Taco or Not Taco: The Case for Being Data-Informed, Not Data-Led 🌮
“We want to be more data-driven.” It’s a phrase that sounds progressive, even essential. But it carries hidden risk.
28 May 2025
World-famous marketer Rory Sutherland, a leading advocate for the application of behavioural economics, recently shared the story of Taco Bell’s failed launch in London more than 15 years ago.
The location was central, the brand was well-established in the US, yet the launch flopped.
If you were looking at the data alone - footfall, revenue, conversion - you’d draw a simple conclusion: the concept didn’t work, and further expansion in the UK wasn’t worth pursuing. But what the data didn’t reveal was that the restaurant’s entrance was hidden down an alleyway. Customers simply couldn’t (easily) find the door. The data said it failed. Context told a different story.
In the same interview, Sutherland also pointed to Nokia, which had received data showing that consumers in developing countries wouldn’t pay more than a set amount for a phone. Based on this, they delayed launching a smartphone. But what the data missed was the leap in perceived value. Smartphones weren’t just better phones, they were people's first computers and their first access to the internet. As a result, demand didn’t follow historic price sensitivity. By the time Nokia realised this, the market had already moved on.
Performance strategist Rich Buchanan highlighted a similar blind spot within football.
On the latest episode of the Sports Pundit Podcast, he reflected on how scouting and recruitment processes often filter prospects using technical or tactical data.
“Maybe a player isn’t showing up in your filtered data set because their coach doesn’t ask them to do certain things. It doesn’t mean they can’t. You’re narrowing your lens based on data, not reality.”
The problem is mistaking clarity for truth. Data can feel objective and precise. But it’s only as good as the questions we ask of it and the context we apply around it.
“Lots of people take data with blind faith… but they haven’t sense-checked whether it’s valid or accurate. That’s your job as a practitioner.”
This is important to consider as there has never been more data in sport.
From player load to heart rate variability or fan engagement metrics to scouting algorithms, every facet of performance, operations, and strategy now comes with a spreadsheet, a dashboard, or an AI-generated insight. Having data is no longer a differentiator. It’s an expectation, even below the top tier.
But as the flood of data accelerates, so too does the pressure to let it lead. We hear it in boardrooms and changing rooms alike: “We want to be more data-driven.” It’s a phrase that sounds progressive, even essential. But it carries hidden risk.
Being “data-led” can sound empowering, but Buchanan warned it often means outsourcing judgment to a system.
“That, to a certain extent, means making decisions on data that you absolutely have to be sure is valid and accurate,” explained Buchanan. “You’re almost devolving yourself of decision-making responsibility and de-skilling yourself in your clinical reasoning or executive mindset.”
In elite sport, where margins are fine and decisions carry real consequences, blind deference to data can become dangerous. Instead, Buchanan championed a more balanced approach: be data-informed.
“What most people meant when they said they wanted to be data-driven is that they wanted an extra perspective. That’s what data-informed really means.”
This is where the human element matters.
“It’s that human skillset, that reasoning, that emotional intelligence, to understand that [data] might inform our opinion but not override it.”
So, use the data. Embrace it. Interrogate it. But don’t let it lead you blindly. Because in sport, as in life, the numbers don’t always tell the full story.