A real-time approach to strengthening data systems in emerging economies

Pelumi Sowemimo

In response to persistent delays in institutional responsiveness and decision-making across low- and middle-income countries, a new publication titled Optimizing Real-Time Analytics offers a forward-looking framework for integrating real-time data capabilities into public infrastructure, governance systems, and development planning. Authored by data scientist Ibrahim Olushola, the book presents a comprehensive strategy for enabling faster, smarter, and more adaptive decision environments.

The book arrives at a moment when many developing nations are investing in digital transformation but continue to face structural barriers that hinder the practical use of data.

These challenges include unreliable data pipelines, limited inter-agency coordination, outdated monitoring frameworks, and a lack of technical pathways for real-time insight generation. Optimizing Real-Time Analytics addresses these issues by proposing a layered system of institutional reform, operational redesign, and technical adaptation tailored to the constraints and priorities of emerging markets.

Organized into several thematic sections, the publication explores the strategic value of real-time analytics for improving decision velocity in sectors such as public health, agriculture, infrastructure, urban mobility, and financial systems. It outlines design principles for building end-to-end real-time systems, from data acquisition and stream processing to dashboard deployment, alert systems, and automated responses, emphasizing modularity, reliability, and contextual fit.

Early readers of the book; including officials from planning ministries, public-sector innovation units, and international development agencies—have cited its relevance to ongoing efforts aimed at modernizing government workflows and embedding data into operational cycles. Since publication, Optimizing Real-Time Analytics has been referenced in regional forums focused on open data strategies, digital public infrastructure, and real-time monitoring initiatives across Anglophone West Africa.

Beyond its public sector applications, the book also speaks to enterprise data teams and civil society organizations working in unstable or data-scarce environments. It examines how real-time systems can support adaptive management, field-level coordination, and improved service delivery, particularly in sectors where conditions change rapidly and decisions must be made with incomplete information.

Drawing from his experience in applied data science, Ibrahim Olushola grounds the book in both conceptual frameworks and practical considerations. His approach blends strategic systems thinking with deep technical clarity, offering pathways for institutions to transition from static, report-driven models to continuous, insight-informed operations.

Throughout the text, emphasis is placed on flexibility, sustainability, and the long-term cost-effectiveness of real-time investments.

Several academic institutions have begun integrating portions of the framework into courses on public data management, digital transformation, and development systems engineering. Technical organizations and regional bodies are also reviewing elements of the book for adaptation into cross-border digital policy cooperation and early-warning infrastructure.
Optimizing Real-Time Analytics contributes to the growing body of work on how developing countries can build data systems that not only capture the present but anticipate the future.

Its insights are practical, timely, and grounded in the realities of where institutional ambition meets implementation constraints—making it a valuable resource for governments, organizations, and professionals working at the intersection of technology, governance, and development.