A few years ago, my son graduated college and asked me to
back him financially so he could launch a business. What business? I asked. New type of tanning salon, said he. So, you got a business plan?
Whereupon my son looked at me like I’d just stepped off a
ship from the Old Country. “Dad,”
he explained carefully, “it’s not that complicated. I mean, you
launched a business, and you were
successful, right?” (Like, how
hard could it be?) He was
referring to Peppers
& Rogers Group, the management consulting firm which had by then grown
to employ more than 100 people. Martha
Rogers and I founded it after our first
I replied yes, but did he know how many other new businesses
I had actually started or tried to get funding for, at one time or
another? No? Six. “What happened to them?” he asked, trying to take this
in. I failed every time, that’s
what. A group legal services firm,
an all-first-class airline, a fax-based media company, a real estate investment
operation, a marketing consulting business…down in flames, each of them. But Martha’s and my business had succeeded,
and we’ve remained partners and co-authors ever since. Our ninth book together, Extreme Trust, is due out in a month,
and Peppers & Rogers Group now operates on five continents.
So what really separates success and failure in business? Everyone has a different explanation,
but in the end a great deal of life boils down simply to being in the right
place at the right time. Energy,
determination, intelligence, vision–all this helps, and of course the
more times you get up to bat the more chances you have to make a hit. In the end, however, things either come
together or they don’t, and in retrospect you can usually point to several
different junctures where your venture might have taken a completely different
Today, however, randomness and uncertainty play even greater
roles in determining business success, largely because of the increasing
importance of rapidly evolving social networks, and the inherent
unpredictability of social sentiment. Social influence cascades in random ways, often very rapidly. Predictions and forecasts are pretty
Researchers for The
Wall Street Journal once analyzed
25,000 user contributions at six large sharing-and-collaboration websites.
What they found in each network was that a very small number of participants
commanded extremely high levels of influence. Of Netscape’s million-plus users
at the time, for instance, 13 percent of the postings rated “most popular” came
from a single one. And of the 900,000 users of Digg, a third of the
contributions rated highly enough to make it to the home page came from just
30. The newspaper’s researchers then decided to track down one of Reddit’s most
widely read users, a blogger named Adam Fuhrer, in order to figure out why his
opinions on software and legal issues had been so widely praised by other
users. What they found was that Adam was 12 years old, and lived with his
parents in Toronto.
Now doubtless Adam was a very smart young man, but out of
400,000 Reddit users, there had to be hundreds even smarter than this
12-year-old. What probably
happened was that one or two posts Adam wrote early on were rated high by
another Reddit user, and because this user had high ratings himself, other Reddit
members read Adam’s post and rated it high, and so forth. Adam’s reputation cascaded because of
this positive feedback loop.
But here’s the thing: If we wanted to predict the next Adam
Fuhrer–that’s a completely impossible task. It would be like trying to predict what
time it will start raining in downtown Dubuque on May 12, 2029. Predicting the future behavior of networks
and other complex systems generating things like the weather and social
sentiment is what scientists call an uncomputable problem, and they don’t
just mean that we lack the computing power to do it with our current technology;
they mean there isn’t enough computing power in the universe to solve the
But knowing that technological progress, networks, and
complex systems are making the business world less and less predictable is a
prediction itself, right? You can
actually plan on it. So here are
six strategies that can help your business deal with increasing levels of
analytic techniques that don’t require high accuracy.
Simple statistical models are often more reliable for
dealing with highly complex situations than more detailed models. This is
especially good advice for marketers, who may be used to seeing awareness and
preference data with two or more decimal places. The problem in dealing with
social networks and other complex systems is that a sophisticated model is more
likely to fit past data well but fail to predict the future, while a more basic
model is less likely to fit past data, but more
likely to be able to anticipate different future scenarios. Multi-variant
trade-off analysis may predict demand for your product quite accurately, but
then over one weekend the mommy
bloggers suddenly take offense…
for multiple outcomes.
Rather than trying to make the one right guess as to what
will most likely happen, make multiple guesses. Place many small
bets on a variety of options. This is the way any truly innovative process works, and
innovation is a good analogy for prediction. Don’t bet the farm on the Edsel,
in other words, without also having a Mustang or Thunderbird in your portfolio.
and rely on the predictable elements of the situation.
You may not be able to predict who the next Adam Fuhrer will
be for any particular social network, but you know there will
be a few participants with extremely high influence, and there will be cascades of sentiment, sometimes sudden. Just because you don’t know which
particular day it’s going to rain doesn’t mean you should sell the umbrella.
your evaluation of initiatives on the inputs, not just the outputs.
Randomness will confound even the best efforts to produce
results, so when assessing an initiative’s success, consider the quality of the
decision to undertake it. Don’t rely solely on the actual outcome of the
project (bad or good), but take into
account the quality of the process that
went into its planning and execution. A bad leader can sometimes get elected
despite the evidence, but as long as the election was fair, you shouldn’t throw
out the democratic process.
agile, and strive to respond quickly.
There’s no substitute for awareness, listening, and detecting
events as soon as they happen. Focus on “sense and respond” as an organization,
and empower your people to act quickly and decisively. Have a social media policy strong on principle but general enough to be flexible,
remembering that actual results can vary. And stage a social-media fire drill
every so often.
your reputation for extreme
In the end, you have to prepare for failure, success, and
everything in between. But as long as others find you
trustable, you’ll never be on your own. Focus on doing
the right thing, and your customers, employees, and other stakeholders
will all have an interest in seeing your company weather whatever unpredictable
storm might come your way.
By the way, my son now has a promising sales career with Interactive
Brokers–a well-deserved success he earned entirely on his own. (He’s afflicted with the
entrepreneurial bug, though, and sooner or later I’m thinking he’ll probably have
to run with it, as I had to.)
[Image: Flickr user dave.scriven]