Part 3 of 4

Written By: Johan Gauffin – Head of Commercial at ForgeSight 

The challenge is that organizations often mistake “change” for “automation,” then wonder why Foundry adoption plateaus after the first wave of efficiency wins.

The idea is to treat Foundry as a change catalyst that progresses through three predictable waves: automating work, reshaping decisions, and redesigning the operating model.

The takeaway is that leaders who plan for all three waves, metrics, incentives, training, sponsorship, and pacing, turn Foundry from a set of tools into a new way of running the business.

After strategy (Part 1) and governance (Part 2), the next question is the one executives eventually face, whether they asked for it or not: what does Foundry do to the organization?

Most teams begin with a straightforward ambition: automate what is manual, integrate what is fragmented, and reduce cycle time. That’s rational, and it’s also incomplete. Platforms don’t just speed up work. They change how work is done, what decisions get made, who makes them, and what the organization can credibly offer to customers and partners. If you treat Foundry purely as an automation engine, you’ll get some wins, then hit a plateau that feels like “adoption” problems but is really “change” problems.

A framing note, consistent with the earlier posts: ForgeSight isn’t selling Foundry. This series is for leadership teams who have already invested in it and are now navigating what comes next, scaling outcomes.

Foundry’s impact tends to arrive in three waves. You don’t need to label them internally, but recognizing the pattern helps leaders anticipate what’s coming and avoid being surprised by resistance that looks irrational from the outside.

The first wave is automation, doing the same work faster, cheaper, and with fewer errors. The second is decision change, improving what people know and how they decide, often forcing role changes, new habits, and new incentives. The third is transformation, redesigning how the organization is structured and what it can do in the market because the platform makes new operating models viable.

Each wave creates value. Each wave also creates friction if you haven’t designed the business to absorb it.

Automation is where Foundry earns its first trust. It removes manual reporting, consolidates siloed spreadsheets, accelerates compliance documentation, and reduces operational noise. These wins tend to be the easiest to justify because the economics are simple: time saved, errors reduced, cycle time shortened.

For leaders, the trap is not in pursuing automation. It’s in declaring victory too early. Automation is often what makes the platform visible, but it rarely makes the enterprise different. If the Foundry story becomes “we generate reports faster,” you’ve created efficiency without changing advantage. The better way to treat first-order gains is to treat them as credibility-building, and then use that credibility to sponsor the bigger changes that follow.

The executive move in this phase is to insist on measurement. If the initiative is worth doing, it should have a baseline and a delta, fewer hours, fewer exceptions, fewer stock reconciliation failures and fewer late compliance cycles. Those measures do more than prove value. They create a language for the organization to discuss outcomes rather than activities.

The more consequential change begins when Foundry stops being a reporting layer and becomes a decision layer. When planners are asked to trust a forecast they didn’t build in Excel, when operations teams are asked to prioritize based on risk indicators rather than intuition, when commercial teams are asked to use integrated customer signals rather than local knowledge alone, work changes.

This is where adoption stops being a training issue and becomes a management issue. People resist not because the tool is confusing, but because the tool changes status, identity, and routine. Foundry can make expertise more visible, but it can also make certain forms of “hero knowledge” less central. It can reduce the value of being the person who knows where the data lives and increase the value of being the person who can interpret it and act on it.

Leaders underestimate this shift because it is subtle. No org chart changes on day one. Yet the work feels different, and employees experience that difference as risk, fear of being evaluated differently, fear of losing autonomy, fear of being held accountable to new metrics.

The executive response here is to align sponsorship and incentives. If you want second-order change, you need senior leaders who can credibly say, “This is the new way we run planning,” then back it up by changing what is rewarded. If Foundry introduces a new set of leading indicators and the performance system continues to reward the old behaviours, the platform will become shelfware with a great user interface.

This is also where forward-deployed delivery models shine. Engineers and product teams working closely with operators can iterate in real time, remove friction, and translate insights into workflows. But second-order change still requires leadership to do what delivery teams can’t: set expectations, protect time for adoption, and enforce the behavioural pivot when the organization tries to revert to comfortable habits

Eventually, Foundry forces a bigger question: now that the organization has integrated trustworthy data and repeatable decision logic, what kind of company can it become?

This is a transformation, not in the marketing sense, but in the operating model sense. Foundry can enable control-tower models that coordinate end-to-end operations rather than optimizing within silos. It can support product-based ways of organizing work, where cross-functional teams own outcomes rather than projects. It can even make new services feasible, visibility products, analytics-driven partnerships, or commercial offerings that turn internal capabilities into customer value.

This is also the stage where technology stops being the limiting factor, and instead, leadership becomes the limiting factor. Structural change creates real winners and losers. It touches reporting lines, budget authority, and identity. If executives want the upside of third-order change, they have to be willing to absorb the discomfort that comes with redesigning how decisions are made and who owns what.

A practical bridge between “platform” and “new operating model” is a Center of Excellence or a product governance model that institutionalizes standards, reusable components, and shared practices while still enabling local innovation. The form will vary by enterprise, but the intent is the same: keep the platform coherent while scaling change.

Most Foundry programs that grow stagnant fail in the middle because leaders assume change will “follow” technology. It doesn’t. Change follows leadership.

There are a handful of patterns that consistently separate organizations that scale Foundry from those that plateau.

One is pacing. Rapid platform expansion can trigger change fatigue, new tools, new processes, new expectations and sometimes new structures. Executives need to sequence change in digestible waves and support those waves with visible sponsorship and local champions who can translate “why” into daily behaviour.

Another is iteration. Foundry rollouts are never “done.” Each wave of change should produce feedback that improves the next one. Leaders should treat the deployment as a continuous learning loop, what created value, what created friction and what new opportunities emerged once the first set of capabilities existed.

A third is benefit realization discipline. The point is not usage: it is outcomes. A system can be technically successful and strategically irrelevant. Each wave should connect to a measurable benefit, so the organization learns that Foundry is not “another platform” but a mechanism for results.

If Part 3 is about managing the waves of change Foundry creates, Part 4 is about sustaining momentum after the initial waves, demystifying the platform across the enterprise and building an organizational model that keeps Foundry generating new value rather than returning to steady-state complacency.

Acknowledgments
With thanks to Ben Menesi(LinkedIn) and Percy Rivera Salas(LinkedIn) for reviewing earlier drafts of this piece and offering thoughtful feedback that strengthened the argument and improved clarity. Any remaining errors or omissions are mine alone.

References and further reading
Ross, Jeanne W., and Peter Weill. “Six IT Decisions Your IT People Shouldn’t Make.” Harvard Business Review (November 2002).
Eastwood, Brian. “4 levers that create digital value.” MIT Sloan Ideas Made to Matter (October 16, 2023).
Pratt, Mary K. “Transforming IT for digital success.” CIO (October 23, 2023).

Author’s note:The “three waves of change” framing in this article was informed by coursework and class discussion in Prof. Suchit Ahuja(LinkedIn)EMBA 621 (Information Technology: Digital Strategy, Analytics & Transformation), Executive MBA, Concordia University (Winter 2026).