Jean Marc Pestoni, Head of North America Business at Data Migration International (DMI): “When ERP works properly, leaders stop debating whose numbers are correct”

“Typically, I step in when things become complicated – mergers, divestments, SAP S/4HANA deadlines, audit exposure, or legacy systems that everyone depends on but nobody fully understands anymore,” said Jean Marc Pestoni, Head of North America Business at Data Migration International, when we asked about his experience with ERP systems.

“That’s the moment when ERP stops being a technology project and turns into a business risk conversation.”

If that resonates, then read on. Jean Marc has many years of experience in management, sales, and SAP project and program management. Including seven years with Accenture, followed by leadership roles across a range of consultancies. In short, he’s seen it all, having led major transformation projects within banking, insurance, manufacturing, and consumer goods and services.

The repeated mistake? Companies investing large amounts of money and time in ERP systems without tackling the tough questions first. Especially around legacy data. “That gap – between modern systems and unmanaged legacy information – is where ERP programs either quietly succeed or quietly struggle,” he said.

To avoid making this mistake yourself, read on – starting with Jean Marc’s view on the difference a properly implemented ERP system can make.

Can you tell us about your role and your experience with ERP systems?

Typically, I step in when things become complicated – mergers, divestments, SAP S/4HANA deadlines, audit exposure, or legacy systems that everyone depends on but nobody fully understands anymore. That’s the moment when ERP stops being a technology project and turns into a business risk conversation.

To me, ERP has never just been software. It’s where a company’s operational history lives. Every acquisition, every restructuring, every pricing model change leaves a trace in the data. Over time, that data becomes layered, duplicated, inconsistent – but still critical.

What I’ve seen repeatedly is this: companies invest heavily in new ERP systems while avoiding the harder question of what to do with the old data. That gap – between modern systems and unmanaged legacy information – is where ERP programs either quietly succeed or quietly struggle. And often, leadership doesn’t see it until late in the program.

In your view, what’s the biggest advantage a well-implemented ERP system can bring to an organisation?

A well-implemented ERP system doesn’t magically make a company faster. I think that expectation creates disappointment from the start.

What it actually does is create clarity.

When ERP works properly, leaders stop debating whose numbers are correct. Finance isn’t arguing with operations. Sales isn’t questioning supply chain. The conversation shifts from “which report is right?” to “what do we do next?”

That shift is bigger than people realize.

I’ve seen organisations unlock real value simply by cleaning up their core systems – removing duplicate master data, eliminating outdated records, simplifying structures that had grown messy over decades. Often, the efficiency they were looking for was already there. It was just buried.

ERP delivers its greatest impact when it becomes a stable foundation for decision-making. Not when it’s treated as a silver bullet, but when it quietly removes friction from the business.

How do ERP systems help businesses become more agile and data-driven?

To be honest, ERP systems by themselves don’t automatically make a business more agile. In fact, if they’re overloaded with legacy complexity, they can slow things down.

Agility comes from discipline – especially around data.

When companies keep the ERP core clean and separate historical data intelligently, the system becomes easier to adapt. It becomes scalable. It becomes manageable. That’s when agility becomes realistic.

A modern ERP environment should allow organisations to introduce analytics, automation, or AI-driven use cases without destabilizing the operational core. But that only works if the data foundation is structured and governed properly.

I’ve seen environments where innovation feels heavy and risky. And I’ve seen environments where new capabilities can be added almost naturally. The difference is usually not the software. It’s how clean the core is.

True agility isn’t about adding more features. It’s about removing unnecessary weight.

What are the most common reasons ERP implementations fail or fall short?

ERP implementations rarely fail because the software is wrong. Modern ERP platforms are capable.

They fall short because of how data is handled.

Most projects start with process design workshops and structured timelines. They end with stress around data. Data is often treated as a technical migration task, when in reality it’s a business risk issue.

Companies consistently underestimate how much legacy data they have – and how little of it they actually use day to day. The safe assumption becomes: “Let’s move everything.” But moving everything rarely solves anything.

There’s also fear involved. Fear of deleting data. Fear of audits. Fear of losing access to something “just in case.” That fear drives conservative decisions.

And conservative decisions usually mean excessive scope.

The result? Higher costs. Slower systems. More complexity than before. Essentially, the old problems get transferred into the new environment.

What lessons have you learned from challenging ERP rollouts?

The biggest lesson is simple: reduce scope early.

ERP projects expand very quickly if you let them. Every department has valid requests. Every stakeholder has concerns. And before long, the transformation becomes overloaded.

The most successful rollouts I’ve seen focus only on what is operationally essential. They build a clean core first. They resist the temptation to fix everything on day one.

Another lesson is governance. You cannot listen to every voice equally during an ERP program. If leadership doesn’t prioritize clearly, scope explodes.

I’ve learned that saying “not now” is often more important than saying “yes.”

If you build a stable, clean foundation, you can evolve continuously afterward. But if you overload day one, you spend years managing complexity.

How do you balance the complexity of ERP systems with the need for usability?

ERP systems are complex because businesses are complex. That part won’t change.

But the real value isn’t the ERP system itself. It’s the people who use it.

The mistake I see is designing everything around technical possibilities instead of operational realities. Domain experts – the people in finance, supply chain, manufacturing – know exactly what they need to operate successfully. When you listen to them carefully, usability improves naturally.

Another major factor is keeping the ERP core lean. When historical data is separated and unnecessary customization is avoided, the system feels lighter. Complexity becomes manageable instead of overwhelming.

Usability doesn’t come from simplifying the business artificially. It comes from removing unnecessary friction.

When migrating, do organisations tend to under-estimate the challenge of data migration?

Almost always. Especially teams that haven’t gone through a large transformation before.

There’s a common belief that the right tools will solve the migration challenge. But tools don’t decide what data still matters. They don’t understand compliance exposure, business relevance, or operational necessity. They simply move what they’re told to move.

The real challenge isn’t data size. It’s complexity. Over time, companies accumulate multiple systems, inconsistent rules, overlapping master data, and evolving regulatory requirements. That’s where the real risk hides – in the interdependencies.

So how do you mitigate that risk?

First, you start asking better questions early. Instead of asking, “How do we move everything safely?” the better question is, “Why are we moving this at all?” That shift in mindset changes the entire program.

Second, you involve business stakeholders early in defining what data is operationally required versus what is historically important but does not need to sit inside the new ERP core. Separation of live and historical data is often the turning point in reducing scope and complexity.

Third, you treat data migration as a strategic decision-making exercise – not a technical task at the end of the project plan.

When organisations take that approach, projects become simpler. Risk decreases. The ERP core stays cleaner. And the migration becomes a strategic reset rather than a replication exercise.

What role do you see AI and machine learning playing in ERP in the near future?

AI will absolutely shape ERP environments. But not in the way many expect.

AI won’t fix problems caused by poor data quality. In fact, it exposes them faster. If the data foundation is inconsistent or poorly governed, AI amplifies the noise.

That said, historical data is incredibly valuable for AI-driven analytics. Long-term patterns matter. Predictive modeling depends on structured historical context.

But that data has to be managed properly and separated intelligently from live systems.

Interestingly, AI is forcing companies to confront legacy data discipline. Organisations that ignored historical complexity for years are now realizing that AI requires structure.

In that sense, AI isn’t replacing governance. It’s enforcing it.

If you could give one piece of advice to a CIO about to embark on an ERP project, what would it be?

Decide early what data you are not going to move.

Most ERP programs focus entirely on what needs to be migrated. Very few ask what should be left behind. That distinction changes everything.

Historical data should be managed strategically, not dragged into a new system by default.

And don’t let fear of audits drive technical decisions. Compliance is critical, but there are structured ways to retain access without overloading the ERP core.

ERP projects don’t usually fail because of technology. They fail because uncomfortable decisions are postponed.

The earlier those decisions are made, the smoother the transformation becomes.

If there was one single pitfall you would warn people of, what would it be?

The biggest pitfall is postponing the data conversation.

I’ve seen teams spend months debating architecture, integrations, and timelines – assuming the data will sort itself out later.

It never does.

By the time data becomes central, deadlines are tight and decisions are driven by fear instead of logic. That’s when companies default to moving far too much historical data into the new system, just to be safe.

The result is predictable: higher costs, slower performance, and unnecessary complexity.

ERP projects don’t fail because the software is wrong. They fail because leadership avoids making early, clear decisions about what data actually matters.

Clarity at the beginning prevents replication of the past.

That’s when organisations default to moving far too much historical data into the new ERP system, just to be safe. The outcome is predictable: higher infrastructure costs, slower performance, increased complexity, and reduced flexibility. In essence, they carry yesterday’s problems into tomorrow’s platform.

ERP projects do not fail because the software is wrong. They fail because leadership avoids making early, disciplined decisions about what data truly matters – and what doesn’t.

Clarity about data relevance at the beginning of a project is what separates transformation from replication.

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