Maintenance Matters Focus on: CMMS 18 | Plant & Works Engineering www.pwemag.co.uk Annual Buyers’ Guide 2025 Unlocking the power of CMMS As 2024 ends, UK industrial facilities face CMMS challenges, from technology integration to workforce shortages. Overcoming these requires strategic upgrades, data management, and skilled training to unlock CMMS’s full potential. PWE reports. One of the most significant trends affecting Computerised Maintenance Management Systems (CMMS) in UK facilities is the growing reliance on emerging technologies like artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT). These technologies are reshaping how maintenance teams manage assets and perform predictive maintenance. For instance, IoT sensors embedded in machinery can monitor factors like temperature, vibration, and humidity, sending real-time data to the CMMS. This allows for more accurate predictions of when equipment is likely to fail, enabling proactive maintenance before a breakdown occurs. However, integrating these technologies with existing CMMS platforms is not always straightforward. Many industrial facilities across the UK are still using legacy systems that are ill-equipped to handle real-time data streams or leverage advanced analytics. Consequently, facilities managers may struggle to optimise maintenance strategies, and the full potential of predictive maintenance may remain untapped. The challenge is not just about adopting new technologies but ensuring that the CMMS can integrate seamlessly with existing operational systems and processes. As more industries embrace these technologies, the pressure on CMMS providers to offer flexible, adaptable solutions will continue to grow. This need for integration is particularly pressing in sectors where real-time data is crucial for operational efficiency, such as in manufacturing, food production, and pharmaceuticals. The ability of a CMMS to incorporate data from multiple sources and translate that data into actionable insights will be key to improving decision-making and reducing downtime. Data management The integration of AI, ML, and IoT into CMMS platforms is not only about predictive maintenance but also about data management and analysis. As these technologies generate vast amounts of data, the ability to process, interpret, and act on this data is essential for effective facilities management. Business intelligence (BI) tools integrated with CMMS platforms can enable managers to make more informed decisions by providing advanced analytics and high-level dashboards that highlight key trends and performance indicators. For UK industrial facilities, one of the most pressing challenges in 2024 is effectively managing the growing volume of data. Facilities managers must ensure that their CMMS platforms are capable of handling this influx and that the data generated is actionable. Without the right tools and processes in place, the wealth of information provided by IoT sensors and other devices could quickly become overwhelming. As facilities strive to optimise their maintenance processes, data overload becomes a very real risk. Beyond simply managing data, facilities must also ensure that the information they collect is accurate, timely, and relevant. This requires a strategic approach to data governance and the development of systems that allow for easy interpretation. With a strong data management framework, CMMS systems can support predictive maintenance, asset lifecycle management, and cost forecasting—all of which contribute to more efficient and cost-effective operations. Addressing the skills gap In addition to technological challenges, UK industrial facilities are grappling with a significant skills gap within the maintenance sector. With an ageing workforce and a shortage of skilled technicians, particularly in areas involving advanced technologies like CMMS platforms, there is a growing need for training and recruitment. Many facilities managers are struggling to attract younger workers with the technical expertise required to operate sophisticated maintenance systems. This skills shortage is particularly pronounced in fields such as predictive maintenance, where staff must be able to interpret complex data and apply advanced analytics. The challenge is further compounded by the rapid pace of technological change, which requires facilities managers to continuously upskill their teams to stay ahead of the
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