Signal to noise

Why doesn’t early warning work?  While it’s a good idea in theory, in practice it seldom seems to have its intended effect.  In every major intelligence failure I’ve looked at, there were clear, credible early signals — and even explicit warnings—that tragically remained unheeded.  Why is this, and what can we do about it?

For example, in the recent meltdown of the US real estate market, and much of the world economy with it, there were lots of warning signs.  Some of these were very explicit and very public.  To name a couple:

  • The FBI’s 2006 published report warning of widespread fraud in the US residential mortgage market, which backed the mortgage-back securities market that subsequently collapsed
  • Yale economist Robert Shiller’s testimony before Congress in September 2007 that housing prices were dangerously overinflated, and that their imminent collapse would cause significant damage to the economy.
World Trade Center - September 11, 2001 9:45am

Downtown New York City - September 11, 2001 9:45am

In another example, leading up to the bombing of the World Trade Center towers in New York City in 2001, there were many events that could have been read as “feasibility tests” for 9/11.  There is a chapter (“Foresight — and Hindsight”) in the 9/11 Commission Report that catalogs the missed signals and other structural conditions that might have prevented the attack.  In retrospect, there seems to have been a straight-line connection between:

  • The February 1993 truck bombing of the WTC North Tower
  • The August 1998 bombings of the US embassies in Nairobi, Kenya and Tanzania
  • The October 2000 bombing of the USS Cole.

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Tick or trend?

It’s not the latest Halloween ritual (sorry, couldn’t resist), but rather the basic choice every investor, corporate executive, analyst must make in forecasting what’s most likely to come next.

If you had been paying attention in March, you could have made 48.2% since then on your investment in the DJIA index.  If you did, congratulations—but don’t spend the money just yet.

With some of the world’s major stock markets up by over 50% in six months, it’s clear some kind of serious rally is under way.  But is it a trend—a genuine rally that signals a bottom, and an end to this long recession?  Or is it just a tick—a “sucker’s rally” that gives everyone false hopes before plunging us to even greater depths?

So far, in some respects the stock market is behaving like it did during 1929-30.  In the figure below, you see where we are now compared to where “we” were in 1930.  (The numbers are accurate, however the timelines are not drawn to scale.)  Then, as now, we lost about 50%, then in short order gained about 50%.  (Note to poets:  This does NOT put us back to where we were, but rather at 75% of that.)

1930a (Small)

Now some are forecasting that the next bull market is already under way, and that DJIA will double from here, putting it well over 25,000.  That the recovery, in other words, will be V-shaped, as shown by the dotted gray line.

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The two kinds of information

When asked to name his favorite kind of music, pioneering jazz musician Louis Armstrong is said to have replied, ”There are only two kinds of music, good and bad.  I like good music.”

You could say the same about information—there are fundamentally only two kinds, good and bad.

According to one definition (“Intelligence:  An Economic Good” by Mark Jensen), good information is defined as being timely, objective, usable, accurate, and relevant to whatever decision it is supporting.   It’s not the same as “good news”—good information can be favorable or unfavorable—but solely by virtue of its being “good”, it’s essential to decision-making.

To the extent information doesn’t adhere to most or all of the above criteria, it is “bad” information.  The problem is, it’s often hard to tell the difference between the bad and the good.

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The value contract

Still more ideas from the SCIP annual conference in Chicago…

When I work with internal corporate practitioners of intelligence or research, one of my first recommendations is to run their operation as if it were a stand-alone business.  That is, with clients (managerial decision-makers), suppliers (databases, contractors, etc.), and possibly even rivals of their own-both internal and external.  This helps them determine where the value for their clients is, and how to maximize that value.

Few of the internal practitioners I’ve met charge back for their services—so they are essentially “free” to their users on a transactional basis.  In those rare cases where there is a charge-back system, there is a market value assigned to the function.  People either pay for the service at the quoted price, or they do not.  The user is the judge of what value is received, and whether it was “worth it”.

However, absent this market mechanism—which has its own drawbacks—there is no direct measure of value for intelligence.  There must be some proxy for it—typically informal conversations or a survey at budget time to the effect—Is this function worth its salt, or not?

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Intelligence takes a holiday

Last week I went on vacation with my “lifemate” Ellen and the rest of my immediate family.  We were on Cape Cod, MA, which is a pretty sophisticated area as far as vacation spots go, so I had assumed that there would be good Internet connections.

Wrong.  No Wi-Fi signals, only one bar (at best) of cell phone, and my cell-powered wireless WAN working only briefly on one very stormy morning.  (Thanks, Verizon!)

I started thinking maybe Ellen planned it this way.  Instead of reading various chat boards, calling people, and posting to my blog, I actually talked to my family and read some of those heavy paper things—oh right, books.

Ellen claims that “vacation” means not only do you vacate your usual PLACE, you also vacate your MIND—and that you can’t do that while constantly being on the phone and the Internet.  So I think she secretly engineered this—to save my sanity.  It’s scary to go “off the grid” for even several hours, let alone several days as I did.  There are stages:  first you panic, then you get angry…but then you start to care less and less, and so on.  Eventually, you settle into a deeper zen-like level based more on the sunsets and the tide patterns than on the latest news morsel.  I wouldn’t want to live there, but it sure is a nice place to visit.

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Customized vs. syndicated intelligence

More ideas from the SCIP09 conference in Chicago…

I’ve worked a lot during my career with business-to-business publishing and information services clients—and consider myself in that business as well.  There are basically two business models for this kind of information—customized and syndicated.

Customized information is that which is developed—often at great effort and expense—and which is highly tailored to the needs of a very small audience or number of “users”.  A consultant’s report is a good example.

Syndicated information is that which is developed—again often at great effort and expense—but that is intended to meet the needs of a much wider audience.  A magazine or a mass-appeal web site are good examples. Read the rest of this entry »

TOR vs. TIVE

Ideas from the SCIP09 Conference in Chicago…

When I was in business school, my dean (William Donaldson—who earlier in his career had founded the brokerage firm Donaldson, Lufkin, and Jenrette) had several homespun sayings that would guide those of us who knew him.  One of these was “You have two ears and one mouth—you can’t use them both at the same time, and you’d be wise to use them in that proportion.”

Listen more, talk less—what a concept!  When you get to be an “expert” in something, it’s too easy to talk without listening, thereby limiting your flow of new information to your own direct experiences.

Last week I attended the annual conference of the Society of Competitive Intelligence Professionals in Chicago.  I had given lectures and workshops for many of their recent conferences, but this time my role was different.  This time, instead of being the “expert”, my job was to moderate and guide a discussion (“Active Dialog”) of the intelligence practitioners in the room.

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Tragedy and statistics

“The death of one company is a tragedy; the death of one million is a statistic.”

Originally said of catastrophic human events, so it is too with “The Economy”.  It’s too easy to get lost in the quantified abstractions of the aggregate, and thereby lose focus on the realities that drive individual business enterprises.

If “The Economy” exists in any sense as an economic reality that can be acted on, it’s only in centrally-planned top-down economies.  On the other hand, in a free-market, unplanned economy, “the economy” is the sum of the activity of individual firms.  Firms in turn are the sum of individual businesses or products.  Product markets are aggregations of individual customers.  Customers are aggregations of individual transactions.  Up to that point, it’s like fractal geometry—there’s always another level deeper you can go.

So while it’s sometimes a useful shorthand to say the economy is expanding, contracting, or WHATEVER—it’s really a gross oversimplification.  As such it blurs the actual reality, and causes unintended consequences—for example, lulling us into a sense that all is hopeless until “the economy comes back.”   It’s almost as if we ascribe supernatural powers to this abstraction.

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The tough get going

Now the tough get going.  The economy will come back—not because it decides to come back, but because we together make it come back.  How long this will take to happen, no one can say for sure.

This much is clear:  silly season is over.  Things like having not one, but two places on your block that serve expensive coffee that takes a long time to make, are over.  Things like getting funding for business models that are “cool”, but that have no hope of ever making money, are over.

Value creation doesn’t stop in a recessionary economy like this one—but it does change, sometimes dramatically and very fast.  Value can migrate from one economic sector another.  This is because each “value chain” interacts, and displacements in one—like you lost your job—cause displacements in another—like cutting out the overpriced coffee. Read the rest of this entry »