Many years ago, Clay Christensen visited his firm where I was a partner and told us a story*.
“I imagine the day I die and present myself at the entrance to Heaven,” he said. “The Lord will show me around, and the beauty and majesty will overcome me. Eventually, I will notice that there are no numbers or data in Heaven, and I will ask the Lord why that is.”
“Data lies,” the Lord will respond. “Nothing that lies can be in Heaven. So, if people want data, I tell them to go to Hell.”
We all chuckled at the punchline and at the strength of the language Clay used (if you ever met him, you know that he was an incredibly gentle and soft-spoken man, so using the phrase “go to Hell” was the equivalent of your parents unleashing a five-minute long expletive-laden rant).
“If you want data, go to Hell.”
Clay’s statement seems absolutely blasphemous, especially in a society that views quantitative data as the ultimate source of truth:
- “In God we trust. All others bring data.” W. Edward Deming, founding Father of Total Quality Management (TQM)
- “Above all else, show the data.” – Edward R. Tufte, a pioneer in the field of data visualization
- “What gets measured gets managed” – Peter Drucker, father of modern management studies
But it’s not entirely wrong.
Quantitative Data’s blessing: A sense of safety
As humans, we crave certainty and safety. This was true millennia ago when we needed to know whether the rustling in the leaves was the wind or a hungry predator preparing to leap and tear us limb from lime. And it’s true today when we must make billion-dollar decisions about buying companies, launching products, and expanding into new geographies.
We rely on data about company valuation and cash flow, market size and growth, and competitor size and strategy to make big decisions, trusting that it is accurate and will continue to be true for the foreseeable future.
Quantitative Data’s curse: The past does not predict the future
As leaders navigating an increasingly VUCA world, we know we must prepare for multiple scenarios, operate with agility, and be willing to pivot when change happens.
Yet we rely on data that describes the past.
We can extrapolate it, build forecasts, and create models, but the data will never tell us with certainty what will happen in the future. It can’t even tell us the Why (drivers, causal mechanisms) behind the What it describes.
The Answer: And not Or
Quantitative data Is useful. It gives us the sense of safety we need to operate in a world of uncertainty and a starting point from which to imagine the future(s).
But, it is not enough to give the clarity or confidence we need to make decisions leading to future growth and lasting competitive advantage.
To make those decisions, we need quantitative data AND qualitative insights.
We need numbers and humans.
Qualitative Insight’s blessing: A view into the future
Humans are the source of data. Our beliefs, motivations, aspirations, and actions are tracked and measured, and turned into numbers that describe what we believed, wanted, and did in the past.
By understanding human beliefs, motivations, and aspirations (and capturing them as qualitative insights), we gain insight into why we believed, wanted, and did those things and, as a result, how those beliefs, motivations, aspirations, and actions could change and be changed. With these insights, we can develop strategies and plans to change or maintain beliefs and motivations and anticipate and prepare for events that could accelerate or hinder our goals. And yes, these insights can be quantified.
Qualitative Insight’s curse: We must be brave
When discussing the merit of pursuing or applying qualitative research, it’s not uncommon for someone to trot out the saying (erroneously attributed to Henry Ford), “If I asked people what they wanted, they would have said a horse that goes twice as fast and eats half as much.”
Pushing against that assertion requires you to be brave. To let go of your desire for certainty and safety, take a risk, and be intellectually brave.
Being brave is hard. Staying safe is easy. It’s rational. It’s what any reasonable person would do. But safe, rational, and reasonable people rarely change the world.
One more story
In 1980, McKinsey predicted that the worldwide market for cell phones would max out at 900,000 subscribers. They based this prediction on solid data, analyzed by some of the most intelligent people in business. The data and resulting recommendations made sense when presented to AT&T, McKinsey’s client.
Five years later, there were 340,213 subscribers, and McKinsey looked pretty smart. In 1990, there were 5.3 million subscribers, almost 6x McKinsey’s prediction. In 1994, there were 24.1M subscribers in the US alone (27x McKinsey’s global forecast), and AT&T was forced to pay $12.6B to acquire McCaw Cellular.
Should AT&T have told McKinsey to “go to Hell?” No.
Should AT&T have thanked McKinsey for going to (and through) Hell to get the data, then asked whether they swung by earth to talk to humans and understand their Jobs to be Done around communication? Yes.
Because, as Box founder Aaron Levie reminds us,
“Sizing the market for a disruptor based on an incumbent’s market is like sizing a car industry off how many horses there were in 1910.”
* Except for the last line, these probably (definitely) weren’t his exact words, but they are an accurate representation of what I remember him saying