Foodstuffs North Island Limited

Data has always been with us in retail. What’s changed is its gravity. No longer a passive by-product of transactions, data has become an enterprise asset. But owning data and using data effectively are two very different things. At Foodstuffs North Island, one of New Zealand’s largest FMCG retailers, we’ve spent the past 24 months shifting the centre of gravity, from scattered insights to orchestrated value. It hasn’t been easy. But it’s necessary.

And it starts with a blunt realisation: complexity is our enemy.

The Problem Isn’t Access, It’s Alignment

Too often, data sits in silos, optimised for the operational needs of yesterday, not the decision-making demands of today. Merchandising, supply chain, digital and property all capture data in slightly different ways, with different standards, definitions and expectations. That fragmentation might feel manageable day-today, but it’s fatal for scale.

The result? Reconciliation fatigue. Endless wrangling. Multiple versions of the truth. And ultimately, slower decision-making at a time when retailers must be faster and smarter than ever. This isn’t just annoying. It’s expensive.

The solution isn’t just technical, it’s architectural and cultural.

Take our ‘Single View of Shipment’ data product. It consolidates 13 disparate source systems into one canonical truth, enabling end-to-end visibility for our supply chain teams and reducing store delivery errors. It took considerable time of close collaboration with our Supply Chain SMEs to align business logic, resolve discrepancies and ensure we built something fit for purpose.

This wasn’t just a reporting fix, it reshaped team workflows, drove operational improvements, and proved that trusted data leads to better decisions.

AI That Earns Its Keep

Like everyone else, we’re exploring Generative AI. But we’re not chasing hype. We’re applying it where it makes business sense and where trust, transparency and governance can be built in from the start.

We’ve prototyped GenAI use cases in:

• Automated ‘analyst’ Q&A via natural language.

• Personalised product labelling for our wholesale business.

• Drafting supplier communications and onboarding content.

But here’s the catch: without trustworthy, well-curated enterprise data, GenAI won’t fly. It’s garbage in, garbage out, at machine scale.

That’s why our investment in cloud-native, governed and secure data infrastructure matters. It’s the runway for AI, not just the engine.

Chase Velocity, Not Maturity.

If you’re a data leader in retail, here’s a suggestion: stop obsessing over maturity frameworks. They’re useful, but they don’t tell you how fast you’re delivering value.

We hold ourselves to a simple rule: aim for visible value within 90 days, otherwise we don’t start. Whether that’s cost savings, time savings, safety improvements or strategic optionality, there must be a ‘so what.’

We’ve also learned that value is rarely created by data and analytics teams alone. We succeed when we embed ourselves in the value chain, executive reporting, store ops conversations or planning forums. It’s not about serving up reports. It’s about shaping strategy.

Making Data Work: Some Final Thoughts

1. Empower, don’t ‘own’ – Give teams governed self-service tools, not just dashboards.

2. Speak their language – Data folks need to learn to say ‘on-shelf availability’ and ‘promotion ROI’ more than ‘delta load latency’ or ‘data lineage’.

3. Design for portability – We intentionally designed our platform to be cloud-agnostic, not just for flexibility, but to keep partners honest and ensure long-term leverage.

4. Value isn’t always flashy – Some of our biggest wins came from fixing boring but broken processes. It’s not always AI that drives ROI.

Retail will always be about people, but the next decade belongs to the most intelligent retailers, those who know data isn’t the exhaust. It’s the engine.