Sleeping Barber - A Marketing Podcast

Why do organizations say innovation is mission-critical, then create conditions that make innovation almost impossible?
Fiona Stevenson has spent her career on both sides of that problem.
After 12 years at Procter & Gamble, she co-founded The Idea Suite, an innovation consultancy that has worked across hundreds of innovation projects. She is also the co-author of Built for Breakthrough: Why Innovation Fails and How Smart Leaders Get It Right.
In this conversation, Fiona joins Marc and Vassilis to unpack why innovation usually fails long before the idea itself is tested.
They explore the famous Febreze story and why understanding the actual consumer problem changed the brand’s trajectory, before getting into the organizational conditions required for innovation to survive.
Fiona explains why big innovation ambitions often collide with tiny budgets, part-time teams and unrealistic timelines; why past data can become dangerous when designing for the future; and why innovators need to build evidence instead of waiting for certainty.
The conversation also covers Fiona’s six-stage innovation framework:
Identify → Insights → Inspiration → Ideation → Iteration → Implementation
And perhaps a seventh: Intuition.
Plus:
Why “we should…” is not an idea
Why “How might we?” is such a powerful innovation question
How AI is dramatically lowering the cost of prototyping
Why AI should be an input, not the final output
How implementation destroys good ideas through “death by a thousand cuts”
Why innovation needs dedicated time, not calendar scraps
How to create an innovation charter
Why the best first step is simply defining the problem properly
If your organization wants innovation but struggles to actually get ideas into market, this episode is for you.
Enjoy the show!
Chapters:
00:00 Why Innovation Dies Before the Whiteboard
01:36 Meet Fiona Stevenson
02:16 From P&G to Innovation Consulting
04:07 Moving From Client Side to Consulting
05:41 The Febreze Innovation Story
09:09 Why Consumer Understanding Comes First
10:59 What Is Innovation, Really?
13:02 The Uber Opportunity Fiona Turned Down
14:24 Different Types of Innovation
16:23 Big Innovation Ambitions vs. Organizational Reality
17:44 Why Stakeholder Alignment Matters
20:16 The Innovation Charter
21:24 Fear and the Unknown
22:00 Why Past Data Can Mislead Innovation
23:48 Why Great Marketers Can Struggle With Innovation
25:29 Getting Innovation Out the Door
27:24 The Future Has No Data
28:04 Challenging Assumptions With First Principles
30:00 AI as a Tool for Building Evidence
32:00 AI, Prototyping and Creative Potential
32:51 AI Should Be an Input, Not the Output
34:15 “We Should” Is Not an Idea
36:03 Why “How Might We?” Changes the Conversation
37:39 Fiona’s Six I’s of Innovation
39:09 Insights, Inspiration & Ideation
40:28 Why Iteration Matters
41:53 Implementation and Death by a Thousand Cuts
42:18 Protecting the Idea’s DNA
42:45 Is Intuition the Seventh I?
45:05 Why Skipping Steps Kills Innovation
47:06 The Most Undervalued Stage
48:49 How Innovation Survives Budget Pressure
50:17 Why Innovation Can’t Be a Side Job
51:39 What to Do Monday Morning
53:48 Why Innovation Needs Champions
54:26 It’s Never Too Late to Redefine the Problem
55:41 Built for Breakthrough Resources
56:11 Where to Find Fiona
Link to the book:
Built for Breakthrough - https://www.builtforbreakthrough.com/

Marketing has never been more measurable. It may also have never been more short-term.
If measurement was supposed to solve marketing's credibility problem, why hasn't five years of better data increased CEO confidence in marketing?
In this Sharp Cut, Marc and Vassilis unpack what happens when the things marketing can observe quietly become the things organizations value.
They trace the progression from visibility → accountability → optimization → observability, and ask whether attribution windows, platform dashboards and ROI have inadvertently trained marketers to optimize for short-term outcomes.
Using research from Boathouse, the Norwegian marketing industry and others, they explore why the same data can produce radically different conclusions depending on how it is framed.
They also tackle a harder question: who is responsible?
Is finance forcing marketing to think short-term? Or have marketers quietly accepted the measurement windows handed to them by platforms and brought those definitions of effectiveness into the boardroom?
The answer turns measurement into something much bigger: a leadership decision.
Because the moment you choose the window, you decide what value counts — and what value doesn't.
Chapters:
00:00 Marketing Has Never Been More Measurable
00:50 More Measurement, Same Confidence
02:14 Marketing Won the Seat but Lost the Argument
03:49 How Measurement Became Optimization
05:13 When What We Can Observe Becomes What Counts
05:30 The Fishing Net Problem
06:47 Where Leadership Enters the Measurement Debate
08:38 Are Marketers Responsible?
09:12 When Marketing Takes Credit for the Weather
11:16 The 35 Forces That Affect ROI
12:09 The Halo Effect
13:30 Same Data, Two Completely Different Answers
15:45 The Retail Number That Changes the Story
16:26 Why Every Channel Wants More Budget
17:57 Measuring Podcast Advertising With the Wrong Net
20:07 The Problem With the 95:5 Rule
21:46 Why ROI Can Mislead
24:06 How Cutting Spend Can Improve ROI
25:20 What Does “Return” Actually Mean?
27:03 When Long-Term Evidence Loses to the Quarter
28:23 Can Marketing Choose a Different Window?
31:29 Measurement Becomes a Leadership Problem
32:42 You Can Predict the Answer by Looking at the Net
34:07 Five Questions to Ask Before Measuring
35:00 What Marketing Can Learn From Finance
35:35 The Measurement Problem Is a Leadership Problem
35:59 What Comes Next: Discounted Cash Flow
Episode Sources:
Boathouse, Fifth Annual CEO Study on Marketing and the CMO, 150 US CEOs, fielded January 2026. Coverage via Marketing Dive, SmartBrief, CommPRO.
Gartner, May 2024, CMO survey on internal skepticism of marketing value.
Calgary Marketing Association and Stone-Olafson, 2024 ROI report, Alberta marketers, n=124.
Kapero, ANFO and the Norwegian Media Businesses’ Association, The Commercial Power of Brands in the Digital World, 13 Norwegian companies, 2024 data.
Podscribe, Conversion Rate by Podcast Player, more than 50 direct response brands, 30 daywindow.
Quatical, The 35 Factors That Affect Marketing ROI.
Rosenzweig, P. (2007). The Halo Effect. Free Press.
Eddington, A. S. (1939). The Philosophy of Physical Science. Cambridge University Press. The ichthyologist parable, told in summary. No direct quotation used.

Are marketers getting better at measuring activity while getting worse at understanding value?
In this edition of The Barber’s Brief, Vassilis and Marc unpack four marketing debates that caught their attention.
First, the agency industry's truth-in-pricing problem: agencies teach clients to build premium brands while continuing to sell their own expertise through hours and headcount. As AI changes how quickly work gets done, what should clients actually be paying agencies for?
Then, a provocative challenge to Byron Sharp and the Ehrenberg-Bass school of thought: if mental and physical availability are table stakes, what actually allows a brand to break away from the competition and win?
The conversation then turns to attribution vs. incrementality, and why creators, affiliates and reviews can appear to generate revenue without necessarily creating incremental demand.
Finally, we explore pricing power and the idea that the biggest danger isn't failing to become a premium brand. It's losing the ability to set your own price.
And for Ad of the Week, Spotify shows how data, culture and great outdoor creative can create personalization at scale without needing to personalize advertising to individuals.
In this episode:
Why agency pricing may be fundamentally broken
What AI means for the billable-hour model
Mental and physical availability vs. competitive strategy
Roger Martin's “Where to Play / How to Win”
Attribution vs. incrementality
The changing role of creator and review content
Why pricing power is really permission
Spotify's hyperlocal OOH campaign
Why creative can be the targeting mechanism

Chapters:
00:00 Welcome to the Barber’s Brief
01:23 The Marketing Industry’s Truth-in-Pricing Problem
03:36 What Should Clients Actually Pay Agencies For?
06:54 Why the Agency Model Is So Difficult to Change
09:14 Will AI Actually Reduce Agency Costs?
11:04 The Mental & Physical Availability Trap
14:52 What Actually Helps a Brand Win?
16:06 Breaking Out When Every Competitor Plays the Same Game
18:58 Attribution vs. Incrementality in Creator Marketing
21:18 How Creator Content Changes Value Over Time
22:49 Do We Have Too Much Attribution Data?
24:23 Pricing Power: Permission, Not Intent
28:20 Have Discounts Trained Consumers to Wait?
31:28 Ad of the Week: Spotify’s Hyperlocal Playlists
33:56 Why Spotify Gets Personalization Right
35:41 What’s Coming Next
37:12 Stay Sharp
Links:
The marketing industry's truth-in-pricing problem (and why adland is to blame)
Link: https://www.mediaweek.com.au/marketing-industry-truth-in-pricing-problem
Off Kilter 232: The Availability Trap.
Link: https://offkilter.substack.com/p/off-kilter-232-the-availability-trap
How to measure the true value of creators and review content
Link: https://searchengineland.com/value-creators-review-content-485028
Pricing Power
Link: https://www.linkedin.com/posts/mary-kyriakidi-4a5a4a57_when-i-talk-about-pricing-power-the-question-share-7496127277890568192-nzTS/
Ad of the Week - Spotify
Spotify turns playlist names into hyper-local punchlines
Link: https://www.thedrum.com/news/ad-of-the-day-spotify-turns-playlist-names-into-hyper-local-punchlines

AI is going to take our jobs. AI will commoditize creativity. AI will make strategy worse.
But AI isn't making those decisions. We are.
In this PostPod, Marc and V reflect on their conversation with Pats McDonald, Chief Strategy Officer at dentsu, and explore one of the most important ideas emerging from the AI conversation: human agency still matters.
They discuss why AI may eliminate barriers without eliminating expertise, how LLMs naturally pull marketers toward the average, the danger of settling for “strategy-ish,” and why faster answers don't necessarily produce better thinking.
The conversation also explores what AI means for specialists and generalists, how marketing organizations may need to evolve, and why companies may eventually need to onboard their AI systems with the same strategic frameworks, principles and ways of working they use to onboard their people.
Because the biggest question may no longer be what AI can do.
It's what we're going to choose to let it do.
Chapters:
00:00 Stop Blaming AI
00:46 Reflecting on Pats McDonald
02:02 AI, Jobs and Human Agency
03:00 AI Is Removing Barriers to Entry
05:13 Why Expertise Still Matters
06:36 Design for Difference, Not Sameness
09:27 The Danger of “Strategy-ish”
11:24 When AI Becomes “Good Enough”
13:53 Do We Still Need Specialists?
14:58 The Marketer of the Future
16:16 Why AI Still Needs Human Expertise
17:07 Turning Ideas Into Reality Faster
20:16 Human Agency Still Matters
20:27 AI and Strategic Drift
21:30 Keeping AI Inside the Strategic Framework
24:00 Should Companies Onboard Their AI?
26:29 Final Thoughts

What if the biggest mistake we're making with AI is the way we talk about it?
Pats McDonald, Chief Strategy Officer at Dentsu Creative, joins the Sleeping Barber Podcast to challenge one of the dominant narratives surrounding artificial intelligence: that AI itself is determining what comes next.
Her argument is simple: AI doesn't make these choices. People do.
We explore what that means for marketers, strategists and leaders as AI becomes embedded in everyday marketing practice.
Pats explains why AI's greatest opportunity isn't simply doing more with less, but enabling ideas that previously weren't possible. We discuss the danger of “strategy-ish”—plausible, polished strategic thinking that never gets somewhere genuinely distinctive—and why strategists should use AI to identify category conventions so they can deliberately break away from them.
We also tackle one of the biggest organizational questions surrounding AI: if technology increasingly performs the work traditionally given to junior marketers, how do we develop the next generation of senior talent?
Plus:
Why strategists need to understand both consumers and algorithms
Why curiosity may become more valuable than having all the answers
How AI can expose category clichés and strategic blind spots
Why data hygiene and fact-checking become even more important
How AI could become institutional memory for brands
Why marketers should design for difference rather than scale sameness
What responsible AI leadership actually looks like

Ultimately, Pats leaves us with a powerful distinction:
Stop saying “AI will.” Start asking what people, enabled by AI, will choose to do.
Chapters:
00:00 - Introduction
01:03 - Stop Saying “AI Will”
02:58 - How AI Is Changing Strategy
05:40 - Doing What Wasn't Possible Before
06:50 - What Happens to Junior Talent?
08:35 - Specialists vs. Generalists
11:35 - Curiosity as a Strategic Skill
13:45 - Can AI Accelerate Curiosity?
15:10 - Why Leaders Must Keep Learning
16:50 - The Danger of “Strategy-ish”
18:10 - Designing for Difference, Not Sameness
19:45 - AI, Bias and Strategic Blind Spots
21:05 - Why AI Still Needs Fact-Checkers
22:45 - Can AI Prevent Strategic Drift?
24:15 - AI as Institutional Brand Memory
25:55 - Great Examples of AI in Creativity
27:35 - AI Becomes Part of the Creative Toolkit
28:50 - Human Agency and the Future of AI
30:05 - Stop Saying “AI Will”