Data-Driven Optimization of Plumbing and HVAC Business Management through Predictive Analytics
Year: 2025
Type: article
Abstract: This article explores the use of predictive analytics to enhance operational efficiency in the household services sector, with a particular focus on plumbing and HVAC businesses. The study provides a broad examination of existing methods and frameworks, while also incorporating practical company case studies to illustrate real-world applications. It outlines the key stages of implementing predictive analytics—from data collection and model development to integration into business processes—and highlights how these tools can optimize resource allocation, streamline inventory management, and support proactive maintenance strategies. By analyzing both theoretical models and industry practices, the article demonstrates how demand forecasting and equipment failure prediction can lower costs, increase reliability, and improve customer satisfaction. The findings offer actionable insights for service company executives seeking to shape digital transformation strategies and make informed decisions about adopting data-driven technologies.
Author: Bekhruz Nagzibekov
Language: English
Subfield: Management Information Systems
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4415212814
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