For years, data has been hailed as the new oil. A powerful resource waiting to be refined. Yet for many consumer goods brands, that resource is piling up in silos, overwhelming teams, and failing to deliver the commercial impact promised by years of digital transformation rhetoric.

At a recent roundtable hosted by Grocery Gazette in partnership with analytics automation platform Advise, senior category leaders from across the CPG landscape gathered to address a hard truth. The problem is no longer access to data, it’s knowing what to do with it.

In a conversation that spanned AI trust, generational change, cultural bottlenecks and execution fatigue, one message was clear: insight alone isn’t enough. If CPGs want to thrive in the next era of decision-making, they need to rethink their relationship with data, and fast.

The paralysis of abundance

The modern CPG business has never had more visibility. From real-time market data and retailer feeds to internal performance metrics, the volume of information at hand is staggering. Yet, as one executive put it, “There’s a huge gap between access and use.”

Sales, marketing, and category teams may technically be drawing from the same data well, but how many are really drinking from it? Too often, data isn’t seen as a shared business asset. It’s siloed, scrutinised and crucially, underutilised.

One category leader captured the core issue: “I want my team to be solving new problems. Not spending time confirming what we already know.” That sentiment echoed across the room. Data is supposed to be the unlock for innovation but right now, it’s often just a mirror.

Trust, automation, and the fear of the ‘black box’

As generative AI tools enter the conversation, many hoped this might be the turning point. The moment analytics finally shifted from retrospective reporting to proactive decision-making. But the trust gap remains a major hurdle.

“Everyone wants automation,” one attendee said. “But the moment something is automated, there’s a compulsion to mark its homework.” In other words, leaders don’t trust what they can’t see, and if outputs still need to be sense-checked by humans, the time savings are wiped out.

There was deep concern about the risks of skipping steps. “If we remove the manual process, do we lose the understanding? Do we lose the trust?” asked one category manager. The consensus? Automation is only as valuable as the confidence leaders have in its outcomes and right now, that confidence is fragile.

Best practice doesn’t yet exist

Part of the problem is that even within the same business, different functions define and measure success differently. What’s ‘good’ analysis in a category team might not be trusted in commercial. In the absence of agreed standards, teams revert to their own methods, often reverting back to Excel and legacy systems that are comfortable, if inefficient.

One participant pointed out that even Gen Z hires – digital natives by default – lack the training to know what to question versus what to trust. As another leader put it, “How do we educate new grads to interrogate AI-driven insights, if we haven’t agreed on what best practice looks like ourselves?”

This points to a broader, more existential issue: the lack of an agreed operating model for AI and data in the CPG space. Most are still in the ‘pilot and patch’ phase. Testing, fiddling, hoping something sticks.

Cultural reform, not just technological reform

The leaders at the table didn’t hold back on where they believe transformation needs to happen. At the top.

“Digital transformation is a cultural shift,” said one exec. “It’s not about the tools. It’s about how we behave.” That includes moving away from asking the data team for ad hoc reports, embedding insights into every layer of the business, and having leadership that actually uses the data tools they endorse.

If the CEO still relies on emailed PowerPoints rather than interacting with live dashboards or AI platforms, the rest of the organisation won’t change either. In short, AI won’t solve your decision-making problems if your culture resists change.

Fail fast… or don’t?

Interestingly, the group was split on the once-sacred mantra of innovation – ‘fail fast’. One executive insisted that this approach still holds water, especially for AI applications. “Start small, build use cases, let success create the momentum for larger investment.”

But others were blunt. “Fail fast is dead.” Budget holders, they argued, are no longer interested in experiments. They want ROI now. That demand for certainty is clashing with the still-developing nature of AI. As one attendee noted, “Everyone knows they need to be in the space but no one wants to fund the journey to figure it out.”

Without budget for experimentation, however, capability remains stunted. Confidence never builds. And AI tools, no matter how advanced, remain underused. It was mentioned by a number of participants that the most efficient way to get organisational buy-in is to set-up a pilot. One that is big enough to show scale, impact, usage and ultimately ROI, before rolling out company wide.

From data concierge to strategic powerhouse

The most energising discussions centred on what could be unlocked if businesses restructured their data approach. As Advise’s Dr Kevin McCarthy explained in the pre-session interview, “Category teams shouldn’t be data concierges. Their time is better spent thinking, planning, leading.”

And that’s the pivot everyone in the room seemed to want. “More thinking, less digging.”

With clean, harmonised data and intelligent automation, brands could shift from reactive reporting to proactive planning. From compiling decks to building strategy. From asking “what happened?” to “what’s next?”

Or, as one attendee brilliantly put it: “I want AI to tell me what the next pistachio is.” (A nod to the Dubai chocolate and pistachio craze, and a perfect metaphor for using data to spot, not just track, emerging consumer goldmines.

The final word: From insight to impact

This roundtable made one thing clear. CPGs don’t need more data. They need more clarity, confidence and action.

Until leaders trust the tools, define best practice, and invest in the skills and structures to support real-time, AI-enabled decision-making, the promise of transformation will stay unfulfilled. But for those bold enough to act – and not just analyse – the rewards are significant. Faster decisions, more proactive thinking, and a serious commercial edge.

Advise’s proposition is simple but powerful. Stop stockpiling analytics and start scaling intelligence.

To learn more about how they’re helping CPGs close the gap between insight and action, email sam@advisecpg.com.

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