Challenges in implementing Data Governance Program

Let’s not mince words: Data Governance plays a pivotal role in ensuring data quality and security within organizations, as well as enabling compliance with relevant data regulations. The benefits of effective Data Governance are crystal clear. [For instance, consider reading the Whitepaper “Data Governance the foundation for building a successful datamanagement strategy ” by our Tentive colleague Karel Siemerink, which extensively delves into these benefits.] However, before an organization can boast of a well-implemented and well-maintained Data Governance program, it typically needs to navigate through various hurdles to reach that stage. In this blog, we’ll describe three examples (or rather, challenges) that organizations may encounter during the implementation process and actual execution.

1. Lack of data-driven leadership.

A significant challenge organizations may face is the absence of strong data-driven leadership. Successful Data Governance initiatives require robust leadership to guide the program. Not only does this establish clear policies, but it also transparently and unequivocally communicates the importance of Data Governance to other leaders within the organization. The data-driven leader, often referred to as the Chief Data Officer (CDO), has the important task of steering the Data Governance team. Additionally, the CDO must ensure alignment with business objectives and, where necessary, enforce accountability. Without effective data-driven leadership, a Data Governance program will not receive the attention it deserves. The risk of costly failure in such cases is nearly inevitable

2. Emergence of data silos

Over time, data tends to become isolated and fragmented. This occurs when different business units or functional areas develop new data sources and utilize various technologies. These so-called ‘data silos’ hinder data integration as a collection of information within the silo becomes isolated from the rest of the organization. Consequently, accessing, analyzing, and utilizing data across the entire organization becomes difficult or even impossible. Addressing these data silos presents a persistent challenge within a Data Governance program, requiring coordination, data integration, and cross-functional collaboration.

3. Lack of resources

Data Governance initiatives often struggle due to inadequate investments in terms of budget and personnel. However, it is crucial that Data Governance is owned and funded by someone within the organization. The problem, however, is that it is rare for the Data Governance program to directly generate visible income. [Which is somewhat remarkable, considering, for example, that IBM estimated as early as 2016 that the annual costs of poor data quality alone in the US amounted to 3.1 trillion (!) dollars. So, if an organization assumes it doesn’t have bad data, it probably hasn’t found it yet.] The investment required for a robust Data Governance program includes personnel, technology, tools, and ongoing support. Many organizations underestimate these costs. This can hinder the development and sustainability of Data Governance efforts.

Conclusion

Effectively tackling the challenges within Data Governance programs requires a strategic approach, commitment, and collaboration across the entire organization. However, don’t forget, successful Data Governance programs are crucial for enabling organizations to maximize the value of their data assets and make informed decisions based on high-quality, well-managed data.

Tentive Data Management Consultants

The consultants at Tentive have extensive experience in data governance and are ready to support your organization in this area. If your organization is interested in getting started, we invite you to contact us. We are available for a non-obligatory conversation.