Informatica Perspectives

Recently I spoke at a User Group Meeting on the topic “Align for Success: The critical part Data Quality plays in complex Business and IT Initiatives.” I began the discussion by polling the group to find out how many of the organizations represented had a data quality solution in place. The response to the question was mixed, with approximately half the audience indicating they either had a solution or were considering one, while the other half indicated they weren’t currently considering data quality (or the person was unaware of any data quality initiatives). Although this was a very unscientific survey, it set the tone for my presentation, as I attempted to explain the concept of a data quality maturity model. By understanding where an organization is today from the standpoint of the model, management can begin to develop plans as to where they want to end up both in the short and long term.

Gartner’s Data Quality Maturity Model is comprised of five phases – Aware, Reactive, Proactive, Managed, and Optimized. In order for an organization to move along the curve from the awareness phase an attitude shift needs to occur. An organization must move from seeing data quality as an initiative that provides few benefits to something that is considered a core asset to the organization (especially in the proactive and managed phases). As attitudes begin to change, so does the value proposition for data quality, as it moves from being viewed as a cost that could be eliminated to being considered a strategic initiative within the company. Understanding where your organization fits in this model is crucial, as any long term plans that an organization may be considering, such as a Data Governance or MDM initiative, will be hampered if the concept of data quality is still somewhat immature within the company.

In my previous post I discussed the cultural aspect of data quality and how change doesn’t happen over night. Similarly, moving along the maturity model to the point that data quality is seen as a strategic component will take time and require an attitude shift. Even with support from upper management, the best approach to implement a data quality strategy in the organization is something that will need to be hashed out through a series of discussions and iterations of data quality analysis. Although this might seem to be a time consuming process, the end result will be a better understanding of the underlying data that is ultimately driving the key business decisions within your organization. In addition, the process of moving through the maturity model should provide an added benefit - increased collaboration between business and IT stakeholders within the organization.

Until next time…