It's funny how a set of data can lead to two completely different conclusions in the space of fifteen minutes.
Let me explain. My mother had been suffering from a baffling joint ailment;
one that would flare up periodically, leading to swelling, pain and immobility. She was having trouble being heard by her doctor, so I went with her to get her test results and the diagnosis. Overflowing with arrogant confidence, the doctor explained
that my mother had no inflammation of any kind. Rather, her symptoms were most unquestionably the result of age-related osteoarthritis, where bone starts rubbing against bone as cartilage thins out.
Yes, there was one stray bit of data in the blood tests that was a little abnormal, but it was not a marker for any kind of rheumatoid arthritis. Given that the rest of the tests and x-rays for rheumatism were negative, he concluded that she most definitely did not have rheumatoid arthritis.
All that pain and suffering? A figment of her imagination. He told my mother to take some Tylenol and get over it.
Not so fast, Doc. Based on the symptoms I had witnessed when she was not taking anti-inflammatory meds, I challenged his diagnosis.
And, after nearly coming to blows with the doctor (what a condescending, patronizing, tone-deaf jerk!), I finally got him to really LISTEN
to my mother. And he changed his diagnosis completely.
Her real-life experience (now that he had bothered to find out what that was), in conjunction with that slightly anomalous blood reading (the one indicator of what she does have!), meant that she has something entirely other than osteoarthritis.
Living happily ever after with Tylenol wasn't going to cut it.
She has a new doctor now - surprise, surprise - and is doing fine.
I share all this (with my mother's permission) because there is an important investment - if not life - lesson in this incident:
The data were never in dispute. However, the correct interpretation of the data was dependent on having the proper context
. A context that is qualitative
and derived from asking a lot of good questions.
Without context, data is often misleading at best, and worthless at worst. Unfortunately, as an industry, we miss a lot of context. Shrinks, cops, interrogators, and journalists
are taught how to ask questions and how to parse answers. Professional investors, on the other hand, are not, and yet that may be the most important part of our job.
In my case, thanks to a genuine curiosity about what makes a company tick and how people think about their respective businesses, I naturally ask lots and lots of open-ended questions.
This both disarms people and allows me to ferret out crucial insights into their business.
For me, I need to know how the concrete (the everyday reality of how a business runs) translates into the abstract (massive financial models).
It's easy to model sales growing and margins doubling; gauging the probability
of doing so rests on a qualitative understanding of the business. And diagnosing that properly comes from asking the right questions, and being an active listener. Here, then, are some questions about questions to ponder whenever you seek to tease the truth out from under a pile of data:
- Do you know when to ask a closed-ended question, and when to ask an open-ended question?
- Can you tell when you've framed the question in a way that will only elicit the answer you want to hear?
- Do you know how to frame a question to maximize the chances of hearing something that you don't want to hear? (And have you considered what the investment-thesis-crushing answer in that situation would be?)
- Are you so focused on your preset list of questions, and your haste to cross them off, that you don't pursue an interesting line of inquiry?
- Do you know how to reframe a question based on the non-answer received to elicit a better answer?
- Can you tell the difference between something someone won't answer as opposed to something they can't answer? If they won't answer, why not? And if they can't answer, why not? (The latter is often where true insights are born.)
- When you hear an anomalous answer, does it provoke more questions, or do you shrug and move on, because it doesn't fit your tidy theory about the business?
- Do you take the time to hear the narrative of the company's history and management's background? (How a company behaves today is informed by its past, good or bad. How management looks at the world is similarly colored by their past experiences.)
Getting into a catfight with my mother's doctor was a great reminder that while data can be indisputable, the conclusions derived from such data are not
. So here's a prescription for better investment returns: Invest a lot of time
upfront in understanding the context from which that data was derived by asking great open-ended questions. Or, if you just want, take two Tylenol and call me in the morning.
That's fine; just don't expect a rapid recovery.