Are your data models enabling operational and planning decisions like you thought they would? If decision-making tools built on data-driven risk models are a valid means of improving asset management programs, why do so many products fall short? In this presentation, see how a live solution already deployed for one major utility is enabling real-time risk analysis, traceability, automated reporting, data-quality verification, and more. By understanding the factors that make your organization unique, including data collection, storage, and availability, we’ll explore how an engineering-based approach to risk modeling, informed by a broad scope of diverse data, can help your organization build tools to understand its assets and unlock decisions at a scale unparalleled by off-the-shelf solutions alone. We’ll also cover technical pitfalls and lessons learned from the field, including how our solution went from proof-of-concept to production in a matter of months with the support of a multidisciplinary team.

Key Takeaways:

• Understand how your organization can design, launch, and scale software products that enable real-time asset risk management and work in concert with your existing software products and platforms. 
• Learn how to transition rapidly from proof-of-concept to production-ready solution while accounting for daily data refreshes.
• Identify the datasets that are relevant to your organization and how to collect, organize, and analyze them to unlock action with speed.
• Gain insight and lessons learned from real-world use cases now deployed and in use for a major utility.