Why Data Governance is Crucial for Public Sector Success

By John Walubengo

Imagine visiting a new city that has no map, has street signs missing, roads changing names without notice, and there is no one to guide you. I suppose that would be very scary and chaotic. That’s exactly how navigating the data landscape within a government agency would feel like – without proper data governance.

The key data required might be out there, but finding it, trusting it, or using it effectively to serve the public becomes a formidable challenge.

In today’s data-driven society, data governance is not just a critical requirement—it is essential for delivering public services efficiently, maintaining public trust, and ensuring compliance with laws and regulations.

Without it, government agencies can quickly find themselves entangled in a web of data-related problems that can undermine their operations and mission to serve the public.

In this first part, we break down some of the four elements of a data governance program and explore what happens when those elements are missing in a government ministry, department or agency.

Data Discovery: Unearthing Valuable Public Data

Data discovery is the process of identifying, locating, and evaluating the data assets spread across government departments and agencies. It is like creating a detailed map of the agency’s data landscape so that one gets to know what data they have, where it’s stored, and how it can be used to serve the public.

Imagine a scenario where different government ministries—like health, education, agriculture and transport—are working on initiatives to improve public services, but are unaware of the valuable data held by one another.

Without data discovery, each department operates in silos, leading to duplicated efforts, increased costs, and missed opportunities to collaborate on more comprehensive solutions.

For instance, if the education ministry does not know that the health department has data on vulnerable and malnourished children, a program aimed at improving public sector education outcomes may fail due to overlooking these critical health needs. This lack of coordination can hinder the effectiveness of public services and waste taxpayer money.

Data Catalogue: The Government’s Data Index

Once the critical data sets have been discovered, they need to be arranged in an easily accessible way. A data catalogue does this by providing a portal, of a well-organized inventory of data assets across government ministries and agencies.

It provides descriptions, locations, and metadata for each data set. It is a directory that would help government employees quickly find and access the data they need to serve the public effectively.

Imagine a scenario where government employees are spending hours searching for specific data sets to make important decisions, only to give up because they do not know where to look or if the dataset exists.

Without a data catalogue, valuable data may go unnoticed and unused, simply because no one knows if it exists and if so, where and how to access it. This can lead to inefficiencies and delays in delivering public services.

For example, crucial data that could help improve public safety or enhance social services might be sitting in an overlooked database, in some unknown ministry or agency and unused due to lack of visibility or awareness.

The absence of a data catalogue hampers the government’s ability to respond to public needs efficiently and make data-driven decisions that benefit society.

Metadata: Understanding the Story Behind the Data

Once the data catalogue guides the employee to the dataset they may be seeking, the employee needs to appreciate the context of that data, especially because it may have been shared or imported from a sister ministry or agency.

The Metadata comes in to provide this background information and describes the content, context, and structure of data assets shared within the public sector. It is like the footnotes that explain where the data came from, who created it when it was created and how best it should be used.

Imagine a scenario where a government agency is trying to make policy decisions based on data, but they can’t determine whether the data is up-to-date or relevant.

Without the metadata, understanding the context of the data becomes a guessing game. For example, if a health department pulls a report on disease outbreaks but the report lacks metadata, they might not know when the data was last updated or if it includes all necessary variables. This can lead to incorrect conclusions, poorly informed decisions, and ineffective public policies.

Data Policy: Establishing the Ground Rules for Public Data

We conclude with what we probably should have started with – data policies. A data policy is a set of guidelines and rules that govern how data should be created, managed, accessed, used, and protected within government agencies. It ensures that everyone from top officials to front-line workers is on the same page regarding data handling.

Without a clear data policy, different government departments might adopt their inconsistent data management practices.

For example, one ministry or department might be diligent and rigorous about their data quality and security, while another might be relaxed or laid-back on the same, leading to data that is unreliable or even compromised. This inconsistency can cause significant issues when their data needs to be shared across departments or used to inform policy decisions.

Additionally, the absence of a unified data policy increases the risk of data misuse—employees might inadvertently share sensitive data with unauthorized parties or fail to comply with legal requirements, resulting in privacy breaches and public outcry.

There are a few other important data governance elements like the data dictionary, business glossary, and data classification but we can tackle them next week.

John Walubengo is an ICT Lecturer and Consultant. @jwalu.