On October 7th, 2024, Mr. Ernest Kpentey addressed an audience of developmental stakeholders like the Forestry Commission, Social Welfare Unit, Environmental Protection, Health Service, etc., sharing insights on a vital but often overlooked resource: administrative data. Sponsored by the Ghana Statistical Service, this session highlighted the power and challenges of using administrative data for statistical purposes, drawing attention to its value for policy-making, planning, and informed decision-making.

This was a two-day lecture held at the Twifo/Ati-Morkwa District Assembly Hall.

Mr. Kpentey opened by defining administrative data as information collected not for statistics but for routine administrative tasks, such as tax records, census counts, educational reports, and health data. While these data sources are foundational for government operations, Mr. Kpentey pointed out that administrative data often come with limitations that statisticians must recognize. “This type of data is not always complete or up-to-date, and it may contain errors,” he cautioned, emphasizing that such data needs refinement to be fully reliable for statistical analysis.

To improve data quality, Mr. Kpentey introduced a set of rigorous processes, including data cleaning, imputation for missing values, and validation checks. Through practical examples, he underscored the importance of “getting it right from the start.” These processes, he explained, involve identifying and rectifying inaccuracies, filling in missing information, and verifying data consistency.

An essential part of the training focused on data handover processes. When data is transferred between organizations, Mr. Kpentey said, maintaining data integrity and security is critical. Whether at the creation, collection, or storage stages, handover protocols must be clear and well-documented to prevent data loss or corruption.

The discussion then turned to the data lifecycle, a structured journey that takes data from its creation to its eventual destruction. “From collection to analysis and storage, data must be managed at each stage with great care,Mr. Kpentey noted, highlighting that handovers can happen at any step, underscoring the need for stringent security and accuracy measures throughout the data’s lifecycle.

Environmental health and data security were also on Mr. Kpentey’s agenda. “Data quality is not just about numbers; environmental factors like storage conditions play a huge role,” he explained, stressing the need for secure storage protocols to safeguard sensitive data and protect it from environmental degradation.

Mr. Kpentey further delved into data cleaning, validation, and acquisition processes. With examples, he illustrated the meticulous steps involved in obtaining data, validating it for accuracy, and cleaning it to remove errors. Each step, he argued, contributes to creating a dataset that meets the high standards required for effective statistical use.

A unique part of the training was a group exercise aimed at brainstorming strategies to improve data collection methods. Participants worked together to identify ways to standardize data collection, train data collectors, and use technology to automate processes. The ideas flowed fast, and Mr. Kpentey observed how such teamwork is essential to achieving meaningful change in the data landscape. “When we collaborate, we find better ways to ensure data quality and accuracy,” he said.

Technology, particularly Excel, was a focal point for Mr. Kpentey when discussing software tools. He demonstrated how workbook design, data visualization, and formatting in Excel can enhance statistical analysis, with special attention to data visualization as an essential tool for making sense of complex datasets.

Toward the end, Mr. Kpentey emphasized the roles and responsibilities within the administrative data ecosystem. He outlined the duties of data providers (who generate and collect the data), data users (who analyze and use it), and data custodians (who manage and protect it). Each role, he stressed, is critical to preserving data quality and security.

Key Takeaways for the Audience

Attendees left with several critical insights:

• Recognizing Limitations: Administrative data is valuable, but users must understand its limitations and refine it for accuracy.
• Improving Data Quality: Consistent quality control—through cleaning, validation, and acquisition processes—is essential for reliable data analysis.
• Streamlining Data Handover: Clear handover procedures safeguard data integrity during transfers between entities.
• Ensuring Data Security: Protecting data against both security breaches and environmental factors is crucial.
• Leveraging Technology: Tools like Excel play a valuable role in analyzing and visualizing data.
• Role Clarity: Understanding the responsibilities of all stakeholders ensures data is accurately collected, managed, and safeguarded.

The lecture by Mr. Kpentey offered a comprehensive look at the nuances of administrative data, from its origins to its critical role in statistical analysis. Attendees left with a reinforced understanding of data quality’s importance, the impact of careful data management, and the many ways technology can help. It was a valuable session, providing essential knowledge for anyone working with administrative data in Ghana and beyond.