The Messy Reality of Transforming Operating Models: Lessons from the Trenches

In my last article ( https://www.linkedin.com/posts/raganmcgill_activity-7294526327041261568-DrlYhttps://www.linkedin.com/posts/raganmcgill_activity-7294526327041261568-DrlY ), I shared a picture of a future-ready operating model rooted in Team Topologies, talent-driven practices, and social learning ecosystems. It’s a model designed to unlock speed, autonomy, and continuous learning while ensuring alignment with strategic goals.

But let’s be real - theory is tidy, reality is messy.

Transitioning to a new operating model isn’t just about organisational charts and frameworks. It’s about people, behaviours, mindsets, and systems - all tangled together. And as with any transformation, I've experienced challenges over the years that don’t always fit neatly into a slide-deck or playbooks.

Here are 10 messy realities I've encountered over the years, along with lessons learned along the way.

1️⃣ Matrix Management: Multiple Managers, Multiple Dynamics

🔥 The Challenge:

When we shift to this model, people often find themselves with more than one “manager.” Suddenly, there’s a practice manager supporting personal growth and a manager in the deployed team focused on product outcomes. This can create confusion:

• Who do I go to for feedback?
• Who’s responsible for my development?
• Who decides my priorities?

🤔 Lessons Learned:

• Leadership as a team, Not a title: I’m a big fan of leadership teams instead of single-point managers. In deployed teams, leadership should represent feasibility, viability, and desirability - bringing clarity, not command to teams. In the practice world, leadership promotes a people positive POV.
• Reframing Line Managers as Coaches: I’m not fond of the term "line manager" in this context. The day-to-day pastoral care is lightweight. Instead, my preference is to position them as coaches who help people become the best version of themselves.
• Flexibility is Key: Moving between coaches should be encouraged, not seen as disloyal. Imagine being supported by Wendy, who’s brilliant at strategic thinking, then asking to be supported by John, who excels at personal branding - both of whom will propel you to greatness and who both have core line management capabilities. This flexibility helps people grow in diverse ways. build networks, etc
• Clear Roles & Responsibilities: I’ve learned the hard way that ambiguity breeds tension. Clearly defining who’s responsible for what helps reduce friction.

2️⃣ Primary Teams: Where Do I Truly Belong?

🔥 The Challenge:

For most people - like engineers - their primary team is their deployed delivery team, ideally long-lived and shaped around a product or a suite of products. But for managers, it’s more complex.

• An Engineering Manager might be part of both the Practice Leadership Team and the Product Leadership Team.
• This duality raises questions: Where do I focus my energy? Which team comes first?

🤔 Lessons Learned:

• Primary ≠ Only: Your primary team is where you spend most of your time, but it doesn’t mean you’re not part of others. The key is clarity on your role in each.
• Mandate Levels Matter: Define what decisions you can make in each team. It’s about having the right authority in the right context.
• Rituals for Connection: I’ve found that consistent team rituals (like retrospectives or alignment sessions) help people stay connected, even when juggling multiple team commitments.

3️⃣ Budgetary Constraints: The Hidden Hand Behind Every Decision

🔥 The Challenge:

Operating models like this sound exciting, but they require investment - in both time and money. And guess what? Budgets are rarely as flexible as we’d like.

• Delivery teams are often caught between delivering business outcomes and investing in their own sustainability (facets like tech debt management, regular maintenance, or cross-cutting initiatives such as observability and DevSecOps)
• Time feels like the ultimate luxury as there are always more sausages to push through the sausage factory

🤔 Lessons Learned:

• Mindset Shifts Around Prioritisation: It’s not just about funding projects; it’s about funding capabilities. Teams need the autonomy to balance delivery with sustainable and enduring technical health.
• Business and Tech Outcomes Are Interlinked: We need to educate stakeholders that investing in areas like platform resilience isn’t a nice-to-have - it’s what enables faster, high quality, delivery in the long run.
• Time is an Investment, Too: It’s not just about money. Giving teams space to learn, reflect, and improve pays dividends in productivity and quality down the line.

4️⃣ Mindset Shifts: The Invisible Barrier

🔥 The Challenge:

New structures are easy to design on paper. The harder part? Unlearning old habits.

• Leaders struggle to let go of control.
• Teams hesitate to take ownership.
• People cling to familiar processes, even when they no longer serve them.

🤔 Lessons Learned:

• Change Management Is a Continuous Process: It’s not a one-off workshop. It’s about ongoing conversations, coaching, and reflection.
• Celebrate Small Wins: Culture shifts don’t happen overnight. We’ve learned to spot and celebrate behaviours that reflect the new mindset.
• Psychological Safety is the Foundation: People need to feel safe to experiment, fail, and learn. Without that, no structural change will stick.

5️⃣ To Cascade or Align Goals? Both - But Differently

🔥 The Challenge:

In complex ecosystems, goal alignment can either become a tangled web or a dilution of value pushed through the team for individuals to deliver business outcomes - when they're not set up for success

• Individuals are charged with delivering key initiatives when their sphere of control or even influence are not appropriate
• There is no connection between business goals and team design - not appreciating that engineers, designers, etc have different skills to bring to the game

How do you connect the two without overwhelming people?

🤔 Lessons Learned:

• Individual goals often live in the practice ecosystem, focusing on skills, behaviours, and competencies.
• Team goals exist in the delivery ecosystem, aligned to business outcomes.
• Shift from “Cascading” to “Connecting”: Traditional models cascade goals top-down. Learn to connect goals horizontally and vertically, creating a web of alignment rather than a strict hierarchy.
• Acknowledge that a delivery team is the smallest unit of delivery for business value
• OKRs with Flexibility: OKRs (Objectives & Key Results) are useful, but they need to be adapted to allow for dynamic alignment, not just annual planning cycles.
• Transparent Goal Setting: Making team goals visible across the organisation helps individuals see how their work contributes to the bigger picture.

6️⃣ The Reality of Team Topologies: Messy Before It’s Smooth

🔥 The Challenge:

Team Topologies provide a great blueprint, but reality rarely fits neatly into predefined structures. Some teams have felt overloaded, while others struggled to define their purpose in the ecosystem.

🤔 Lessons Learned:

• You can’t ‘big bang’ Team Topologies – Moving to stream-aligned, enabling, and platform teams takes time. Phasing of this transition gradually is vital to the success of the model.
• Cognitive load mapping is essential – It’s not enough to assign labels to teams. There's a need to deeply assess where teams are struggling with cognitive overload and adjust accordingly.
• Be flexible with interactions – The Collaboration, X-as-a-Service, and Facilitation modes are useful, but teams need help defining and evolving their interactions over time.

7️⃣ Governance vs. Autonomy: Finding the Right Balance

🔥 The Challenge:

We set out to make governance an enabler, but, old habits creep in. Compliance functions defaulted to rigid controls, creating bottlenecks instead of guardrails.

🤔 What We Learned:

• ‘Just Enough’ Governance is key – Over-governance kills speed, while under-governance invites risk. The goal is to create enabling constraints that allow teams to move fast, safely and autonomously.
• Shift from ‘approval-based’ to ‘trust-based’ governance – Instead of approval gates, it's crucial to move toward self-service guardrails, where teams can self-assess compliance.
• Governance as a product – Treat governance frameworks like a product: iterative, feedback-driven, and continuously improving rather than static and one-size-fits-all.

8️⃣ The Struggle Between Practices & Delivery

🔥 The Challenge:

Practices are designed to be "homes" for talent development, but when they lack influence, they become side-lined. Teams prioritise short-term delivery over long-term development, and suddenly, practices feel disconnected.

🤔 What We Learned:

• Tie practice leadership to delivery success – When practices help teams solve real business problems (not just define standards), they gain credibility.
• Balance ‘support’ with ‘accountability’ – Practices shouldn’t just be advisory. They should own elements such as coaching, upskilling, and quality assurance.
• Prevent the ‘us vs. them’ mindset – Ensure practice leads don’t become gatekeepers. Instead, they should embed themselves within teams to build trust.

9️⃣ Rewiring Leadership Behaviours

🔥 The Challenge:

Many leaders are used to command-and-control decision-making. Moving to an empowered model requires leaders to shift from directive management to coaching and enabling. But this is easier said than done.

🤔 Lessons Learned:

• Not all leaders are ready to let go – Some - or even, many - struggle to transition from decision-makers to facilitators. Providing leadership coaching and feedback is critical.
• Decentralised decision-making needs boundaries – Without clear decision-making frameworks, autonomy can lead to chaos. Teams need clarity on what they can decide versus what requires alignment.
• Micro-managers will surface – In an outcome-driven model, micro-management has nowhere to hide. It’s important to address control tendencies early to avoid slowing teams down.

🔟 The Cognitive Dissonance of Change

🔥 The Challenge:

People intellectually understand the need for change, but emotionally, they resist it. Teams may acknowledge the inefficiencies of the current model, but when asked to shift to new ways of working, discomfort sets in.

🤔 Lessons Learned:

• Clarity beats certainty – No model is perfect from day one. It’s better to clearly articulate the intent behind the shift rather than pretending to have every detail worked out.
• Emphasise the ‘Why’ continuously – Change fatigue is real. Keep reinforcing why the shift is happening, especially as teams hit turbulence.
• Acknowledge the discomfort – Instead of pushing resistance aside, openly discuss what makes people uncomfortable. Often, it’s about uncertainty, not the model itself.

🔄 Embracing the Messiness of Change

At the end of the day, operating model transformations aren’t clean-cut projects. They’re living, breathing evolutions where what we think is the right answer now will bear little resemblance to what we acknowledge in the future to resemble an operating model that unlocks excellence.

The messiness is the work - fact!

• It’s where growth happens.
• It’s where assumptions are tested.
• It’s where real learning sticks.
• It's the rewarding part of the job...

If you’re navigating a similar transformation, I’d love to hear: What messy challenges have you encountered in operating model shifts? How have you navigated matrix management, goal alignment, or budget constraints?

Ragan McGill

Technology Leader

Engineering leader blending strategy, culture, and craft to build high-performing teams and future-ready platforms. I drive transformation through autonomy, continuous improvement, and data-driven excellence—creating environments where people thrive, innovation flourishes, and outcomes matter. Passionate about empowering others and reshaping engineering for impact at scale. Let’s build better, together.