Improving data quality in the preparation of shareholder identification report

Data quality is of high importance especially to Investor Relations where transparency enables companies to develop strong relationship with its investors. Thus, in case of manual data entry, human error is inevitable, and this could adversely affect the results of the analysis which could lead to making wrong decisions. This action research project aims to improve the quality of the data entered during the preparation of the Shareholder Identification report by reassigning roles to more experienced Junior Financial Analysts to check the disclosures that are manually entered by the less experienced Junior Financial Analysts in the report, and by conducting a more comprehensive training to the less experienced Junior Financial Analysts on the preparation of the Shareholder Identification Report. The data were generated from primary and secondary sources, and its authenticity was validated using the first, second, and third person skills throughout the action research cycles. The interventions were collaboratively facilitated through informal meetings, discussions, and one-on-one interviews. The conceptual frameworks used guided us in planning and implementing the interventions. And in order to assess the data quality in the Shareholder Identification Report, me and my collaborators used the Data Quality Dimensions, which illustrates the factors that has to be considered in assessing data quality. The strategies implemented within the two cycles of this action research have reduced the errors committed by the Junior Financial Analysts when it comes to misallocation of shares, duplicates and wrong report formatting. Moreover, overtime works were lessened, while the data quality checking scheme is kept in place. More importantly, this action research brought changes not only on the report, but it also empowered the team driven by the developments among the members of the team and change in myself