Finding the Right Predictive Maintenance Partner - with Kelli Case

Welcome to the Trend Detection podcast, brought to you by Senseye Predictive Maintenance – which gives you visibility and insights into all your assets, from single machines to full plants to help you reduce downtime, increase knowledge sharing and accelerate digital transformation across your organization. In this episode, Liz McGinn is joined by Kelli Case, a Business Development Director for Senseye at Siemens, who shares practical guidance drawn from her experience working with organizations adopting predictive maintenance. • Why choosing a predictive maintenance partner is a strategic, long‑term decision, not just a software purchase—covering culture change, transformation, and sustained value. • How to assess your organization’s readiness for predictive maintenance, including maintenance maturity, data access, internal capabilities, and willingness to change. • What separates a strong PDM partner from a weak one, such as listening skills, adaptability, domain experience, global support, and the ability to scale with your business. • Key technology and architecture considerations to look for, including openness and vendor agnosticism, data ownership, security, configurability vs. customization, and integration across systems. • How to avoid common pitfalls and measure success, from unrealistic promises and long time‑to‑value to proving ROI quickly, enabling user adoption, and planning for future evolution toward prescriptive maintenance. You can find out more about how Senseye Predictive Maintenance can reduce unplanned downtime and contribute towards improved sustainability within your manufacturing plants, by visiting: www.siemens.com/senseye-predictive-maintenance (http://www.siemens.com/senseye-predictive-maintenance)