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