Abstract
Knowledge Management and Predictive Analytics in IT Project Risks
Highlights
The predicament of IT projects today shows that despite the new technologies, new processes, and sophisticated systems today, IT development success is still lower than expected
This paper explores Knowledge Management (KM) combined with big data tools, predictive analytics, in identifying risk data in IT projects, and predicting which risks are most likely to happen
The study explored common practices of IT development risk prediction and how these can be improved with new tools using the predictive analytics and knowledge management
Summary
The predicament of IT projects today shows that despite the new technologies, new processes, and sophisticated systems today, IT development success is still lower than expected. Billions of dollars are being wasted because of project failures. The year 2013 has shown a stagnation of IT project success [1]. That year was the time the rate of success started increasing, there is still the need for IT projects to improve its success rate. The nature of IT projects is that the entire process entails high risks. Risks in IT projects are many, varied and the probability and impact of these major risks are mostly between low to high
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