Your Product Operating Model Has a Blind Spot

There’s been a noticeable shift in how product organizations talk about themselves over the past few years. “Product Operating Model” has become the language of choice. It shows up in transformation decks, org design discussions, and leadership offsites. It sounds substantial. Systemic. Thoughtful.

In many cases, it is.

A Product Operating Model is meant to answer a hard, necessary question: how do we actually build products here? Not in theory, not in a framework diagram—but in practice. Who decides what matters. How priorities get set. What inputs carry weight. How ideas move from early signal to committed roadmap.

That’s the promise.

Where things tend to break down is more specific.

Most Product Operating Models get the structure right. They define cross-functional teams, establish rituals, introduce planning cycles, and often adopt Agile delivery practices. On paper, the system looks coherent.

Then the real work begins.

A roadmap decision gets made. It’s backed by data, supported by stakeholders, and framed as aligned. A few weeks later, it starts to wobble. A new data point surfaces. A stakeholder raises a reasonable concern. Customer feedback gets reinterpreted. The team reopens the discussion—not because anyone failed, but because the original decision didn’t fully hold.

This is where the operating model gets tested. And this is where many of them show strain.

Because underneath the structure, there’s a bigger issue: the model hasn’t resolved how to weight input.

Most teams are not short on customer perspective. They have interviews, surveys, usage data, sales feedback, support tickets. The problem is not access. It’s discrimination.

Which of these inputs should actually shape the decision?

Which perspectives are describing the current product—and which are pointing to where the category is going?

Which voices should carry more weight when the stakes are high?

Without a clear answer to those questions, the operating model defaults to something that feels responsible: include more input, gather more perspective, synthesize more broadly. It creates the appearance of rigor. It also dilutes direction.

This is the gap where Catalytic Customers become useful.

A Catalytic Customer is not a heavy user or an extreme expert. They are an experienced participant in the category who is highly engaged, able to articulate what matters, and constructively critical in how they evaluate products. They tend to notice where things fall short before those issues become widespread. They focus on utility—what actually makes something better to use—rather than novelty for its own sake.

They don’t represent the average user today. They tend to reflect where the category is heading.

That distinction matters inside a Product Operating Model.

Because one of the model’s core jobs is to help teams make decisions that hold under pressure. Not just decisions that can be justified in a meeting, but decisions that remain intact when challenged later—by new data, by stakeholders, by the market itself.

Catalytic Customers improve the odds of that happening by sharpening how input is weighted.

Instead of treating all customer feedback as equally informative, they introduce a form of prioritization. Not by volume or frequency, but by relevance to the decision at hand. When a team is making a bet—on a feature, a workflow, a positioning—these are the customers most likely to expose whether that bet will stand up once it’s in the market.

Used well, they change a few things inside the operating model.

They tighten the connection between discovery and decision-making. Discovery stops being a broad collection exercise and becomes more focused on specific, decision-relevant perspectives.

They improve the quality of tradeoff conversations. Instead of reconciling competing feedback at a high level, teams can anchor discussions in the perspectives most likely to anticipate downstream consequences.

They strengthen decision integrity. When a decision is challenged later, there is a clearer rationale behind why certain inputs were weighted more heavily. That rationale is easier to defend, and more importantly, more likely to prove right.

None of this replaces Agile, or design thinking, or any of the other components that typically sit inside a Product Operating Model. It works alongside them. It sharpens a part of the system that is often left implicit.

How do we decide what to trust?

That question sits at the center of every product organization, whether it’s acknowledged or not. Most operating models gesture toward it without fully resolving it.

Catalytic Customers offer a way to answer it more precisely.

Not by adding more input.

By making better use of the input you already have—and knowing whose perspective should shape the decision when it matters most.