quality of the data that we forget to first measure it. It’s crucial to take that initial baseline so you can showcase how data governance is improving the data set you’re managing.

#8 Measure your successes

As a continuation of the previous bullet point, you need to expand the baseline measurement into a data governance scorecard. Track operational items such as number of data governance meetings, issues submitted and resolved, number of processes identified, number of data owners and stewards assigned, number of business terms defined, data elements approved, and so on. Use data profiling to show your data quality improvements for data accuracy and completeness.

#9 Employ tools to support your projects

Perhaps not in a MacGyver spirit, but you can only do so much with spreadsheets, word documents and presentation tools. At one point you need to invest in dedicated tools to help you profile your data, uncover and document the data lineage as well as data sources, model your data environment, document and disseminate your data and business dictionaries/ glossaries, enforce data security policies, and monitor the status of your data quality.

#10 Communicate to stakeholders

Communication is the basis of the data governance success. You need to continuously communicate what is being done, what has been done, and what will be done. Tailor your message to the audience, determine the best messaging frequency and of course, the medium. Setting those expectations and tieing your data governance activities and results to the unit goals is key. Everyone should be aware of what data governance is, who is involved, how they can participate if they want or need to, what the goals and scope are, and most of all understand that data needs to be managed as an asset. – Check out this free communication plan template if you need somewhere to start.

What advice do you have and what is currently in your MacGyver toolkit?

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