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One of the key components in asset health and risk modeling is relating the theoretical health scores and risk values into something tangible, such as failure rates and the monetary cost of the failures that are being experienced on the network. To minimize disruptive failures of your assets, you need to understand this relationship and to be able to use the information collected when failures do occur to refine your asset models. In time, you will become more confident in using the asset models and in ensuring that they best reflect the condition of your assets, knowing what data needs to be refined and how and when to collect it. In this recorded webinar, we take an analytical look at the failure mechanisms within the asset health and risk models. We examine some typical outputs for the capture of failure information, show how it can be analyzed and how to use it in the model. We also consider what happens where there is no failure data available and point you to other sources of information that can be useful when setting model parameters. Key takeaways Understand the data points for asset modeling. Know what you can do with the data that you've got and how it fits into the models. How to create a plan to backfill asset data in an economical and methodical way. To learn more about invest visit: https://invest.eatechnology.com/ For other EA products & Services visit: https://eatechnology.com/americas/