Uploaded March 2026 | Updated September 2026, 2 weeks ago
Most transformation programmes do not fail because of the technology.
They fail because the business is judging risk, cost, change, and timing on a completely different scorecard.
My guest here is Don Mahoney, Global Head of Products and Innovation at SNP Group, with nearly 15 years at SAP before joining SNP and a front-row seat to how some of the world’s largest enterprises handle transformation, trade-offs, and operational change. What makes his perspective useful is that he is not looking at this as abstract strategy theatre. He has seen where programmes stall, where data becomes a blocker, and where resilience gets talked about more than it gets built.
That matters now because senior supply chain, procurement, operations, and risk leaders are under pressure from every direction at once: cost volatility, fragmented data, AI hype, regulatory pressure, and the very real problem of trying to modernise without breaking the business in the process. Don makes the point that transformation is no longer a one-off event. It is becoming an ongoing capability, and that changes how leaders need to think about data, systems, timing, and organisational readiness.
What shifted my thinking most was how clearly Don framed the hidden failure mode. In one project, the customer was evaluating the path forward across five dimensions: strategy, cost, risk, organisational change, and technology, while the implementation side was focused on technology alone. That is a brutal but useful reminder that projects can look fine in the tech lane and still be heading for a wall.
I also liked his line about moving from a transaction machine to a decision machine. That gets to the heart of why better data matters. If your information is scattered across silos, takes a week to reconcile, and still leaves gaps filled by guesswork, you do not have agility. You have delay dressed up as process. And in an AI context, the stakes get even sharper: do you really want to train models on the way you worked 30 years ago? Probably not.
This is for supply chain, procurement, operations, transformation, and risk leaders trying to modernise without dragging legacy confusion into the next system.
If you’re dealing with this on the ground, I’d like to hear how you’re handling it.
🔗 Podcast: resilientsupplychainpodcast.com
🔔 Follow the channel and subscribe for more conversations on supply chain resilience, operational risk, sustainability, and decision-making
💡 Chapters / Timestamps
00:00 – Why transformation fails outside the technology lane
00:00:20 – Don Mahoney’s view from SAP and SNP
00:02:30 – Why transformation is now continuous, not episodic
00:03:40 – Why AI should not learn from 30-year-old processes
00:05:00 – The trap between brownfield ROI and Greenfield risk
00:09:06 – How to modernise without creating operational chaos
00:11:41 – Why data hygiene becomes a resilience issue
00:12:38 – The five-dimension decision model most teams miss
00:14:15 – Why poor change capacity gets expensive fast
00:16:24 – From transaction machine to decision machine
00:18:40 – Why AI raises the value of unstructured data
00:22:28 – Why siloed data kills agility under pressure
Most transformation programmes do not fail because of the technology.
They fail because the business is judging risk, cost, change, and timing on a completely different scorecard.
My guest here is Don Mahoney, Global Head of Products and Innovation at SNP Group, with nearly 15 years at SAP before joining SNP and a front-row seat to how some of the world’s largest enterprises handle transformation, trade-offs, and operational change. What makes his perspective useful is that he is not looking at this as abstract strategy theatre. He has seen where programmes stall, where data becomes a blocker, and where resilience gets talked about more than it gets built.
That matters now because senior supply chain, procurement, operations, and risk leaders are under pressure from every direction at once: cost volatility, fragmented data, AI hype, regulatory pressure, and the very real problem of trying to modernise without breaking the business in the process. Don makes the point that transformation is no longer a one-off event. It is becoming an ongoing capability, and that changes how leaders need to think about data, systems, timing, and organisational readiness.
What shifted my thinking most was how clearly Don framed the hidden failure mode. In one project, the customer was evaluating the path forward across five dimensions: strategy, cost, risk, organisational change, and technology, while the implementation side was focused on technology alone. That is a brutal but useful reminder that projects can look fine in the tech lane and still be heading for a wall.
I also liked his line about moving from a transaction machine to a decision machine. That gets to the heart of why better data matters. If your information is scattered across silos, takes a week to reconcile, and still leaves gaps filled by guesswork, you do not have agility. You have delay dressed up as process. And in an AI context, the stakes get even sharper: do you really want to train models on the way you worked 30 years ago? Probably not.
This is for supply chain, procurement, operations, transformation, and risk leaders trying to modernise without dragging legacy confusion into the next system.
If you’re dealing with this on the ground, I’d like to hear how you’re handling it.
🔗 Podcast: resilientsupplychainpodcast.com
🔔 Follow the channel and subscribe for more conversations on supply chain resilience, operational risk, sustainability, and decision-making
💡 Chapters / Timestamps
00:00 – Why transformation fails outside the technology lane
00:00:20 – Don Mahoney’s view from SAP and SNP
00:02:30 – Why transformation is now continuous, not episodic
00:03:40 – Why AI should not learn from 30-year-old processes
00:05:00 – The trap between brownfield ROI and Greenfield risk
00:09:06 – How to modernise without creating operational chaos
00:11:41 – Why data hygiene becomes a resilience issue
00:12:38 – The five-dimension decision model most teams miss
00:14:15 – Why poor change capacity gets expensive fast
00:16:24 – From transaction machine to decision machine
00:18:40 – Why AI raises the value of unstructured data
00:22:28 – Why siloed data kills agility under pressure
