“There are three kinds of lies: lies, damned lies, and statistics,” Mark Twain famously said.
Everything we read, hear and see bombards us with random data and statistics.
Authors draw conclusions from loose correlations and neatly package the data for consumption.
In other words, opinions masquerading as facts. This is a problem.
No one is blameless in this.
As humans we all take small samples of data and extrapolate them to conform with, or confirm, our own world view. As a result, that view is often at odds with reality.
The late Hans Rosling, in his excellent book, “Factfulness: Ten Reasons We’re Wrong About the World – and Why Things Are Better Than You Think,” provided multiple examples of this phenomenon.
Even a Nobel Prize winner like Daniel Kahneman is not immune to this. To his credit, he publicly admitted drawing conclusions about the power of “priming” by relying on “underpowered studies”.
We increasingly see this unwarranted certitude about data collected and reported about sales.
For instance, published articles purport to tell us the magic words to use at the right moments in sales conversations. (The conclusions presented are drawn from analyzing tens of thousands of recorded calls.)
The problem is the variables aren’t controlled.
For example, if these articles said the analyzed calls were all made by a defined population of sellers to a defined population of buyers (let’s say sellers employed by SaaS companies with fewer than 20 sales reps and less than $15 million in revenue calling on buyers in companies with more than $100 million in annual revenues) then the conclusions about word choice would be valuable to sellers that fit the above profile.
However, if the data was drawn from studying a large pool of calls made by sellers from companies of all sizes, selling a range of disparate products (software, services, hardware), then any conclusions reached would basically be averages.
Therefore, they would be of limited value to sellers that matched the above profile. And, of limited value to sellers in general.
I’m not a data expert. I’m just trying to make myself smarter about data and how we use it to radically improve individual sales productivity.
We need good data to use as intelligence to make this happen. However, we cannot continue to be sloppy about the judgments we draw from it.
I encourage you to start educating yourself about data. Start by reading this excellent book from John H Johnson “Everydata: The Misinformation Hidden in the Little Data You Consume Every Day.”
It’s a great introduction to becoming a more sophisticated consumer of data. It shows how to spot the holes in the data that we use to make decisions in our business and personal lives.
What books have you read that have helped make you smarter about data?
Lastly, a little wisdom from Isaac Newton: “A man may imagine things that are false, but he can only understand things that are true, for if the things be false, the apprehension of them is not understanding.”
– Andy Paul