Malcolm Gladwell Under Fire: Marketers Miffed
Witnessing the firestorm that erupted as a result of a Fast Company article, I've concluded that the quickest way to earn the ire of marketers is to trash Malcolm Gladwell and his breakthrough hit book about influence, The Tipping Point. The article has gotten so much attention that Fast Company's servers have been unable to handle the traffic.* Download an image of the error message.
I've already been participating in this conversation through the comments of other's blogs (and you'll probably have more luck accessing them than the Fast Company website), but since so many people are talking about it, I'm having difficulty keeping up, and if the topic is interesting to you, I'll bet you are, too.
To help us all, I'm posting links to some of the most interesting articles I've read on the subject:
- David Reich: Has the Tipping Point tipped over?
- Scott Monty: Keep the Tip(ping Point)
- Stephen Denny: Tipping Points and the Psychology of Influence
- David Armano: Influence Ripples, Tipping Points + Toast
- Gavin Heaton: The Dream of Influence and Democracy of Action
- Guy Kawasaki: Forget the A-List After All
- Ben McConnell: Why it's best not to predict
- Seth Godin: The Hyping Point
- Valeria Maltoni: Forget Influentials: in Viral Marketing, Context Matters
I loved The Tipping Point and thought it was well written.
However, I recognized even while reading it that there was no possible way to conclude without any doubt whether Gladwell was right or wrong, based on the data that was being given.
Gladwell was convincing (as he usually is), and his conclusions "felt right," but he is susceptible to a particular type of non sequitur fallacy called post hoc ergo propter hoc, which is Latin for "After this, therefore because of this."
This is what it means:
In a given sequence of events, it cannot be concluded that the first thing caused the second (or some number thereafter).
So, in Gladwell's case, just because crime decreased after New York fixed the broken windows, it cannot be concluded that fixing the broken windows caused the decrease in crime. But it is an interesting theory.
At the same time, I'm not very impressed with Watt's computer models that led him to his conclusions, either. Computer models rely on someone to program certain uniform, finite rules to draw a conclusion about a reality where the rules of influence are more diverse and infinite.
To his credit, Watts completely realizes this limitation. From the Fast Company article:
"'My models might be totally wrong,' he says cheerfully. 'But at least I'm clear about what I'm saying. You can look at them, and tell me if you disagree. But none of these other thinkers are actually clear about what they're saying. You can't tell if they're wrong.'"
So what are we to think?
The conclusions each person draws lend themselves to tactical solutions, but perhaps the entire approach is wrong. Rather than deciding between mass marketing and targeting selected "influencers," just do what you love, and find other people who love (or can be convinced to love) the same things you do.
That way you don't have to worry about all of this, and Fast Company will get their servers back online. - Cam Beck
*I cannot conclude that the article in question caused Fast Company's server crash.