Real Deals: Why an obsession with big data is costing dealmakers dear

By Nicholas Neveling
This contains excerpts from Neveling's article available online here at realdeals.eu.com

The editor of Real Deals Magazine, a UK based publication about Private Equity, spoke to Mikkel Rasmussen about ReD Associates, the dangers of over-reliance on big data, and why social science just might be one of private equity’s greatest tools.

ReD has led a “quiet revolution” in business theory by focusing on immersion in the day-to-day world of the customer rather than taking a distant, data-driven approach.

Rasmussen is co-founder and European director of ReD Associates, a firm founded 15 years ago in Denmark with the goal of applying the human sciences to business. Since its inception, ReD has grown to over 90 staff in their New York and Copenhagen offices and has led a “quiet revolution” in business theory by focusing on immersion in the day-to-day world of the customer rather than taking a distant, data-driven approach.

Given how often buzzwords like “big-data” and “artificial intelligence” are thrown around in the financial industry then, it may be surprising to learn that private equity firms have been increasingly calling on ReD to help them understand the drivers behind trends.

But Rasmussen argues that it’s a natural match. “Private equity invests substantial amounts of money and makes judgements on what is going to happen in the future. It should come as no surprise that it seeks an understanding of what is driving human behaviour.” As Rasmussen notes, “if you rely entirely on data, you strip decision making of all context. Data is incredibly valuable, but on its own it does not provide insight. It does not explain why… You can’t sit in an office trying to quantify and reduce everything to a data point. You need to understand how people behave and why they do things. It is important to recognise that when people take out a mortgage they are not buying a financial product, they are buying a home. When children buy toys, they are actually buying play. When you buy a television, you are buying entertainment. If business wants to understand why consumers buy its products and what it needs to do next to meet customer needs, it must gain understanding of how people experience and behave in the real world.”

That isn’t to say that method and rigor can go out the window. On the contrary. “All [ReD’s] people have gone through rigorous training and we invest a huge amount in codifying what we do,” says Rasmussen. “We do not build models and metrics, but we do collect data. On every case we work on, we build up files that include hundreds of thousands of artefacts, linguistic analyses, photographs, diaries and field notes. The minimum amount of time we spend on a project is 12 to 15 weeks. We like to go deep. Exercising judgement lies at the heart of any business decision, but that judgement must be based on evidence and thorough observation.”

Rasmussen cites Lego as an example of a company that adopted this method— that took a step back from data and focus groups and looked for answers by taking a qualitative approach to understanding the people playing with its toys.

While the rest of toy the industry was, according to Rasmussen, pouring money “into making toys with lots of noises and flashing lights that would hold a child’s attention,” Lego’s investigation helped them realize that children didn’t play for superficial entertainment, but to establish hierarchies, develop mastery, and explore independently from their parents. As a result, Lego brought focus away from the flashier sides of their products and “back to the brick,” which fundamentally fulfilled all the motivations behind play they discovered.

This insight, along their deep understanding of the reasons for play, has helped Lego to more than quadruple revenues at a net margin of more than 35 per cent over the last decade. Annual revenues now sit in excess of €5bn, the company has surpassed Mattel as the largest toy group in the world and topped Ferrari in some brand league tables.

With this kind of success then, it makes sense that the future may require more “old fashioned methods than many think.”


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