Solving Data Governance by Scaling Agile/Scrum

When all is said and done, regulatory requirements comes down to data management. Legislation like Sarbanes-Oxley and Dodd-Frank have ushered in the necessity of adopting a data governance program to align information accountabilities amongst stakeholders, and to foster intelligent collaboration between the business and technology.

“Data governance is a set of processes that ensures that important data assets are formally managed throughout the enterprise. Data governance ensures that data can be trusted and that people can be made accountable for any adverse event that happens because of low data quality. It is about putting people in charge of fixing and preventing issues with data so that the enterprise can become more efficient. Data governance also describes an evolutionary process for a company, altering the company’s way of thinking and setting up the processes to handle information so that it may be utilized by the entire organization. It’s about using technology when necessary in many forms to help aid the process. When companies desire, or are required, to gain control of their data, they empower their people, set up processes and get help from technology to do it.”[3] 

Key is providing checks and balances between those who create/collect information, and those who consume/analyze information. In any enterprise, much less a large institution, this is not an easy task.

Some stakeholders are concerned with operational systems and data; while others care mostly about analysis, reporting, and decision-making. In fact, the needs of stakeholders who are concerned about data quality and controlling access to information may conflict with stakeholders who want to increase the ability to acquire and share content, records, and reports. In addition, these needs must consider risk management, data security, and legal issues. To make matters more complicated, stakeholders tend to have different vernaculars to describe their assumptions, requirements, drivers, and constraints.

The question is how to best implement data governance within an organization? It is one thing for a company to desire or be required “to gain control of their data,” but it is all together another issue to “empower their people” and do it in practice.

The answer to the above question may exist in applying Agile/Scrum methodologies and scaling the agile mindset across the enterprise by implementing a matrix organization.

Figure 1. Iron Triangle Waterfall / Agile Paradigm Shift

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