Predictive Analytics for E-Governance in Developing Economies: Applications, Readiness, and Institutional Challenges

Abstract

Predictive analytics is the process of using past and current data to predict what might happen in the future and to help make decisions. This approach has become a part of e-governance systems all around the world. For countries that are still developing predictive analytics provides a way to skip over time-consuming ways of managing government work. It helps governments see what services people will need find cases of fraud focus help where it is needed most and use public money more wisely. This paper looks at what predictive analytics how it works in e-governance. It also checks where it is being used to improve services and make better policies. The paper also looks at the probabilities and problems that developing countries face when trying to use analytics. These include missing data systems, weak government abilities and not enough trained people. A comparison shows the differences between predictive and prescriptive analytics and how each fit into government work and how ready they are. Another comparison looks at how ready different countries are to use these tools. The paper ends by saying that predictive analytics can really help e-governance in developing countries. This only happens if there is long-term support, for better data systems, stronger government abilities and better ways to manage the data properly.