Data Governance Planning Document for Enterprise Systems

Introduction and Governance Overview

Our organization's major functions include collecting large volumes of data through automated systems covering customer utility, supplier records, and customer account information. While some data are used in aggregate form, other data are cross-referenced with GIS (Geographic Information System) data. These data represent the organization's strategic critical infrastructure assets and require effective protection to maintain data integrity.

The objective of this report is to develop a data governance planning document that provides information pertaining to customers, operations, supply chain partners, and production facilities.

Data governance refers to the overall usability, integrity, availability, and security of data within an organization. A sound data governance program encompasses the policies and strategies needed to make data consistent, secure, accurate, and available in order to accomplish organizational objectives (Thomas, 2010). Effective data governance allows an organization to save money and reuse data to support analytical decision-making. The data governance framework also assists an organization in effectively managing its data assets. The policy document is critical to establishing a clear understanding of the layout and intent of our data governance program.

Data Governance Policy Template

A data governance policy is a living document that sets guidelines to ensure the proper management of an organization's digital information. Such guidelines include policies for BPM (Business Process Management), data security, privacy, and data quality (Duvall, 2011). The data governance policy is implemented to ensure data accuracy, consistency, protection, and accessibility (Illinois State Board of Education, 2011). A data governance policy must be updated regularly to meet the changing needs of an organization.

This data governance policy establishes a framework of guideline standards to be followed in data storage and access mechanisms. Our organization will exercise control over and access to data to enhance the integrity and security of its information. To support all aspects of operations, all organizational data will be managed as a strategic asset in accordance with established governance procedures.

In accordance with Public Records Law and the Data Protection Act, all personnel must abide by the rules and regulations pertaining to company data assets. It is the responsibility of all personnel to protect company data from theft, misuse, and alteration. All personnel must follow the policies and legal statutes relating to company data assets.

Data stored in the organizational information system are the property of the organization. Access to those data must be consistent with applicable ethical and legal policies.

Organizational data must be protected from deliberate, unauthorized, or unintentional destruction, alteration, inappropriate use, or disclosure. All data stored in electronic format must be protected using appropriate electronic safeguards and physical access controls to restrict data access to authorized agents only.

Data retrieved from corporate assets must be appropriately protected to ensure integrity and availability. All data retrieved in electronic format must not be altered in any form, in order to maintain continuous integrity. All data taken from corporate data assets must be encrypted before being transferred offsite to safeguard data security.

Data Governance Corporate Working Group

A best practice for successfully implementing data governance is to foster collaboration between business leadership and IT management to design and refine the future state of the data governance program. The major benefits of selecting an efficient and effective working group include ensuring that solution-minded leaders are engaged to resolve data governance issues. The group will also be able to address critical issues related to privacy, security, and compliance.

Our data governance corporate working group will consist of an Executive Sponsor, a Data Quality Leader (DQL), a Data Governance Board, an Executive Steering Committee, and an Enterprise Data Architect (Berson & Dubov, 2007). The roles, responsibilities, required skill sets, and time commitments for each position are described below.

The Executive Sponsor sets the initial goals and direction for the program. This role approves the tracking of progress and information policy, and compares quality initiatives against the target plan. The Executive Sponsor requires respected and recognized leadership ability, line-of-business (LOB) expertise, and a proven ability to manage multiple functions such as governing, enforcing, and arbitrating governance policies. Time commitment is less than 5%.

The DQL provides day-to-day leadership over the Data Quality Management (DQM) program. Responsibilities include ensuring the execution of policies and strategies with the Steering Committee and Data Governance Board, prioritizing and reviewing projects to determine funding needs, and providing scorecard feedback to all parties involved. The DQL requires significant data management expertise and the ability to engage deeply in all aspects of the program, including participation in both the Executive Steering Committee and the Data Governance Board. This is a full-time role.

The Enterprise Data Architect delivers a single point of architectural coordination for all approved data-related initiatives. Responsibilities include planning infrastructural efficiencies, overseeing data usage, linkage, and implementation, ensuring compliance with data governance requirements, and managing the maintenance, reconciliation, and re-creation of data design. Required skills include strong IT knowledge, solid data analysis capabilities, mining and migration experience, and strong technical writing and presentation skills. This is a full-time role.

This group serves as a liaison between business leaders and IT to achieve data quality, data management, and process and data element alignment. Members play various data management support roles, including metadata lead, data quality lead, data architect, and enterprise architect. Required skills include leadership and communication skills, data governance expertise, the ability to work and make decisions within a team, strong IT knowledge, a basic understanding of data modeling, solid data analysis skills, mining and migration experience, and strong technical writing and presentation skills. This is a full-time role.

The Data Governance Board monitors progress and develops the overall strategic plan for enterprise-wide data quality improvement. It approves sponsors, prioritizes and champions data quality initiatives, ensures resource and scheduling allocation, provides data quality progress feedback, and communicates with business segments to align data quality expectations and initiatives. Required competencies include effective data governance leadership, knowledge of industry practices, strong data governance expertise, excellent communication skills, and proficiency with collaboration tools such as WebEx, SharePoint, and wikis. This role requires quarterly participation and ad hoc meetings as needed.

The Executive Steering Committee is responsible for developing data policies and quality strategy, and for providing leadership and supervision over the overall program. Responsibilities include delivering periodic data quality updates to senior management, estimating high-level funding needs, requesting budget from the Executive Sponsor, and approving data quality initiatives. Required qualifications include recognized leadership ability, LOB expertise, and a proven ability to manage multiple governance functions including enforcing policies, governing, and arbitrating. This role requires monthly participation.