Prime
On data driven decision making
What you need to know:
By innovating around data, NSSF has been able to predict customer demands and develop the personalised products we see today. This has kept NSSF ahead of the curve, and it is not by surprise that the Fund managed to hit its Shs 20 trillion target of Assets Under Management in February, one and a half years ahead of its 2025 schedule.
In today’s rapidly evolving world, data has emerged as a vital asset due to its immense value in driving strategic decisions across sectors. However, its true potential has only recently been recognised with the advent of technology and big data.
Big data refers to large datasets that can’t be analysed using traditional methods. It contains a variety of data types, including structured data stored in tables and unstructured data like text, images, and videos. While the volume, variety, and velocity of big data present an uphill challenge in extracting insights, they also present incredible opportunities that can drive significant improvements in strategy development.
In 2002, businessman Wyc Grousbeck and his partners acquired the Boston Celtics of the National Basketball Association (NBA). As part of their strategy to win the NBA championship, they hired PhD students to study data on the teams that had won the past 25 NBA championship titles. The students discovered a unique characteristic across all the teams, and this was the presence of a “Big Three.” In 2007, the Celtics assembled a big three of stars: Ray Allen, Kevin Garnett, and Paul Pierce, and one year later, the Celtics shifted from a 25-win, 58-loss record to a remarkable 66-win, 16-loss regular season performance, ultimately winning the 2008 NBA championship. Today, many NBA teams hire full time data scientists to enhance game strategies with statistical insights on the most efficient plays.
Beyond sports, data science is being fused with corporate governance, as seen with institutions like Uganda’s National Social Security Fund (NSSF). NSSF has built in-house solutions using artificial intelligence (AI) technologies like machine learning to generate insights from big data. Machine learning uses big data to train algorithms to develop models that can identify patterns, make predictions, and improve on their own. Through harnessing AI, NSSF has been able to make informed decisions, thus creating further value for its members. By innovating around data, NSSF has been able to predict customer demands and develop the personalised products we see today. This has kept NSSF ahead of the curve, and it is not by surprise that the Fund managed to hit its Shs 20 trillion target of Assets Under Management in February, one and a half years ahead of its 2025 schedule.
Given the above backdrop, it’s puzzling that in public health management, where human lives are at stake, it has been slow to adopt the use of big data, and yet the potential for generating this data is immense, given Uganda’s internet penetration of approximately 27percent (13.30 million Ugandans). This is a sufficient sample from which authorities responsible for Uganda’s public health can mine data upon which they can predict, mitigate, and avert public health disasters. For context, the average person generates over 1.5 megabytes of data every second they’re online.
By exploring data from health records, weather forecasts, environmental sensors, social media, population mobility patterns, and Google searches, authorities can identify trends and anomalies that signal potential health risks. Citing the most recent case of the Kitezi landfill collapse, if there had been data infrastructure to monitor real time data on waste accumulation, ground stability, and weather patterns, maybe a more accurate prediction of the day of the disaster would have been made. This would have sounded the drum louder, prompting preemptive action that could have saved lives.
To safeguard the well-being of Ugandans, it is imperative that big data analytics be integrated into the public health infrastructure, especially in the urban centres since they are most at risk. Just as data has revolutionised sports and corporate strategy, it holds a major key to building a resilient public health system, if well embraced.
Jimmy Muhangi Bakesi, Statistician
