When enterprise operating models change in consumer-facing organizations—shifting from local to global structures, or vice versa—innovation execution often slows. This happens even when the strategy and structure appear sound.
The reason is rarely poor process or weak leadership. It’s that innovation operating models aren’t disciplined enough to support enterprise trade-offs; impacting how innovation decisions, governance, and resource allocation happen in the real world.
Without explicit and disciplined mechanisms to translate enterprise strategy into execution-level choices, organizations default to escalation, ambiguity, and inconsistency—the very outcomes operating model change is meant to fix.
This is the translation gap. And for innovation leaders, it’s where responsibility and reality collide.
Across consumer health and the broader CPG sector, enterprise operating models are under renewed scrutiny. Margin pressure, portfolio complexity, and the need to move faster with fewer resources are driving structural shifts: consolidating P&Ls, centralizing functions, and redefining accountability from geography to category or platform (and, in some cases, back again).
When enterprise operating models are renewed, innovation operating models typically need to follow. Innovation is not a downstream process or a supporting function; it is one of the primary mechanisms through which enterprise strategy is translated into real investment choices, portfolio trade-offs, and long-term bets. If the enterprise logic changes but the innovation reality does not, misalignment is inevitable.
In practice, most organizations solve this challenge on paper. Priority statements are clarified. Governance structures are updated. Decision rights are documented. From an enterprise perspective, the logic appears to hold.
What is often underestimated is how quickly that logic is tested and how fragile it can be once the organization moves from design into execution.
Consider this common scenario: A regional team has a local brand that’s critical to their specific market but marginal at an enterprise level. Under a newly category-led operating model, that brand requires innovation investment to remain competitive locally, yet it doesn’t align with stated enterprise priorities.
Who decides? The category leader accountable for global performance? The regional GM accountable for local results? R&D, who controls the resources?
Under the previous model, this tension was often resolved through relationships, precedent, or informal negotiation. Under the new model, innovation leaders are often left without clarity about how nuanced decisions should be made, or how to ensure consistency across the organization.
This isn't a rare occurrence; it's simply what happens when a new operating model meets human inconsistency. And this is often where innovation execution begins to slow.
The symptoms are predictable:
The instinctive response is to redesign the innovation process: add rigor, tighten stage gates, and refine criteria. But process changes rarely resolves the underlying issue, because the problem here is not process. It’s the absence of an innovation operating model that is designed explicitly as a decision-making system, and followed with discipline, enabling the translation of enterprise strategy into execution-level choices.
What is often missing is the translation layer between the two: the explicit logic by which enterprise priorities become repeatable decisions. Without that translation layer, and the required discipline, organizations tend to fall into one of three patterns:
None of these outcomes reflect a poorly designed operating model. They reflect a lack of sufficient translation to govern decisions under the new enterprise logic.
For organizations navigating operating model change, three questions quickly expose whether the innovation operating model is fit for purpose:
Innovation slows when these questions can't be answered reliably, largely because the governance and decision logic has not caught up with the operating model.
Closing the translation gap is a challenge of discipline, not just design.
Every priority framework creates winners and losers. Every decision rights model constrains autonomy. Governance only works when leaders are willing to accept decisions they may not agree with because the system, not individual judgment, determined the outcome.
This is uncomfortable. It is also where many operating model transformations falter. Exceptions accumulate. Decisions are relitigated. Over time, the framework becomes optional. These actions are more likely to result in ambiguity than flexibility, and ambiguity is corrosive for innovation teams trying to plan, prioritize, and execute over multi-year horizons.
Operating model change is more than a structural exercise: It's a test of whether an organization can design and sustain better decisions.
For innovation leaders, process excellence is not enough. Innovation operating models must function as decision-making systems that translate enterprise strategy into disciplined choices across brands, markets, and portfolios.
Ready to close the innovation gap? North Highland brings the talent and technology to help organizations build innovation operating models that hold up under pressure.