Enhancing Water Park System Operations with Predictive Analytics

Abstract

Water parks are one of the most sought-after recreational spots, with millions of visitors each year. Yet, it is a difficult task to manage water parks effectively as there are varying numbers of visitors, seasonal effects, machinery wear and tear, and heavy operational expenses. Historically, water park operations were dependent on reactive management strategies, which in turn result in inefficiencies and less-than-ideal customer experiences. With the advent of big data and advanced analytics, predictive analytics emerges as a game-changing tool that enables water park operators to predict and mitigate operational issues before they crop up.  It identifies pertinent literature, suggests data-centric methodology, and discusses real-world applications like attendance prediction, preventive maintenance, queueing optimization, and revenue optimization. It then concludes by discussing future paths and the extent of integrating emerging technologies to create intelligence-enabled and more sustainable water park systems.