I have made many predictions in my life, publicly. And I have been wrong plenty of times. If you write boldly, you will be, too. People who are sometimes wrong are smarter than people who are always right. So learn how to be wrong properly.
If you’re one of those people who don’t ever want to be wrong, don’t say anything. Try not to put anything in writing. If you must write something, use weasel words to equivocate. Be ambidextrous as well as ambiguous — say “on the other hand” a lot. You are now a pusillanimous lump, curled up in fear. It’s not much of a life. And when the moment comes when you must take a stand — for yourself, or your children — you won’t know how to do it, because you will have no experience.
If you aspire to take a stand, you should learn to be a true analyst. And you are going to be wrong sometimes. Here’s how to do that properly.
Choose things that are difficult to predict
Here are some predictions: The Boston Celtics are not going to be be the NBA Champions this year. A new iPhone model will come out this fall. And more people will cut the cable cord than ever before. Unimpressive, I know. You already knew these things.
Your colleagues and readers have to make difficult decisions about things that aren’t known. Do the work to support those decisions and you’ve actually done something positive. You might be wrong, but that’s better than having no informed opinion at all.
Once you’ve chosen something worthwhile to predict, you’re on the spot. This should motivate you to do research. Start with what’s on the Web, but don’t stop there. Find data and analyze it in a new way. Interview people. Take the untrodden path. Unless you go where others have not gone, you won’t learn anything new.
If you start with a preconception, you can make a prediction quickly — and it will be worthless.
Let’s take an example. In 1995, right after I started at Forrester Research, Bill Bluestein and Mary Modahl asked me to predict the future business model for online content. I quickly determined that two answers were possible: online subscriptions or online advertising. Neither had much traction.
After a lot of research and interviews in the first few weeks, I told Bill “I think the main support of online content will be advertising.”
“So write a report about online advertising,” he said.
“I can’t do that,” I said. “I’m not sure it will be advertising.”
“OK,” he responded. “So write about subscriptions.”
“No, I don’t think it will be subscriptions,” I said.
“Well, you better pick one or the other.”
I then created the firmest possible argument for advertising based on evidence from research. And I did the same for subscriptions. The case for advertising was stronger, so that was my prediction. (And it was right for about a decade, and is still mostly right.)
There’s no point in equivocating as you predict. The penalty for being wimpy and wrong is exactly the same as the penalty for being bold and wrong. So speak up clearly.
Explain the case for. And explain the case against, and why you rejected it.
Finally, tell people what to watch for that will determine if your prediction is right.
Refine your prediction
Now you’re on record. So spend the next few months (or years) observing the consequences of your prediction.
If you’re lucky, you’re on target. Explain why you were right, and extend your prediction.
More likely, you were mostly right and partly wrong. Maybe something that you predicted is happening, but slower than you thought. Adjust your prediction, explain why you did.
When you’re wrong, explain why and change your prediction
Sometimes, you’re completely off. This usually happens because you missed a trend, or a disruptive influence changed things in a way you didn’t predict.
A true analyst does not slink away and hide in these situations. They explain what has happened and why.
For example, I predicted that HDTV would fail and SDTV (a lower-resolution digital TV standard) would succeed. My analysis was based on the stubbornly high price of high-resolution projection TV sets, the high cost to the whole TV industry (production, broadcast, cable) of switching technologies, and the marginal differences in viewing quality between SDTV and HDTV. Some people in the TV industry agreed with me at the time, but in the end, I was wrong.
The reason I was wrong was that I failed to see the emergence of plasma and LCD TVs and their rapid price drop. The consumer electronics industry invested many billions of dollars in plants to manufacture these TVs and then beat each other senseless (and profitless) with them. Those flat TV sets blew up everything that I had predicted.
I changed my predictions once these trends were clear. And nobody wrote me off as an analyst. They were more interested in my latest reasoning.
If you made your prediction based on a heartfelt belief rather than research, then being wrong isn’t likely to help you. You’re like those cult leaders who predict the end of the world and then keep adjusting their predictions when the world doesn’t end. The only thing you might learn is that your heartfelt belief is a lie, which, while devastating, doesn’t give you anything to build on.
If you made your prediction based on facts and reasoning, though, then being wrong is just more evidence. You can see where you made your error. You already carefully evaluated the other side of the argument, so you can pick up that reasoning. And as an analytical skeptic, you’re in the best position to predict where things will go next — absent the fervor of the zealot.
Smart people made plenty of mistakes along the way. Ironically, I think it’s better to trust someone who has been wrong from time to time than someone who is always right. The person who is always right has hubris and has made only easy predictions. They’ll be wrong eventually, and they won’t know what to do about it. The person who has been wrong from time to time has gotten a lot smarter in the process. That’s who you want on your team.