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”

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.

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.

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