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February 04, 2011
Information Insight

Not Enough Governance?

Your boss asks you if you could run a “quick report”, and his request sounds simple enough.  But you know what it’s going to entail.  She says, “I just want to see a list of our clients, what they purchased from us and how profitable the relationship is.”  She goes on, “specifically, give me the top 100 clients, their name, the products they bought, the number of each product they bought, and our net profit”.  All kidding aside, this is a simple request.  However, to produce such a report rarely is.  And it’s not the complexity of the reporting tool that’s the trouble.  It’s the location, the quality, and the meaning of the data that can tie this request up for weeks.  This scenario is the case in point for Data Governance.

So you ask, “What is Data Governance”?  Data Governance is the organizing framework for establishing data quality, data management, data policies and business process management for effectively managing corporate data.  So your organization is lacking the ability to have quick access to reliable and accurate enterprise data and you need help?  Kenway Consulting can help. At Kenway, we understand the value of having an organization built to govern data and we know the steps required to achieve it.

Step 1:  Gain consensus.  Build use cases to show critical stakeholders, i.e. executive management, that Data Governance is the solution to many challenges.  When commencing this step, ask yourself some common questions, “Does this mean exactly what everyone thinks it means?”, “What are some pain points and unresolved issues related to data and corporate information?  Product data?  Client data? Sales data?  Reference data?” and “Do I know and trust the source of this data?”  From a Kenway standpoint, this means building use cases to show commonalities across the organization, such as:

  • Not having a consistent definition across business areas
  • Inability to provide accurate information quickly
  • Redundant maintenance and duplicate entry
  • Incorrect or out of sync information
  • Inconsistent data distribution mechanisms and no centralized control

Step 2:  Document the vision, mission, objectives and guiding principles.  This step in the formation of any governing body is often overlooked as hokey or overkill.  However, this is a reference point from which many future decisions will be made.  It is an important step in creating a Data Governance program and will establish the ever-important foundation.

Step 3: Define the data owners, custodians and the overall decision makers within the organization.  This includes a Steering Committee, and working teams (as necessitated by each project), which will vary depending on the size, complexity, organization maturity, etc.  One way to enforce the organization’s clout is to invoke a policy which defines the roles and responsibilities of the different groups and members within the data governance organization and recognizes their authority across the company. Defining who “owns” the data, who “owns” the problem, and who “owns” the solution is a critical early step.

Step 4: Define and deploy a process for policy deployment. This includes defining each phase of the Data Governance process.  Kenway’s process includes:

  • Identify Data Issues – Identify the systems that are impacted and profile/mine the data to come up with a baseline understanding of the areas that need data governance the most
  • Define Policies – Define a set of policies and standards to address any data issues.  Identify and meet with business groups to review these policies and validate and document policy exceptions.
  • Define Procedures – Conduct meetings with each team (i.e. system, operations, business) impacted by the policy.  Define current and potential future state processes, estimate the effort of implementing new processes, and determine courses of action based on time, resources and costs.
  • Execute – Implement the policies and procedures through change management, training and/or technology modifications.
  • Monitor & Measure – Track, report and monitor the progress to ensure sustainability of quality, and identify areas needing further improvement.
  • Refine – Refine policies and procedures as needed.

Step 5:  Enable Data Governance by technology.  As your data governance organization matures, there will be a need for more sophisticated tools to support the efforts, such as source data profiling, maintaining data quality, central management of data brokerage and metrics. 

I have found that, once these steps are established and implemented, the organizations can gain innumerable benefits.  Data Governance organizations can help enterprise organizations realize benefits, such as:

  • Improved customer satisfaction resulting from streamlined data
  • Reduction of costs and increased operational effectiveness by eliminating errors due to data that becomes out of sync or is incorrect
  • Improved ability to meet regulatory needs and make sound business decisions
  • Reduction of activities dealing with manually reconciling data and duplicate data entry

If the need for data governance seems to resonate with you, Kenway Consulting has established our self as experts specializing in data management solutions.  Together with our technology partners, we can deliver a comprehensive Data Governance and Master Data Management solution that is right for your business.

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