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A researcher, Femi Esan, is examining how information systems, predictive analytics and artificial intelligence can be used to identify risks and support decision-making in organisations.
The research focuses particularly on healthcare and other public-service environments where decisions are often made with limited resources and incomplete information.
Esan’s area of study considers how data from different sources can be combined to provide information about emerging risks.
In healthcare, for instance, patient numbers alone may not provide sufficient information about pressure on a facility.
Other factors, including staffing levels, medicine availability, referral patterns and facility capacity, can also be considered when assessing operational risks.
The research also examines the use of explainable artificial intelligence, which allows users to better understand the factors behind predictions or risk assessments generated by AI systems.
This can be relevant where AI-generated information is used to support decisions involving patients, public services or the allocation of resources.
Another aspect of the research concerns risk management and the limitations of predictive models.
Rather than treating predictions as certain outcomes, the approach considers them as information that can be used alongside other evidence when assessing possible developments.
The issues being examined are not limited to healthcare.
Similar applications can arise in areas such as emergency response, education, social services and infrastructure management, where institutions handle large amounts of information while making decisions under resource constraints.
The research is centred on how organisations can use available information to determine what has happened, identify possible causes, assess what could happen next and decide what action may be required.
Esan’s academic background includes mathematics, strategic management, data analytics and information systems, areas that have informed his research into data-driven decision-making.
