Scale: Episode 2 | Flying through the fog: Six biases that wreck strategy

Dave Heywood (00:00)
It’s never been easier to create stuff, but deciding what’s worth making has never been harder. This is Scale, an OX7 Partners podcast, and I’m Dave Heywood.

Dave Heywood (00:12)
So what’s actually getting in the way here?

Why are brilliantly talented teams still making avoidable errors?

It’s not always down to a lack of data, and it’s certainly not a lack of effort or intellect. What I’ve seen and observed is a series of hardwired cognitive traps that filter reality

So today I’m doing a quick audit on six specific biases that ruin our decision making and what we can actually do about them. So let’s get stuck in straight away.

First of all, a classic external blind spot is survivorship bias. So by definition, this is the habit of focusing entirely on the people or things that made it while completely overlooking the massive graveyard of those that didn’t

So my go-to example here often is Amazon and specifically Jeff Bezos. So for every Jeff in the world, there are hundreds if not thousands of people who did exactly the same thing, worked just as hard, followed the same playbook, and ended up right back in middle management.

But 500 page biographies on people who tried and failed don’t really sell that well. And you typically tend to see the stories of one guy or girl who survived. So the lesson here is that if we only study the winners, we risk learning all the wrong lessons. when we look at Amazon today, we treat their whole…

market position and global dominance as inevitable. They saw something that no one else did. But if we go back to 1999, there was a company called Kozmo.com They had this brilliant promise of sub one hour delivery of convenience goods, books and food straight to your door. They’ve raised some funding too.

$250 million to be precise, and they had some pretty punchy brand awareness. They were one of the shining examples of the dot-com boom.

but they still failed spectacularly.

What happened here was they were paying bicycle couriers more in labour costs than the profit margins on the items they delivered. So they were literally losing money for each and every delivery.

Add in the prospect of highly perishable goods and you’ve got a business that’s got to move stuff particularly quickly and also not making any money in the progress. Do see the problem here? And Amazon survived because they anchored their early business to high margin, easily shippable and non-perishable items.

And they were able to hold that line until the boring, unsexy physical infrastructure of global logistics caught up with their ambition.

Our next filter is confirmation bias. And this is our natural habit of only noticing information that proves we’re already right.

if you’re only looking for evidence that you’re right, trust me, you will always find it. And today, it’s even easier than ever.

The poster child for this one is Quibi

I’ll forgive you if you’ve not heard of this. In 2020, they raised $2 billion on this idea that consumers wanted premium Hollywood produced 10 minute TV shows designed specifically to be watched vertically on a mobile phone during a commute.

The business was led by some real industry veterans, but once that hunch and idea was locked in, confirmation bias really, really took over. They looked at the macro trends of rising mobile video consumption and used it to validate product design and refused to see the counter signals.

vast sums of money on curated, vertically filmed dramas, this little app called TikTok was exploding onto the exact same mobile screens. Actually, what TikTok was proving here was that what consumers really wanted, beaming to mobile phones, was community-driven, low production value, interactive content with the ability to have

conversations with those creators as well. but Quibi’s leadership looked at TikTok and dismissed it. It didn’t fit their prestige high production narrative.

They spent $2 billion validating their internal assumption rather than looking at actual consumer behaviour and adjusting accordingly.

And all in all, the company folded in just six months.

Why didn’t nobody stop Quibi? Why did boards sign off on these hunches? Authority bias now enters the chat and this is the mental shortcut where your brain can overvalue the opinion of someone based solely on their title, status, even their perceived genius, regardless of what the objective evidence is saying. So if we turn to WeWork, for example now, at their absolute peak they reach

valuation of around $47 billion.

And that was mostly because the people backing it were considered the smartest guys in the room. So if a legendary tech visionary is writing a multi-billion dollar check, the rest of the market assumes that they must be seeing a transformative play here that everyone else is missing.

Except in WeWork’s case, there was no tech play. They were a traditional commercial real estate business, renting desks by the month.

while taking on massive long-term leasing liabilities. So traditional real estate analysts were waving the red flags for years, pointing out that the economics just didn’t really make sense

But authority bias created a collective hallucination here. And then to cut a long story short, following bankruptcy and a long drawn out return to private ownership, about $47 billion collapsed to a valuation of around $750 million.

an idea doesn’t become good just because someone says it with confidence and gusto.

And when these authority driven ideas start failing, we hit the most emotionally expensive bias here, the sunk cost fallacy. And now this is the absolute refusal to abandon a failing strategy because the time, money or personal ego you’ve already invested

The hardest thing here isn’t launching something. it’s killing a project you’ve already staked your name and reputation on. So let’s look at meta for that example, and the metaverse specifically. So back in 2021,

Mark Zuckerberg rebranded Facebook to align with a singular vision of digital avatars living in virtual reality. So he committed tens of billions of dollars to Horizon Worlds,

And within a year…

actual real usage metrics were really telling. The virtual worlds were empty. consumer interest just wasn’t there. but when your entire corporate identity and your legacy are staked on a concept you’ve stood up and backed to the hilt,

stopping feels like a public admission of defeat. So meta clung onto the metaverse for far too long because the reputational weight of pivoting was just too much to bear. It’s not too dissimilar to asking for just one more spin of a roulette wheel. Surely we’ll win this time. You can convince yourself that the next feature, the next campaign, the next update, that’ll be the one to turn it all around.

but it rarely ends You usually just end up paying a very high premium to delay the inevitable.

And before we look forward, we also have to look at what’s right in front of us. And this is where availability bias comes in. And this is where we assume that if something is easy to remember or front of mind, that it must be important. ubiquity for widespread necessity.

Now, if you remember Clubhouse back in 2020, they were treated at the time for around six months as the future of media. LinkedIn was going to die a very, very quick death and we’d all be jumping into these essentially audio chat rooms

And it really picked up the pace because in 2020, during the pandemic, we were all stuck at home, isolated, a bit bored. Brands and marketers really scrambled into the app like mad because it was the only thing that everyone seemed to be talking about at that time.

And we treated it as a massive market shift. But when the dust settled, it turned out it was for the most part mainly marketers getting excited with other marketers in a bit of an echo chamber here. And availability bias caused the entire industry to a highly visible signal, completely ignoring the long-term stable data that showed consumers just didn’t want to spend.

post lockdown lives listening to unedited corporate audio panels. And this brings us to optimism bias, the persistent habit of overestimating our likelihood for success, while at the same time underestimating the friction risks real world costs and challenges.

I see a lot of people fall into this trap who really want to be seen and perceived as can-do people. And we want to be enthusiastic and drive things forward.

But if we look at Google Glass, back in 2013,

Google was so optimistic about this technical marvel that they created that they almost treated consumer adoption as bit of a certainty.

They bypassed the normal validation steps and went straight for cultural saturation.

You might remember it was paraded through New York Fashion Week. They had a 12 page spread in Vogue and they were so blinded by their own hype that they forgot to ask a really important question. Does a normal person want to have a conversation with someone wearing a visible continuous recording device strapped to their face?

that completely ignored the social reality. We optimistically assumed that the brilliance of the tech would speak for itself And it was so overlooked that there was a specific term coined for people who walked around wearing these, glass holes.

Now, if we contrast that with how Snapchat launched their glasses a few years later, they knew that the tech was invasive and divisive. So they leaned into that friction. They made them bright plastic cheap toys, sold them through cartoonish yellow vending machines, and even added a highly visible spinning little LED light to signal when it was recording. So Snap designed for human behavior, and Google optimistically assumed that they could

completely bypass it.

And finally, let’s talk about the bias that completely warps our long-term planning, and that’s recency bias. And this is the idea of taking a temporary short-term data spike and treating it as a permanent shift So if we look back at Peloton, and again, this is another pandemic era example, global lockdowns hit.

gyms were closed and Peloton sales went absolutely through the roof. They were everywhere. And they looked at that data spike, and assumed that it wasn’t just an anomaly, but the new normal. They drew a straight line from that lockdown peak upwards to the tune of committing 400 million to build a brand new domestic manufacturing facility in the US.

to keep up with what they believed would be infinite future demand.

But the real world doesn’t always work like that. I tend to view things more like a little bit of a spring here. You can stress and pull it, it’ll snap back eventually. It might look a little bit different, but typically you’re not that far off from your baseline starting point.

And once gyms and wider society began to reopen, Peloton’s demand completely cratered. bikes, a factory that really wasn’t necessary anymore, and an absolutely brutal 90 % drop in their stock price.

Mistaking a temporary environmental condition for a permanent shift in behavior.

So let’s bring this back to you. So in a world where tools, templates, and AI mean we can build anything almost instantly, how do you guard yourself against some of this thinking?

You stop measuring your marketing success by pure output. And we start going through a process of auditing our strategic inputs.

So there’s five non-negotiable questions you really need to start filtering your strategy through. Think about it like filtering some dirty water.

So let’s really question the winners.

Who has failed doing exactly what we’re planning to do now? And what does that graveyard teach us that the success stories conveniently left out? We need to question the data. Are we seeking out data that proves our strategy is completely wrong? Or are we just seeking for backup and validation for something we’ve probably already decided on? We need to question the hype.

Is this channel or trend actually driving business value for our specific audience?

Or are we witness to an echo chamber? We need to question the future. Is recent performance a fundamental shift in the market? Or are we at risk of over-investing in a temporary stretch of the spring? And finally, we need to question our egos.

If this goes sideways, do we have clear kill conditions and acceptable losses, or are we going to keep spinning that roulette wheel to protect our reputation?

Thanks for listening.

I hope you found that useful. I’m Dave Heywood and this is Scale an OX7 Partners podcast.