Data-driven, automated asset management processes are now in full flight across businesses. The challenge that it has created is turning the huge amounts of information into actionable metrics that drive organisational change and create more mature asset management conversations and decision making.

Spending time thinking about how customers and other business stakeholders perceive and look at assets, what the asset’s function is from someone else’s perspective and linking asset management back to tangible real-world examples allows powerful, informed decisions to be made.

Improved communication is the key to obtaining stakeholder buy in and seeing asset management as an opportunity.

• Communication and listening to others is the key to success.
• Data quality isn’t a problem, finding ways to clearly communicate the data is the real challenge.
• Breaking up the problems and solving them is key to making organisational change.

Maintenance and reliability professionals are increasingly turning to data-driven approaches to enhance operational efficiency and asset longevity. This panel discussion delves into the two paramount challenges we're facing as we navigate the complexities of data utilization: data quality and integration, and the skill gap in data analytics.

Ensuring data quality and seamless integration still poses a significant hurdle. Maintenance and reliability operations generate vast amounts of data from diverse sources, including sensors, equipment logs, and maintenance records. However, inconsistencies, inaccuracies, and fragmentation in data can undermine decision-making processes. The panel will explore strategies for improving data quality, standardizing data formats, and integrating disparate data sources to create a cohesive and reliable data ecosystem.

The skills gap in data analytics also remains a critical issue. While advanced data analytics tools and techniques offer tremendous potential, the lack of personnel with the requisite expertise to leverage these tools effectively hinders progress. This discussion will address the need for upskilling existing staff, attracting new talent with data science proficiency, and fostering a culture of continuous learning within maintenance and reliability teams.

Join us as industry leaders share insights, experiences, and practical solutions to these pressing challenges, paving the way for a more data-savvy and resilient future in maintenance and reliability.