It looks like nothing was found at this location. Maybe try a search or browse one of our posts below.

I recently had the pleasure of reading Richard Dawkins’ River Out of Eden. I haven’t spent time with Dawkins since reading his influential The Selfish Gene two decades ago. In both books, Dawkins explores the ramifications of a DNA-centric view of natural selection. Begin with the premise that bodies are just DNA’s way of making more DNA, and the consequences are plentiful, fascinating — and very helpful in understanding how businesses operate, a subject we’ll explore in future columns.

Dawkins is, among other things, a modern Sir Thomas Huxley, who joyfully and convincingly demolishes the arguments of those who reject evolutionary theory. In Eden he takes particular pleasure in demolishing the intellectual sin of what he calls “Argument from Personal Incredulity” (API).

API begins with an accurate statement: “I don’t see how that could be possible.” The implication — that because you don’t see how it can work, it can’t work — replaces logic with a sizable dose of arrogance.

Arrogance? ‘Fraid so. If it’s evolution, API means your inability to figure it out outweighs lifetimes of hard work and deep thought by thousands of geniuses who have researched, modified, refined and extended Darwin’s work over more than a century. Ah, what did they know, anyway?

Natural selection is one thing. If you don’t feel like accepting this thoroughly researched scientific theory, that’s your privilege. The problem is, plenty of managers apply API to their day-to-day decision-making. How about you?

Business is as filled with interesting ideas as a Greek restaurant is with savory vittles. Should you augment financial statements with a balanced scorecard? Perhaps you should start calculating “Economic Value Added” (EVA). On a technical note, there’s the potential for use-case analysis to replace traditional methodologies.

You walk a fine line when you evaluate new ideas. Accept them all and you’re following the fad of the month. Reject them all and you invite stagnation.

It’s tempting to apply API, embracing what fits your biases while rejecting the rest as unworkable. Ever say, “It doesn’t work that way in this company,”? It’s API — you’ve decided it can’t work because you don’t personally understand how it can. Then there’s the popular, “It’s a great theory, but …” Ever wonder what would have happened if Franklin Delano Roosevelt had said that to Albert Einstein?

Okay, both API and automatic acceptance of the experts are wrong. What’s right?

The first step in resolving this dilemma is simply to match new ideas to your top priorities. At any given moment, a good leader will be sponsoring between one and three high-level goals — significant changes that will make a real difference to the company. Screen out as interesting but unimportant, or maybe file away for future use, all except those ideas that can help you achieve your current goals.

Next, assess how widely each idea has been tested.

This assessment shouldn’t drive your choice, just your method of evaluation. A new and untested idea, for example, may be just what you need. Analyze it closely, though. Great ideas live or die in the details, and in the absence of wide real-world use you’ll have to figure them out yourself.

Many of the most highly hyped ideas have been applied in only one, or maybe just a few, companies. In these cases it’s the glowing descriptions of success that call for scrutiny. Sometimes what looks like success on the surface is really a glowing story of how great everything is going to be someday. Or the success is real enough, but the great idea isn’t what caused it. Or you may be reading a history written by the survivors. Regardless, make sure you understand the circumstances of each success before you decide to replicate them yourself.

Then there are ideas that have been widely deployed and are generally accepted. Should you just accept them too and put them into practice?

Since this column challenges popular, widely accepted ideas on a regular basis, that clearly isn’t the right answer. But what is?

Tune in next week to find out.

Journalists and professional marketers know that if all the statistics in the universe were piled in a stack, the whole awesome mass of them would lack the persuasive punch of a single anecdote. Why? Because most people, for most issues, make decisions emotionally and use logic to justify their emotional decision.

Anecdotes appeal to the emotions. Statistics appeal to reason. It’s not a fair fight.

Think about your organizational rival in the next cubicle. He picked the help desk problem tracking system your organization uses, and it’s a disaster. And the clod chose it because the sales rep happened to be pretty, and he’s having marital problems. If he’d looked at the performance statistics, industry ratings, and other objective facts instead, he wouldn’t have made such a bad choice.

We all know of stories like this, and they prove my point, don’t they?

Actually, they don’t. I just used an anecdote to “prove” my point. I haven’t proven anything. If I’d said, “The Farfinkel Institute just released a study showing that 74% of all product decisions do not include a fact-gathering phase,” I’d have proved my point (or the Farfinkel Institute would have proven it). Of course, you’d have fallen asleep in the middle of my explanation.

Next time you listen to a political debate, keep your anecdote-detectors on full scan. No matter what the issue, you’re more likely to hear illustrative stories than statistical facts in our marketing-driven policy dialogs.

Yes, I know what Mark Twain said about lies, damned lies and statistics. Yes, people can contrive misleading statistics. That’s nothing compared to their ability to script tailored anecdotes. Think of it this way: an anecdote is just a statistic with a sample size of one. You can “prove” anything at all that way.

We fall for this stuff all the time. Want an example? How much time, energy, and budget have you expended on disaster recovery planning and virus protection? Compare that to the time, energy and budget you’ve spent researching hardware design problems and software bugs, in implementing preventive maintenance problems, and in instituting administrative quality assurance programs.

Pause to reflect on this question before continuing. Then consider the following two items:

Item #1: Ontrack Data Recovery (the gods of pulling data off of trashed hard drives) recently published a study attributing 44% of all problems to hardware problems, 32% to system administration mistakes, 14% to software bugs, and 7% to computer viruses, and 3% to natural disasters. (Reported by Investors Business Daily, 9/18/96, summarized in Edupage.)

Item #2: In a recent editorial, BugNet (www.bugnet.com), made a similar point, demonstrating that problems from software bugs are 100 times more prevalent than problems from viruses.

(Why the discrepancy between the two reports? Ontrack only counted episodes leading to data loss, while BugNet tallied all problems.)

Do these two items lead you to think your efforts may be misplaced? Good. Without a doubt, computer viruses have been overhyped as a threat. They’re characterized as digital AIDS or Ebola, when in fact, as with biological viruses, most cause minor, annoying symptoms – computer colds and flu.

(These statistics, of course, don’t reveal the overall seriousness of the different threats. Natural disasters, for example, may only contribute to 3% of all episodes of data loss, but I’d bet they contribute to more business failures than all of the others put together. That makes business recovery planning worthwhile regardless of its statistical rank. Statistics devised by other people often won’t serve your purposes, which was Mark Twain’s point.)

Don’t fall for manipulative opinion-shapers who use story-telling as a substitute for facts. On the other hand, when you’re trying to persuade, make sure you do illustrate your points with examples that add some punch to your dry statistics. You need to engage both halves of your audience’s brain. That’s a matter of clarity, not distortion.