Information Governance: Evolution, not Revolution

The Challenge

We are in a time where more and more companies recognize that data is a valuable asset which can provide evidence-based support to decision making in all aspects of their business. Companies also recognize that, as technology rapidly evolves, there are a growing number of both internal and external data collection channels.

With an ever-increasing volume and variety of data comes the challenge of ensuring data is clean, contextual, available, and timely.  For many companies these challenges are daunting, and, while establishing an Enterprise Information Governance function can help, it can easily become resource intensive and overwhelmingly expensive.  One key to implementing an Information Governance Organization successfully is to aggressively manage scope down to only the most valuable and manageable activities.  This can be accomplished by understanding the big picture, focusing on incremental, value-added activities, and implementing processes that are both straightforward and repeatable.

For example, a client recently approached SEI and asked usbig_data to conduct a Business Intelligence assessment.  They didn’t understand how different parts of their organization could report such disparate values for key metrics.   Month after month, executive leadership and their support staff struggled to report accurate and consistent metrics, often having to manually source, transform, and aggregate data while losing valuable time, money, and most importantly the battle of perception.

SEI’s approach was to clearly understand the problem, identify the root causes, and work with our client to create a customized solution based off of return on investment (ROI), business priorities, and resource availability.

Understand the Big Picture

Fundamental to addressing data-related issues is understanding root cause.  By examining the challenges and business needs from different perspectives, not just what tactically presents itself, ROI can be quantified, solutions prioritized, and a holistic strategy created.  In this case, over 70 data quality issues were identified with root causes ranging from inconsistent/poor data entry, manual manipulation of stored data, and definitions/business rules that were inconsistent between lines of business. Next, key stakeholders were identified and a clear chain of ownership and accountability established. Finally, with estimated opportunity costs in hand, we presented our findings and recommendation to C-Suite executives, solicited their buy-in on addressing the highest priority challenges, and established an Information Governance Executive Committee.  This committee’s primary role was to provide guidance on priorities and a clear escalation point for issues as they arose. 

Take a Practical Approach

Once the problem is fully understood, quantified, and prioritized, the key to success lies in effectively managing scope.  Regardless of whether Information Governance functions are new or well-established, it is easy to become overwhelmed or distracted.  Since these functions are not directly revenue generating, justifying an Information Governance program’s value, at an enterprise level, can be challenging and often leads to over-commitment.  This approach soon results in a paralyzing amount of work and should be avoided.

In this example, the governance team selected a small but meaningful set of problems from the list, and for each one assembled a small team.  Each team, called a focus group, had at least one business representative, allocated by the executive accountable, who would own this challenge.  Sharing the responsibilities of information governance is a key step in ensuring buy-in and ultimately success. The focus group’s primary task was to present an outline of possible solutions, both long and short term, for the identified issues.  Additionally, they were asked to provide a way to measure ROI.  The solutions and metrics were presented to the Information Governance Executive Committee for approval before being implemented.

Make It Repeatable

A well-defined scope, schedule, and implementation plan helps make this process modular and repeatable.  Clearly defined processes, roles, and responsibilities helps to maximize efficiency and accelerate work efforts.

In our example, the recommendations included changes to application architecture, database design, process, as well as establishing consistent data standards.  The Information Governance Executive Committee reviewed the recommendations and leveraged them to create standardized processes and enforce compliance across the entire organization. A repeatable methodology was established: solicit executive sponsorship, assign a business owner, pull together a team to address the challenge, select and prioritize based on derived value, establish corresponding data policies/standards, and execute on those action items.

In Conclusion

Improving the quality and richness of data or establishing standards and procedures does not require boiling the ocean. The approach SEI recommends is to define a holistic strategy, start small, aggressively manage scope, ensure strong executive sponsorship, and establish clear lines of ownership and accountability. Take one data challenge at a time and solve it. Small wins are crucial to building trust and demonstrating value.

Aman Garg

About Aman Garg