Inside MRO – Blog Series Part 4

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In the third post of our blog series Inside MRO: Lessons from the Frontlines of Spare Parts Strategy, we explored what MRO excellence looks like in practice, highlighting how strong governance, leadership commitment, and data discipline can drive real transformation. But even the most capable organizations can’t succeed on structure alone—they also need the right tools.

In this fourth installment, Andrew Jordan unpacks one of the most common misconceptions in spare parts management: that ERP systems are the problem. In reality, ERP systems are often underused or misused—while the real challenge lies in how they’re implemented, maintained, and extended.

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The Tools for Efficient Spare Parts Management Are Already There—You’re Just Not Using Them

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One of Jordan’s core observations is that most organizations already have the foundational tools they need for MRO excellence—but fail to leverage them properly. Whether it’s descriptive item data, stocking policies, or lot size modifiers, much of the critical spare parts infrastructure is built into the ERP systems. It just isn’t being used consistently or thoughtfully for proper spare parts management.

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“The first thing I’d say is, use what you’ve got to the max.
ERP systems are really good at doing things consistently, but that doesn’t mean you’re doing things consistently.”

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In other words, ERP systems will faithfully execute any process you define—but if that process is flawed, the system will scale your inefficiencies instead of leading to MRO excellence.

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The Pitfall of “Set and Forget”

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A key issue Jordan sees time and again is the static nature of MRO configuration. Organizations input values when they first implement their ERP systems, then leave them untouched for years—despite major changes in demand, supply, and operations in their spare parts management.

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“The prevailing model is ‘set them and forget them.’
People will put these values in when they’re setting up their ERP system, then ten, fifteen years will pass and nobody’s looked at it.”

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This creates a disconnect between reality and system logic. Worse, because these values were often entered by different individuals over time—using inconsistent logic—planners end up with unreliable outputs and patchwork decisions.

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Where ERP systems End and Optimization Begins

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While ERP systems are great at executing rules, they aren’t built to optimise them and lead to MRO excellence. That’s where external tools for spare parts management come in—particularly for areas like:

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• Ordering parameter optimization
• Lifecycle management of spare parts
• Catalog governance
• Cross-site inventory pooling
• Intelligent item introductions and decommissioning
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“I haven’t seen any ERP system yet that can do the optimization side of things...
You will perpetuate a bad thing for years and years and years.”

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Tools that can sit alongside the ERP system—feeding it with optimised data—are often far more effective than trying to replace or overhaul core systems. That’s exactly what Sparrow.CLEAN is designed to do—ensuring your ERP runs on clean, standardised, and reliable part data from the start.

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AI and Analytics: Promise and Pitfalls

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Jordan also weighed in on the rising excitement around AI and machine learning in MRO. While he sees enormous potential, he’s cautious about how it’s applied.

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“If you can’t tell me why, well, I’m not interested.
I think AI should drive the insight, so that the person can evaluate the outcome.”

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For him, the key value of AI is in insight generation, not decision-making. Machine learning in MRO can only work if planners get visibility into the drivers behind AI recommendations—especially when those recommendations impact risk, uptime, or spend.

That said, he sees huge promise in using AI and Machine Learning in MRO for:
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• Forecasting consumables (which are often ignored or managed in spreadsheets)
• Analyzing machine operating data to detect failure patterns
• Highlighting spare parts with high preservation risk or declining reliability
• Identifying redundant or non-critical inventory
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These use cases move beyond automation into the realm of augmented decision-making—where human expertise and machine intelligence work together. Only then will Machine Learning in MRO be successful. That’s the vision behind Sparrow.PLAN — helping organizations connect asset planning and part availability to make smarter, better-timed maintenance decisions.

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Spare Parts Management: Thinking in Lifecycles, Not Lists

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Jordan encourages organizations to move away from a “spare parts catalog” mindset and toward a lifecycle perspective of spare parts management—understanding that spare parts evolve from introduction to active use to end-of-life. Most tools today are focused on the middle of that journey (catalog and inventory optimization), leaving blind spots at the beginning and end.

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“A lot of the effort that’s taken place is really around that active part...
There’s a bit of an outage there and an opportunity at end of life.”

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Without tools to manage item decommissioning or catalog clean-up, many companies end up with inventory that hasn’t moved in five years—which hurts both operations and finance. There again, Machine learning for MRO can be a big help. That’s exactly where Sparrow.STOCK comes in— offering a simple-to-use spare parts inventory manager to easily locate and manage items across storerooms.

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MRO Excellence: Don’t Automate the Mess

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Ultimately, Jordan’s message is clear: technology can amplify your capabilities, but only if the fundamentals are in place. Blindly trusting tools—or worse, using AI and Machine Learning in MRO to automate flawed processes from your ERP systems—will only make things worse.

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“Just because you have something in your catalog doesn’t mean you need to have it in inventory.”

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Tech can’t replace the hard work of building structure, logic, and governance into your spare parts strategy. But if you’ve done that work, it can supercharge your results and lead you to MRO excellence.

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Coming Up Next: MRO Meets Machine Learning

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In the final post of the Inside MRO series, we’ll look ahead to the future. Andrew Jordan will share how AI, analytics, and a new generation of data tools could fundamentally reshape how organizations manage spare parts—from forecasting to failure prediction to smarter decision-making across the asset lifecycle.

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Stay tuned for:
“How AI for Inventory Management Can Help You Make Better Spare Parts Decisions—But Not Make Them for You”

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Have you found this blog post insightful? Don't miss the previous installments:

Part 1: What I Missed About Spare Parts and MRO — Until Everything Pointed Back to Them

Part 2: Why Parts Inventory Management Doesn’t Get the Love—And Why That’s Hurting Your Business

Part 3: The Gold Standard in MRO Optimisation: What Top Performers Do Differently

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