Any reference to projectlabs.co or the pmoshow has now been superseded by projectchatterpodcast.com. For more information, blogs, and contact details please visit www.projectchatterpodcast.com. Enjoy the pod… Dale spends some time reflecting on what...
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In this episode Val Matthews had the pleasure of presenting his views on disruptions to PMO and technology advances to the members of AIPM. (Technology), what could it mean to PMO's? A new role for PMO in projects? The Australian Institute of Project...
Most data scientists have never touched a project. Yash Desai looked at the project controls world through the data first, and what he found says a lot about why this industry lags behind others on AI. In Episode 220, Dale is joined by returning co-host Martin and first-time guest Yash Desai, Head of Data and AI at Movar Reply, for a practical conversation on where data, AI and robotics actually fit in project delivery. We cover why project controls sits behind other industries, what an orchestration layer really is, how to future-proof your role, the data scientist vs project controller debate, hiring for drive over a skills list, robotics on site today vs the hype, and the Fable situation. No buzzwords, just useful insight. Chapters:00:00 Welcome back01:38 Who is Yash Desai?04:09 Why project controls lags on AI09:44 What is an orchestration layer?14:23 Future-proofing your role22:48 Data scientist vs project controller33:26 Grads and the assurance layer36:17 Why robotics is getting interesting46:21 Robotics in one to two years52:10 Should governments regulate robotics?57:23 The Fable situation and 'Pragmatic'01:01:01 Final thoughts Connect with Yash: https://www.linkedin.com/in/yash-desai-00847216b/Subscribe to Pragmatic: https://www.linkedin.com/newsletters/pragmaitic-7347631768201535488/ A free-access podcast. Pay it forward and share it on. www.projectchatter.com
88% of project schedules don't follow best practice. So why are we so keen to feed that data into AI and trust the output? In this episode, Dale and Val are joined by Michael Pink, Founder of SmartPM, for a sharp conversation on the forensic side of delay and the state of AI in project controls. Mike has analysed hundreds of thousands of schedules and built a career on working out who delayed what, and why nobody could ever agree. His core message: clean data is not the same as honest data. A technically tidy schedule can tell you a story that never happened, and if you point AI at it, you don't get insight, you get a confident wrong answer at scale. What we cover: Mike's route into construction, from a study-abroad debt to KPMG's construction consulting group 25 years of change in the people and process side of scheduling The shift from reactive forensic work to proactive project controls Data honesty vs data quality, and why integrity is the combination of both (framing credited to Isaac Dyer and Carlos Sanchez) The 88% problem: missing logic, inflated float and moving dates The compression factor, and the exact point a schedule becomes infeasible Why a weekly update beats a monthly one, for almost no extra time P6 vs Microsoft Project, and grading schedule quality across 35 metrics Where LLMs genuinely help, and why quantitative AI is still the long game The future of the scheduler: less building and cleaning, more strategy A genuinely optimistic look at where the profession is heading, and why this might be the best time yet to be in project controls. This episode is proudly sponsored by nPlan.nPlan Summer AI Day 2026: Construction Superintelligence takes place in London on Thursday 25 June 2026, with a fireside featuring Peter Hancock, Project Director at National Grid, and Dima Pogorelsky, MD and Partner at BCG. February's event sold out with standing room only. Register here:https://www.nplan.io/events/nplan-summer-ai-day-2026-construction-superintelligence Connect with Michael Pink at https://www.smartpm.com or on LinkedIn. If you enjoyed this episode, help us pay it forward and share it. Stay safe, be disruptive, and have fun doing it.
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