Part I: Pragmatic Data Governance: Accountability and Trust

What is Pragmatic Data Governance?

In their Top 10 IT Issues, 2017, EDUCAUSE identified “data management and governance” as an issue to “improve…the management of institutional data through data standards, integration, protection, and governance.” We suggest the best way to consider data governance is through pragmatism, or practical solutions that consider the human and cultural elements of data use in higher education. Pragmatic data governance can be understood as a series of standard and controlled processes which give clear stewardship and responsibility to data definitions, reports and extracts, data requests, data quality, data access, and data system inventory.

In this series of four blog posts, we introduce 1. The importance of accountability and trust 2. Just-in-time data governance as a method to address the pace of data use, 3. The best practices for successful data reporting, and 4. Institutional cultural shifts occur when clear data governance practices are implemented. This post is about the first pragmatic solution.

In this post, we explore the relationship between accountability and trust.  We discuss trust and accountability together because they are linked: Data users distrust data when they do not trust the people who produce the data. In other words, trust is a critical element in data governance because it works like glue to hold together the processes and the people who work on those processes.

Lack of Trust and Data Governance

Lack of trust hinders data governance because it affects both personnel decisions and processes of data curation, analysis, and distribution. For example, lack of trust may include insufficient knowledge about the data, divisive politics between departments, and a deficit of resources and time. At the personnel level, incomplete requirements and miscommunication, no clear process or ownership, and issues with access to the data can all hinder sound governance.

This means processes involved in analyzing, interpreting, using, and sharing data break down if the data is not trusted. Accountability is the necessary ingredient for trust in the data and in the persons who work with data.

Accountability and Trust

A culture of accountability is one in which people trust each other and the data that is produced and distributed. A culture of accountability uses technology but does not rely solely on it for transparency. Rather, communication, open collaboration, joint knowledge of the data and the process used to generate that data are all necessary to this culture. Combined with training and proper documentation, collaboration tools can clearly define data request processes. The people involved in this process, the owners and stewards of the data, help build and sustain an environment of mutual trust and transparency.

The Data Cookbook

Returning briefly to the notion that a culture of accountability may use technology, but not necessarily be dependent on it, the Data Cookbook helps bridge the human element with the technology. The applicability of the Data Cookbook is found in the functional and technical data definitions capability. This helps build trust because all parties in the workflow can see how words are understood in their various meanings and nuances. Similarly, the specifications capability helps generate reports and ETL (extract, transform, and load) processes. The Data Cookbook helps make clear the entire process for all stakeholders which builds trust in the process.

 

by James E. Willis, III, Brenda Reeb, and Brian S. Parish

 

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