What Happens After the Sale — with Peter O'Hara | The Adoption Gap, Part 4

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 the closing episode of our 4-part series, we sat down with Peter O'Hara, a Customer Success Manager for Senseye who's spent close to a decade helping manufacturers actually adopt and scale predictive maintenance. We cover: → Why asset selection makes or breaks the first 90 days after go-live → What separates a real internal champion from someone who just has the time → How to turn resistors into advocates, often by solving the problem they actually have→ The KPIs that drive renewal and expansion (hint: downtime avoided is only part of it)→ Why Senseye at scale is beautifulIf you've missed Parts 1–3 with Richard Jeffers, Nat Ford, and Pontus Noren, now's the time to binge the full series:Listen to episode one: AI Is Ready. Are We? - with Richard Jeffers here.Listen to episode two: Why Change Management Makes or Breaks PdM — with Nat Ford hereListen to episode three: What Industrial AI Projects Get Wrong About Adoption — with Pontus Noren | Adoption Gap Part 3 hereYou 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