At a global summit on climate change last summer, I attended a workshop run by Ghanaian entrepreneur Peter Benhur Nyeko. Unlike many of the luminaries at the event, he argued that the path to sustainable energy was not a one-size-fits-all proposition; many countries, for political and economic reasons, could not simply “turn off the tap” regarding fossil fuels. While Western solutions often prioritize centralized energy grids, Nyeko’s discussion demonstrated the importance of decentralized solutions like off-grid lighting in regions where traditional infrastructure is lacking. This emphasis on decentralized solutions rooted in local contexts underscores the significance of data-driven research in redefining energy strategies. I understood at that moment that the typical understanding of energy issues was culturally bound — the West believed whatever “worked for us” would work for everyone else. Yet Western leadership on this issue could, in some places, deepen climate injustice. How, in this diverse, disagreeing world, do you recognize and account for every interest, for every point of view? And when interests conflict, how do you choose between them? Achieve some rough justice, where difficult problems are solved, with the cost spread fairly, if not equally?
Those questions have been around for centuries, and will never be solved to everyone’s satisfaction, but modern technology — massive computing power, artificial intelligence, incomprehensibly large data sets, scientifically valid algorithms — at least means we can ask them with reams of evidence at our fingers. Data analysts have a better chance, today, at correctly predicting the future —and suggesting what went wrong in the past. The topics they analyze are diverse, but they share an approach and methodology — the idea that data, utilized properly, can highlight systemic errors in standard practices, and show a path toward greater efficiency and equity. Utilizing off-grid lighting solutions as a microcosm, we can delve deeper into how data-driven operations management can transform traditional energy paradigms and address challenges specific to underserved regions like Sub-Saharan Africa.
One such analyst demonstrating this approach is Wharton’s Professor Serguei Netessine, whom I interviewed by email while researching “energy poverty.” Professor Netessine has contributed to numerous scholarly articles concerning energy issues — swapping out batteries on electric vehicles rather than waiting for a recharge, the economic trade-offs between renewable and non-renewable energy, optimizing investment in the face of uncertain demand, and so on.
The highly regarded “Foreign Policy” magazine recently published an article concluding that “rich-world advocates and policymakers should realize that their demands for immediate fossil-fuel abstinence are very likely to perpetuate the extreme poverty that many Africans face today.” Professor Netessine agreed with that assessment, believing that a more nuanced approach is necessary to address energy poverty sustainably. His notable work in Sub-Saharan African countries like Ghana and Rwanda focused on revolutionizing off-grid lighting solutions for underserved communities. Collaborating with a local rechargeable lamp operator in Rwanda, Netessine and his team proposed practical strategies to address operational inefficiencies of these energy sources, such as expanding the network of recharge centers and implementing flexible payment options. In the paper titled “Design of Off-Grid Lighting Business Models to Serve the Poor,” his team explored how inconvenience and liquidity constraints affect the usage of rechargeable lamps, a popular off-grid lighting solution in developing regions. Netessine’s findings shed light on the potential of off-grid renewable energy sources to combat energy poverty in Africa and beyond by emphasizing the importance of effective operations management tailored to cash-constrained markets.
Data-driven operations management encompasses the strategic utilization of data to inform decision-making processes across various operational facets. This involves collecting data from multiple sources, including consumer behavior patterns, operational performance metrics, and market dynamics. By leveraging advanced analytics and artificial intelligence algorithms, this data can be analyzed to gain insights into the effectiveness of current operational practices and to identify areas for improvement. Professor Netessine and his team, in their research conducted in Rwanda, exemplified this approach by analyzing consumer behavior and operational inefficiencies related to off-grid lighting solutions. For instance, data on consumer recharge behavior can inform the optimal placement of recharge centers. In fact, the paper shows that lowering the price for recharges (a typical tool recommended in third-world countries to increase adoption) is not nearly as impactful as a simple operational decision of collecting lamps door-to-door and recharging them. Ultimately, data-driven operations management enables informed decision-making that enhances the efficiency, scalability, and impact of off-grid lighting initiatives in addressing energy poverty in sub-Saharan Africa.
I agree with Professor Netessine’s approach that emphasizes data-driven solutions and evidence-based strategies, and I think a key component of solving energy poverty involves the political will of the developed world. Economic giants like the U.S. and Germany prioritize investment in African infrastructure, particularly in renewable energy sources such as solar and hydropower. Africa’s transition to renewable energy aligns with global decarbonization efforts and presents significant economic opportunities. By investing in renewable energy projects and supporting Africa’s capacity to produce essential components of the zero-carbon energy economy, the developed world can play a pivotal role in promoting sustainable development and combating climate change. This approach not only addresses immediate energy needs but also lays the foundation for long-term economic growth and sustainability across the continent.
The proper use of data, deployed in properly thought-through systems, can revolutionize business models in tackling energy poverty, particularly in African countries like Ghana and Rwanda. By embracing data-driven solutions advocated by thought leaders, we can effectively address energy poverty and promote resilience and prosperity in underserved regions. Leveraging innovative approaches informed by robust data analytics empowers communities to access reliable and affordable energy sources, paving the way for inclusive development and a brighter future for all.
