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