The Metric Trap: Are Your Dashboards Measuring Reality?

Don’t Automate Chaos: Why Most AI Transformations Fail

EPISODE TITLE OPTIONS Primary recommendation (sharp + timely): “Don’t Automate Chaos: Why Most AI Transformations Fail” Alternatives (more/less provocative): 1. “Rocket Boosters on Paper Planes: The AI Implementation Trap” 2. “AI Isn’t the Problem—Your System Is” 3. “Agentic AI, Real Risk: How to Avoid Scaling Dysfunction” 4. “The 80% AI Failure Rate: What Leaders Keep Missing” 5. “AI Transformation ≠ IT Project: The Systems Approach” EPISODE SUMMARY (LISTING COPY) Companies are spending thousands — even millions — on AI. And then… confusion. Worse outcomes. More complexity. More opacity. Sometimes, real reputational or legal blowback. In this episode of How to Build a Growth System, Colin and Chris unpack why so many AI rollouts are failing to deliver measurable value — and why the “race to AI” is pushing organisations into a dangerous pattern: automating broken systems. Drawing on widely reported failure rates (including claims that ~80% of organisations see no measurable positive impact), they argue the core issue isn’t the model, the vendor, or whether GenAI “works.” It’s that leaders are treating AI like just another tool rollout, when it’s actually a business transformation problem. The conversation explores: 1. Why AI often becomes “a rocket booster on a paper aeroplane” 2. How agentic AI can amplify risk when goals, rules, and context are unclear 3. Real-world cautionary tales (including public failures like AI drive-thru ordering and misguided regulatory chatbots) 4. The systemic causes behind bad outcomes: broken processes, contradictory information environments, weak governance, and unclear ownership 5. Why “move fast and break things” becomes far more dangerous with autonomous systems 6. The missing ingredient: systems education at the executive level And crucially, they outline what to do instead: treat AI as a transformation programme, understand and redesign the underlying system first, and only then layer intelligent automation on top — with governance that enables speed through clarity, not just legal risk mitigation. The takeaway is simple: AI can be a force multiplier — but only for organisations with foundations solid enough to multiply what works, not what’s broken.

Feedback Loops: The Signals Beneath the Dashboard

Dashboards get all the attention — but they don’t actually move the business. They just report the news. In this episode of How to Build a Growth System, Colin and Chris go one level deeper, exploring the signals underneath the dashboard and how to turn them into feedback loops that make your business faster, smarter, and harder to knock off course. They break down feedback loops in plain language: a loop isn’t a metric you monitor — it’s a signal that reliably triggers action and creates learning. From thermostats and sweating to customer reviews and churn, feedback loops are operating in every business whether you harness them or not. You’ll learn: 1. What feedback loops are (and why they’re the “control wiring” of the organisation) 2. The difference between reinforcing loops (that compound change) and balancing loops (that restore stability) 3. Why “flywheels” are only part of the story — and how loops interact across teams 4. How qualitative “quiet signals” (call transcripts, support themes, community chatter) can be better leading indicators than headline metrics 5. A practical way to audit your loops using signal → insight → decision → action and the hidden killer: latency 6. Common failure modes: listening too slowly, too much noise, and dead loops with no ownership 7. Why acting faster isn’t always better — and how overreacting can create oscillations and unintended side effects The big takeaway: if you want dashboards that truly help, start treating them as gauges of the loops that drive behaviour, not a wall of numbers. Tune into the right signals, assign ownership, and build operational rhythms that turn feedback into action — at the right speed.

The Metric Trap: Are Your Dashboards Measuring Reality?

Summary In this conversation, Colin and Chris explore the dysfunctions caused by poorly designed dashboards in organizations. They discuss how metrics can mislead teams into believing they are successful while the reality is quite different. Through examples like the Royal Bank of Scotland, they illustrate the dangers of metric fixation and the importance of designing dashboards that reflect true performance. The discussion emphasizes the need for a cultural shift towards valuing truth and learning over mere numbers, and offers practical advice for revenue leaders on creating effective dashboards that drive meaningful outcomes. Takeaways 1. Dashboards often misrepresent reality, leading to false success. 2. Metric fixation can create a culture of gaming the system. 3. Siloed dashboards can cost businesses over a trillion dollars annually. 4. Goodhart's Law highlights the dangers of tying metrics to compensation. 5. Effective dashboards should have counter metrics to prevent gaming. 6. Shared ownership of metrics can reduce departmental silos. 7. AI can help refine metrics but doesn't replace the need for good design. 8. Cultural change is necessary to prioritize learning over gaming. 9. Identifying toxic dashboards is crucial for organizational health. 10. A minimum viable dashboard should focus on a few key metrics. Chapters 00:00 The Dashboard Dilemma 02:05 The Illusion of Success 06:36 The Cost of Metric Fixation 09:53 Goodhart's Law and Its Consequences 14:30 From Good Intentions to Dysfunction 21:00 Identifying Toxic Dashboards 23:55 The Dashboard Dilemma 27:36 Designing Effective Dashboards 33:00 Shared Metrics and Collaboration 35:00 The Role of AI in Metrics 38:15 Practical Advice for Revenue Leaders 43:52 Cultural Shifts in Metrics Management

When Growth Becomes the Problem: Understanding Growth Debt

Fast growth is supposed to feel like momentum. But for many companies, it quietly turns into friction. In this episode of How to Build a Growth System, Colin and Chris unpack the concept of growth debt — the organisational equivalent of technical debt — and why it may be costing scaling companies 20–30% of their revenue without anyone realising. Starting with Stripe’s finding that a third of developer time is lost to technical debt, the conversation zooms out to show how similar dynamics play out across people, processes, systems, and culture. The result? Teams working harder than ever, yet delivering less. Strategy that looks great on slides but never quite lands. And organisations that slow down just as they try to accelerate. Through a real-world SaaS case study, Chris explains how a well-intentioned attempt to speed up sales created cascading failures across customer success, marketing, onboarding, and data — a textbook example of growth debt compounding over time. The episode explores: 1. What growth debt actually is (and why it’s more dangerous than technical debt) 2. How complexity, context switching, and tool sprawl erode performance 3. The warning signs leaders miss — from stalled strategy execution to rising churn 4. Why throwing more tools, people, or budget at the problem usually makes it worse 5. Practical ways to surface, measure, and start paying down growth debt before it becomes existential The key takeaway? Sustainable growth isn’t about moving faster everywhere — it’s about knowing where to slow down, reducing complexity, and designing systems that still work when you double in size. If you’ve ever felt like your organisation is running at full speed but getting nowhere, this episode will help you see why — and what to do next.

Why Silos Are a Symptom of System Failure

Most leaders treat silos as a collaboration problem. In this episode, Chris and Colin argue they’re something else entirely. Silos aren’t caused by people failing to work together — they’re the natural output of the systems those people are working in. Through real-world examples, systems thinking, and practical tools, this episode breaks down: 1. why smart, well-intentioned teams still end up working at cross-purposes 2. how organizational structure quietly overpowers individual intent 3. and what leaders can actually do to diagnose and fix the real causes of siloed behavior. This is a diagnostic-first conversation focused on fixing systems, not blaming people. WHAT YOU’LL LEARN IN THIS EPISODE 1. Why silos form even when everyone is competent and motivated (Hint: structure beats intent, every time.) 2. The difference between people problems and system problems — and how to tell which one you’re actually dealing with. 3. Why “alignment meetings” rarely create alignment and often make the underlying issues worse. 4. How Conway’s Law shows up in customer experience (your org chart leaks into your product). 5. Why coordination costs rise exponentially as organizations scale — and what that means for growth teams. 6. How to spot systemic friction including misaligned goals, unclear ownership, broken handoffs, and siloed data. 7. Value Stream Mapping, explained simply and why it’s one of the most powerful tools for diagnosing growth friction. 8. A concrete lead management example showing how hours of delay and wasted effort can be eliminated with better system design. 9. The role of shared goals, shared context, and incentives in breaking silos sustainably. 10. Practical advice you can apply this week without mapping your entire organization or launching a transformation program.