Date of Award

12-14-2020

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Information Science and Systems Engineering

First Advisor

John Talburt

Abstract

Organizations around the world are beginning to recognize data and information among their most valuable resources and assets. Just as any business asset, data requires thorough and deliberate care. Data governance is not new, but many organizations and companies finally realize it is a mandatory part of conducting successful business activities. Data governance is an essential part of a data strategy and data management program. Enacting data governance can help companies improve responsiveness, provide employees clarity around roles and responsibilities, and better-managed data assets. The results are more robust products, improved revenue, risk elimination, and fewer costs. Within the data governance strategy and program, the data policy is paramount. The data policy establishes the underlying principles and overarching governance, including the authority, control, shared decision-making, security, and legal/regulatory compliance to ensure that all data which a company owns, licenses, and manages produces the highest data quality and associated value possible. Without enforcement and measure, a data policy is powerless. In companies with 5,000 or more employees, establishing a data policy is not a simple achievement. And enforcing and measuring progress is an immense effort and should not be underestimated. Some of the biggest challenges include, but are not limited to the following: inauthentic support from the senior executive management team, competing priorities, inappropriate strategy and approach, unrealistic timelines, lack of communications plan and support, untested tools and technologies, undedicated team, and unclear examples of measures and metrics. In this action research dissertation, the London Stock Exchange (LSEG) serves as an example of a company pursuing data superiority through its data governance program and, consequently, data policy conformance. The researcher will describe, using narrative analysis, the program approach, processes, tools, data collection method, and thematic assessment analyses to understand enterprise data policy conformance. This study leverages a program, policy framework, and a set of policy and standard review processes with a study population close to 3,000 respondents within the company. This study's outcomes contribute to current body knowledge and information organizations of best practices around data policy conformance within a data governance program. Understanding the drivers of data governance, the need for a data policy framework, and the programmatic view and activities can provide visibility to understand further the measures and benefits of a program of this nature.

Download

Share

COinS