The Ministry of Health has launched a new project called Data Production Management and Use (DPMU).

The project is being implemented with financial support from the Global Fund and technical assistance from Systems for Development (S4D).

The project aims to assess the end-to-end public health supply chain, identify key sources of data, ensure the people, processes and tools that facilitate the exploitation and management of data to each operational process meets the minimum standards.

Additionally, the project will help develop support mechanisms that will not only view data as a business asset, but use it effectively in all decision-making and performance monitoring.

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The Ministry’s Research and Information Management Branch will champion this task to achieve the objectives.

However, S4D will leverage its technical capabilities and resources to develop the public health supply chain data architecture which has been categorized into three key areas: data management, data integration, and data architecture. data analysis, to help the ministry.

It is expected that fostering such an enabling supply chain environment will drive Ghana towards achieving the health-related Sustainable Development Goals (SDGs), including Universal Health Coverage (UHC).

The impact of the project has been classified into three parts. These are cost savings, operational efficiencies and information.

Cost savings

As part of this, data will guide the implementation of strategic supply chain financial methods and decisions, creating opportunities to achieve supply chain profitability.

Accurate and timely inventory data will inform budgeting, procurement, inventory management, and distribution processes while helping to effectively target supply chain investments, reduce waste, and ultimately to better meet patient needs.

Operational efficiency

Thus, data visibility combined with strong data management will help reduce operational costs and improve service levels by optimizing processes such as purchasing planning, demand forecasting and inventory management.


Additionally, the availability of quality data will create an agile supply chain, enabling more informed value-based decisions and proactive risk management efforts.

Leveraging data visibility and analytical tools such as probabilistic and predictive modeling will facilitate the establishment of mechanisms for supply chain risk management methods such as scenario building, assumptions and risk/reward analysis.