Trend Detection Podcast

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 latest episode of the Trend Detection podcast, we're joined by Johnathan Bonner, Head of Solutions Engineering for Senseye, to explore why connectivity is often the most underestimated part of a predictive maintenance deployment.In this episode We discuss:Why industrial connectivity is rarely as simple as “plug and play”How different machines, systems and communication protocols create complexityWhy IT, OT and cybersecurity teams need to be involved from the outsetHow connectivity and integration can account for much of the implementation effortWhy trying to reduce upfront costs can ultimately delay time to valueHow mapping your infrastructure and data sources can support predictive maintenance and future digitalization projectsYou 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

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 live episode of Trend Detection, Belen Brunet from Coca-Cola Europacific Partners joins Mark Hindsbo, Head of Operations Software at Siemens, to explore how manufacturers can turn operational complexity into opportunity. They discuss connecting IT and OT, combining trusted industrial data with AI, and using Senseye Predictive Maintenance to improve asset utilization, support maintenance teams and scale smarter operations.In this episode you will learn:How to turn operational complexity into a competitive advantageWhy trusted industrial data is the foundation for effective AIHow digital twins can help manufacturers design and optimize entire factoriesHow Senseye helps teams fix the right equipment at the right timeWhat it takes to scale predictive maintenance from production to logisticsYou 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

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

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 third episode of our 4-part series, I sat down with Pontus Noren, founder of Ensemble AI, to unpack the patterns he's seen across industries —and why the same mistakes keep showing up in different factories.His perspective is especially valuable because it's from outside the Siemens world. The adoption gap isn't a PdM problem. It's an industrial AI problem.We cover: → The most common patterns behind failed industrial AI projects → Why "proof of concept" culture is one of the biggest blockers to scale → How misaligned KPIs create a gap between what AI delivers and what the business measures → What trust actually looks like in practice and how to build it incrementallyIf you missed Parts 1 and 2 you can listen below: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 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

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 second episode of our 4-part "The Adoption Gap" series, we sat down with Nat Ford from Siemens to unpack why change management isn't a workstream you bolt on at the end of a PdM project. It's the project itself.His take? If you need formal "change management" by the time you go live, something has already gone wrong.We cover: Why change management is often a sign the project wasn't designed properly in the first placeThe difference between managing change and designing change in from day oneHow the Hawthorne Effect applies to PdM adoption — and why paying attention to people matters more than any frameworkWhy predictive maintenance changes how people decide, not just what they doPrevious episodes in the seriesListen to episode one, AI Is Ready. Are We? - with Richard Jeffers here.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