Improving financial data quality through data governance

Abstract

Organizations around the world aim to become data-driven and derive competitive advantage of business data to succeed in the challenging environment. Data is viewed as an important resource and an asset in companies but the quality of data is often not paid enough attention to. In reality, organizations are often unaware of the quality of their data (O’Brien 2015, 443). The quality of financial data is especially important for companies because it is used in business decision making and external reporting. However, financial data in companies is rarely governed in the same way as other business assets.

The purpose of this research was to study how the quality of financial data can be improved by utilizing data governance to address data quality challenges. The theoretical framework is composed of data quality and data governance literature. The themes are first clarified separately and thereafter, a synthesis is made of them in the summary of the theoretical framework. The research was conducted as a qualitative case study in which a design-based research approach was used. The empirical data was collected from eight semi-structured interviews, where the case company’s employees were interviewed. The interviewees were selected from financial accounting and management accounting teams to represent the main stakeholders of financial data. The interview data was used to gain understanding of the data quality challenges and the current state of data governance in the case company. In addition, the interviewees were asked to consider their needs regarding the governance of financial data and the benefits they expect to gain from better governed data.

From the interview data, five main themes of challenges in the current state of the company were identified. The themes included management, roles and responsibilities, communication, internal conditions and technology related challenges. Due to these challenges, the requirements for data quality and the employees’ responsibilities regarding data were not clear which negatively affected the quality of financial data. In addition, decision-making authority had not been defined in the company which created a risk for data quality if several people were making decisions of the data individually. Because the identified challenges were mostly organizational instead of technical, data governance was seen as a suitable solution to address the challenges. Based on the identified challenges and the needs from the interviews, a data governance framework was developed for the case company. First, roles and responsibilities regarding financial data were defined. Then, data governance activities were designed to document the common principles for working with financial data and to enhance common understanding among data stakeholders.

The findings of this research imply that data governance can be used to improve the quality of financial data in organizations because it addresses the organizational challenges that negatively affect financial data quality. The research was restricted to studying a single company and the data governance framework was developed explicitly for the case company. Therefore, the findings of this research cannot be generalized to other organizations. However, this research contributes to the literature by increasing understanding of the challenges for financial data quality and utilizing data governance in the context of financial data. In addition, practitioners can use this research as a case example for designing their own data governance activities for financial data. For the case company, developing the data governance framework was the first step towards ensuring high quality of financial data. However, its effectiveness still highly depends on how well it is implemented and adopted.