‘Harnessing Data to transform Nigeria’s power’ – Adetumi Adewumi

Adetumi Adewumi, a business and data analyst with extensive experience in the U.S. and Nigeria. Her expertise in data-driven decision-making and operational efficiency has transformed organizations in the finance and energy sectors. In this interview, she speaks as a Nigerian in diaspora, addressing some of the key challenges facing the Nigerian power sector.

Can you give us a specific example of how your data and analytical skills can be applied to a challenge in Nigeria?
Let’s take the energy sector as an example, where I’ve had relevant experience. At the Transmission Company of Nigeria, I worked as a Data Analyst and focused on customer retention and operational efficiencies. Here in the US, I gained extensive IoT experience while working at Spacebot, a company centered on IoT technologies. Nigeria has been grappling with issues like inconsistent power supply, operational inefficiencies, and financial mismanagement. These are areas where my skills in data analytics and predictive modeling can make a tangible difference.

One solution I would propose is leveraging advanced analytics and predictive maintenance systems for infrastructure like power grids. By using IoT devices to monitor equipment and machine learning algorithms to predict when maintenance is needed, we can prevent system failures and reduce downtime. This approach (which is widely used in industries in the U.S), can optimize the maintenance schedules for critical infrastructure in Nigeria and save costs in the long run by reducing emergency repairs.

That’s a serious issue-power outages continue to hamper both business operations and everyday life. Can you elaborate on how predictive maintenance could address this?
Absolutely! Predictive maintenance uses real-time data to monitor equipment and forecast potential failures before they occur. Instead of relying on reactive maintenance where you wait for something to break down before fixing it you use sensors and data to predict when maintenance is needed, preventing breakdowns before they occur.

In Nigeria’s power sector, this could be applied to critical infrastructure, such as transformers, turbines, and power lines. By collecting data from IoT sensors, we can monitor the performance of these assets continuously. The data could provide insights into temperature fluctuations, vibration patterns, and energy flow, all of which help predict when a piece of equipment might fail. For example, if a transformer is overheating more frequently, it could indicate that it’s nearing failure. Maintenance teams can then intervene before the transformer breaks down, which would prevent outages and save the cost of emergency repairs.

Implementing predictive maintenance across the power grid could drastically reduce the frequency of unplanned outages and extend the lifespan of equipment. This would not only improve service reliability but also reduce costs associated with emergency repairs and downtime.

How can data analytics be used to address some of the financial challenges in the sector, especially concerning distribution losses?
Financial mismanagement and distribution losses are key pain points in Nigeria’s power sector. Many times, electricity theft, inefficient billing systems, and technical losses result in revenue leakage, meaning distribution companies are unable to recover the full cost of electricity supplied. This contributes to the financial instability of the entire power value chain.

Data analytics can help in two ways. First, by using advanced metering infrastructure (AMI), data on energy consumption can be collected in real-time. With smart meters installed at consumer locations, Distribution companies can monitor electricity usage more accurately, detect any discrepancies, and identify cases of electricity theft or illegal connections. Analyzing the data from these meters can also help detect irregularities in power consumption, which may signal tampering or inefficiencies in the grid. Second, data-driven financial models can be used to optimize billing processes. In many cases, billing systems are outdated, leading to inaccurate billing and poor customer trust. Data analytics can streamline the billing system by ensuring that customers are charged accurately based on their actual consumption, rather than estimated usage. This not only improves revenue collection but also builds consumer confidence in the system.

Given the global focus on sustainability, how can data analytics contribute to Nigeria’s energy transition, especially towards renewables like solar?
Renewable energy is definitely the future, and Nigeria has vast potential when it comes to solar energy, particularly in its northern regions. Data analytics can play a crucial role in optimizing the deployment and management of renewable energy projects.

One key challenge with renewable energy is variability—solar power generation depends on sunlight, which can fluctuate throughout the day. By leveraging weather forecasting data and integrating it with solar grids, we can create predictive models that optimize energy storage timing and capacity, ensuring a more reliable supply.

Furthermore, data from solar farms can be analyzed to determine which areas are most efficient in terms of energy production. This helps in decision-making about where to deploy additional solar infrastructure. For example, satellite data combined with machine learning algorithms can be used to predict solar irradiance levels in different regions, allowing energy planners to strategically invest in areas with the highest potential for solar power generation.

On the demand side, data analytics can help balance energy supply with consumption patterns. Predictive models can forecast electricity demand across different region of the country, enabling renewable energy to be distributed more effectively and ensuring that supply meets demand without overburdening the grid.

What do you think are the biggest barriers to implementing these solutions in Nigeria?
There are several barriers, but I believe the biggest ones are the lack of investment in technology, data infrastructure, and capacity building. Implementing predictive maintenance or smart metering systems requires significant investment in hardware, software, and expertise. Many of Nigeria’s power companies are still using outdated infrastructure, and upgrading to more modern, data-driven systems is a capital-intensive endeavor.

Another challenge is the lack of skilled personnel to manage and interpret the data. While there are many bright minds in Nigeria, the data analytics field is still growing. There needs to be a concerted effort to build capacity through training programs and partnerships with international organizations to develop the talent needed to implement these solutions.
Finally, regulatory support is crucial. The government needs to create policies that encourage the adoption of advanced technologies in the power sector, incentivizing investments in data infrastructure and renewable energy projects. Public-private partnerships could also play a key role in driving these changes forward.

As someone in the diaspora, how do you see yourself contributing to these solutions moving forward?
Being part of the diaspora allows me to bring a global perspective to local challenges, and I believe that knowledge transfer is key. I’m passionate about collaborating with Nigerian energy companies and government agencies to develop data-driven solutions. Whether it’s through consulting, capacity building, or fostering partnerships between Nigerian and international companies, I’m committed to contributing my expertise to help Nigeria’s power sector overcome its challenges and achieve sustainable growth.

The vision is for a more efficient, reliable, and sustainable energy sector in Nigeria, powered by data and technology. The potential is there, and with the right investment and strategic direction, I’m confident that Nigeria’s power industry can be transformed.