Data Governance Challenges at Dutch Financial Services Firms

Abstract

In 2006 already, Clive Humby said: “Data is the New Oil!” and like oil, data needs “infrastructure” to be gathered, analyzed and used. This infrastructure is called data governance and it is essential in today’s data-driven era to ensure availability, quality and security of an organization’s data. This is especially true for financial services firms, which deal with massive amounts of highly-sensitive personal data, such as names, dates of birth and bank details, and operate in a highly regulated environment. Therefore, it is essential that any new data governance policies, such as a transition to a cloud-based data governance policy, are implemented as quickly and efficiently as possible. Research thus far has primarily focused on the importance of data governance and developing data governance models. However, the implementation of data governance proves to be not without its barriers. Some research has been done into what barriers organizations encounter when attempting to implement new data governance policies, but strategies to deal with these barriers have not been found in existing literature. Therefore, this research seeks to answer the question:

“How do managers at financial services firms in the Netherlands deal with the barriers to successfully implement new data governance?”

This thesis used a literature study, twelve individual interviews with PwC employees who were heavily involved in data governance implementation processes at financial services firms in the Netherlands and a focus group interview with experts from PwC to determine what barriers financial services firms face when they are implementing new data governance, which strategies they use to deal with these barriers and what key factors influence the decision-making in this implementation process. These three elements were then used to find the answer to how managers at financial services firms in the Netherlands successfully implement new data governance.

The research attempts to close the gap in the literature surrounding the general strategies that are used to navigate the barriers that inhibit (new) data governance implementation. Furthermore, it can help further identify which barriers (financial services) firms face when attempting to implement new data governance and aid in the development of more effective data governance framework. Additionally, the improved understanding of how financial services firms navigate the barriers that inhibit data governance implementation can help maintain trust in financial services firms and the financial system as a whole and it can aid in the development of more effective regulatory frameworks to increase how fast financial services firms are able to comply to them.

The barriers financial firms face to implementing data governance that were found in this thesis were sorted into four broad categories: “Organizational culture/structure”, ”Senior management priority”, ”IT performance” and ”Lack of information”. Examples of these barriers are: a “restrictive mindset”, “unfocused strategy”, “incompatible IT systems” or a “lack of information on technoliii
ogy”. The strategies the firms used to deal with these barriers were also sorted into four different categories: “Senior management vision/championing”, “Technological tools/skills”, “Stakeholder involvement/consensus” and the “Business case” strategy. Examples of these strategies are: “developing a global vision”, “standardization of technology”, “stakeholder involvement” and “building a broad business case”. A complete overview of the barriers and their corresponding strategies that were found in this thesis can be found in figure 4.1...