![]() A comprehensive literature review was done to understand maintenance analytics, types of data and its sources, and the analytical techniques applied. Therefore, this study aims to identify the various analytical techniques applied in existing maintenance analytics studies and determine the current direction of maintenance analytics studies. In a country like Malaysia where maintenance practice is not data-driven, there is a need to identify the techniques to improve the maintenance process (especially decision-making). ![]() It is used to determine “what has happened?”, “why it happened?”, “what will happen?”, and “what needs to be done?” to enable decision-makers to take appropriate actions. Maintenance analytics is a structured and technological approach used to extract information from data and has proven to be an acceptable tool to improve building operation and maintenance. Data-driven decisions improve building operations and create better predictive maintenance programs because the stakeholders can instantly identify problems and effectively act. This limits the building maintenance strategy to corrective (reactive) and preventive (expensive). The decisions are usually made based on the latest maintenance inspection without taking into consideration the trend of past data. ![]() ![]() Unfortunately, the decision-making process for building maintenance in Malaysia is still traditional. To improve the current state of maintenance, effective decisions must be made by the building stakeholders. There is a prevalence of poor building maintenance practices in both the public and private sectors in Malaysia. ![]()
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