Part II: Pragmatic Data Governance-Just in Time Data Governance

Part II: Pragmatic Data Governance-Just in Time Data Governance

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 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 (data intelligence) 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, controlled, and understood processes which give clear stewardship and responsibility. What is “pragmatically governed” includes data definitions, reports and extracts, data requests, data quality, data access, and data system inventory.

In part one of this series, we introduced the importance of accountability and trust to data governance. In part two, we discuss the idea of just-in-time (JIT) data governance as a method to address the pace of data use. In future postings, we will discuss the best practices for successful data reporting and the organizational shifts in culture that occur when clear data governance practices are implemented.

In this posting, we discuss a practical approach to implementing data governance directly into existing processes: just-in-time data governance. JIT is a form of pragmatism because it sets out a clear method to address the day-to-day issues of data governance. By empowering an individual to handle the daily issues that arise, data governance is streamlined, efficient, and transparent.

Committee Work and Data Ownership

In organizations where complex and far-reaching decisions must be made, committees make sense. Committees help bring together stakeholders, managers, experts, and constituents to make decisions collectively and collaboratively. Committees help account for different goals and agendas while helping to prevent serious errors.

The success of the committee is dependent on clear communication. For example, setting specific and clear goals allows the committee to define specific governance processes. The committee is also able to build buy-in for governing the data, which is particularly important when there are many stakeholders. The committee can also help secure funding for technology and personnel to carry out data protection. Finally, the committee can determine the points of escalation to leadership and arbitrate matters of dispute within the organization.

The Realities of Committee Work

Anyone who has worked on a committee, however, knows this is an ideal: committees are supposed to work this way, but often they do not. From group-think to petty politics, committees can be held back by the fact that they simply do not function in a vacuum. Committees tasked with data governance in a higher education context are not exempt from these criticisms. If anything, the relative safety of jobs in higher education means committees might move especially slowly.

Committees can certainly function to protect student data, but the problems of speed in decision-making, response to requests, and change in data definitions and reports may undermine governance activities. Committees can also inadvertently slow the process which can eventually deplete resources for reporting out the data, hinder the internal use of data to help students, and discourage the use of student data to improve operations.

However, it is important to highlight the good outcomes of committee work. Those serving as data stewards and data owners can be clearly identified, which is important when responding to specific requests. Such positions also require specific responsibilities, leading to clear oversight for specific sets of data. The clear assignment and tracking of data over time provide transparency and relevance for the committee.

Just-in-Time Data Governance

There is nothing inherently wrong with the activities of a committee engaged in data governance issues, but what is needed is a better way to work. Just-in-time data governance is a practical approach that implements data governance directly into existing processes. The JIT data governance process establishes a clear path for day-to-day decision-making spearheaded by one empowered individual or a small group. JIT data governance preserves the time and resources of committees for large-scale decisions. This means the day-to-day questions or requests for reports can be handled by one person without having to filter through a committee where the request can languish. The JIT approach can address the everyday questions asked on campus. 

Application to the Data Cookbook

The Data Cookbook by IData, Inc., the leading data governance solution in higher education, supports both the JIT and committee models.  The Data Cookbook uses customized workflows to manage a clear data request process, which streamlines both the initial need for a report as well as report delivery. These workflows organize the tasks for roles such as requester, report builder, and any approvals related to standards or governance oversight.  Data governance activities are built into workflows, allowing the recipient to trust the delivered report. The Data Cookbook complements the JIT and committee forms of data governance by setting out a transparent process where individuals can view, track, and follow up on processes from request to delivery.

Also check out our other just in time data governance resources in this blog post.

We would love to discuss data governance services and the Data Cookbook with you.  Feel free to Contact Us.

Check out the Pragmatic Data Governance Defined for Higher Education eBook

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

(image credit StockSnap_T8JB5N55MP_JITDGStopWatch_BP #1056)

Brenda Reeb
About the Author

Brenda is a consultant in data management, data governance, and the information needs of users. She has over 20 years' experience providing services and solutions in higher education. Brenda has designed and implemented data management policies, established workflows, and created metadata. She is an experienced advocate for data management at all levels of an organization.

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