The $155M Blind Spot: Why Big Strategy Projects Fail

The failure isn't strategy. It isn't alignment. It's a customer understanding that never went deeper than a checked box.

A widely shared breakdown made the rounds this week. A top-tier consultancy, reportedly paid around $155M across three years, advising a media giant into a merger and then back out of it. Tens of billions in market value gone in the meantime.

I have no inside knowledge of that engagement, and the numbers circulating are reported, not audited. But the shape of it is one I recognise from twenty-five years of watching high-stakes decisions get made. To me this is a textbook case of the largest blind spot management consultants and the C-suite share.

Two explanations that don't hold

Why would a failure of this size happen at all?

Are they not that good at crafting strategies? Who else should be better. The people in those rooms are trained, sharp, and have seen more industry structures than anyone on the client side ever will. If the craft of strategy were the problem, the fee would never have been paid twice.

Are they not that good at organisational alignment? I would guess a large deal of that money went on just that. Workshops, steering committees, stakeholder maps, the machinery of getting a few thousand people to move in one direction. That part usually works. It is the most visible thing a consultancy delivers, so it is the thing that gets resourced.

So the strategy was well built and the organisation moved. And the thing still collapsed.

The reason is a customer understanding that stopped too early

The reason for so many multi-billion failures is a too shallow customer understanding.

Consider what the decision in that media case actually rested on. Combine two brands, then rename the product, then rename it again, then rename it back, then split the brands apart. Every one of those moves is a bet on the same underlying question: what does the customer want this thing to be, and what will make them keep paying for it?

That question does not get answered in a synergy model. It gets answered by understanding demand. And here is the part that makes it so hard to catch: nobody sees this as a gap, because the checkbox "market research" was checked.

A checked box is not looked at again. That is its entire function. Somebody ran a segmentation, somebody fielded a brand tracker, somebody presented a deck with a customer chapter in it. The question is now marked as handled, and the room moves on to the part that feels like real work. Nobody in that meeting is being careless. They are doing exactly what the process tells them to do.

This is the mechanism I call shallow customer understanding: research was done, so the question is treated as answered, while what was measured was never capable of answering it.

Why conventional insights are shallow by construction

And here starts the problem. Conventional customer insights neglect the findings of neuroscience of the last decades.

They measure what people say and think. Not what unconsciously moves behaviour.

Run the standard study on a brand rename. Two thousand respondents, clean sample, good fieldwork. Ask them which name they prefer, how the new positioning makes them feel, how likely they are to keep subscribing. They will answer every question. Willingly, politely, at length. And what comes back is a set of reasons constructed on the spot for a decision that, in real life, is made in milliseconds by a mind that never consults the reasons.

Nobody in that process is lying. They simply have no access to the mechanism. This is the say-do gap, and it does not get fixed with a bigger sample. See also: why customers can't tell you why they buy.

Then the fieldwork is flawless, the deck is beautiful, and the assumption underneath it was wrong from the start. Wrong remains wrong. Everything built on top of it inherits the error, and the error compounds quietly for three years until the write-down makes it visible. That is what a wrong insight actually costs, and it is almost never booked against the research budget that produced it.

Depth is a method question, not a budget question

The fix is not more research. Volume is what got everyone here. The fix is research that reaches the layer where the decision is actually made.

Two things have to change.

1. Measure what people can't tell you

Reaction-time based implicit measurement gets at what a brand or a proposition is linked to before the respondent has time to build an explanation. Fast responses signal intuitive certainty. Slow ones signal deliberation, which is exactly what the buying mind does not do. That is the Frame, Measure, Infer sequence, and it is the only part of this that requires new instrumentation.

2. Separate the drivers from the passengers

Correlation leads astray. Standard statistical models get biased by multicollinearity, because in a real market everything moves with everything else. Causal AI is what separates the factors that cause demand from the ones that merely travel alongside it. Satisfaction, awareness and preference all correlate with revenue. Only some of them move it, and the ranking flips more often than anyone is comfortable admitting.

Do those two things and the customer chapter stops being a checkbox. It becomes the part of the strategy you can actually stress-test before spending nine figures on it.

The uncomfortable version

Here is the line I keep coming back to.

A management consultancy for growth topics that is not leading in nailing customer understanding is a risk factor.

Not a gap in the service portfolio. A risk factor. Because the client is buying certainty about a decision, and the one input that determines whether the decision is right is the one input nobody in the room is instrumented to challenge. The strategy work is genuinely excellent. It is excellent on top of a guess.

Which is also why the same advice is worth challenging even when it comes from the best firm in the world. Not because the consultants are wrong more often than anyone else. Because the thing they are least equipped to verify is the thing everything else depends on. If you want the practical version of that conversation, here is how to challenge your MBB consultant.

Roughly 5% of brands grow, 5% of products survive, 5% of campaigns work. The same 5% keeps showing up, and what they share is not a better deck. They stopped guessing about why people buy. The whole story is in THE TOP 5%.

So before the next nine-figure decision: do you know what drives your customers, or do you know that somebody once checked the box?

Shallow customer understanding: frequently asked questions

Why do expensive strategy projects fail?

Rarely because the strategy was badly crafted or the organisation refused to align. Top consultancies are good at both, and most of the fee buys exactly those two things. Multi-billion failures usually trace back to a customer understanding that was too shallow. The strategic logic is sound. The assumption about what customers actually want, sitting underneath it, was never tested against behaviour.

What is shallow customer understanding?

It is the condition of having done market research and therefore assuming the question is settled. Studies were run, decks were presented, the checkbox was ticked. What got measured was what people can consciously state, not what unconsciously moves their behaviour. Because the box looks checked, nobody looks again, and every decision built on top inherits the error silently.

Why doesn't conventional market research prevent this?

Because it asks people to explain choices they never consciously made. Decades of neuroscience show that buying decisions are formed intuitively and justified afterwards. Conventional methods capture the justification. Respondents cooperate, rate the concept, and give reasons that sound sensible. Nobody is lying. They simply have no access to the mechanism that will decide the outcome. More on that in why market research fails.

How do you know if your customer understanding is deep enough?

Ask one question of your last research: does it tell you what causes purchase, or only what correlates with it? If the deliverable is a ranking of stated importance, satisfaction scores, or attribute agreement, you have a description of what people say. Deep understanding names the mechanism, survives being tested against actual behaviour, and would have changed the decision if it had come out differently.

Dr. Frank Buckler is the founder of SUPRA and a pioneer in Causal AI for marketing. He has applied implicit research methods across FMCG, pharma, financial services, and insurance for over 25 years. His current book is THE TOP 5%.