This session will focus on the critical aspect of asset management in the maintenance domain—specifically, how to make informed decisions about when to replace or maintain equipment. By integrating advanced analytics and financial insights, organizations can enhance the efficiency and cost-effectiveness of their maintenance strategies. In this session, you will learn how to:

• Use analytics to predict asset lifecycles and optimize maintenance schedules to reduce downtime.
• Evaluate the total cost of ownership to make data-driven decisions on whether to replace or maintain equipment.
• Implement tools and best practices to maximize asset value and performance over time.
• Align asset management strategies with broader organizational goals for greater efficiency and long-term success.

• How might predictive analytics be refined to improve asset lifecycle modeling, and which advanced methods are most effective for forecasting maintenance needs?
• In evaluating total cost of ownership, how can indirect costs such as downtime and productivity losses be better integrated into financial models?
• What best practices exist for integrating real-time IoT data, maintenance logs, and financial metrics into a unified asset management approach?
• How can sustainability and regulatory compliance be incorporated into asset lifecycle evaluations, and what role do financial models play in this?
• What limitations exist with data-driven maintenance models, and how might a balance with human expertise be ensured in critical decision-making?

In the Harvesting Session the World Café moderators will summarize the results of their discussions and present key findings.