Monthly Archives: March 2005

Dirty Money

I recall my father’s bemused comment on dirty money: “We can clean it!”

I have a friend who won’t use a very useful piece of open source software because he feels it’s author is a pompous jerk with a short fuse.  You can clean money, it is much harder to clean your reputation.  Relationships relationships, complex transactions, can not be reduced to simple market commerce.

Today’s debacle around WordPress (they were running a link farm on the reputation credit created by all the WordPress blogs “thank you links”), bleck. I use WordPress here and in a few other venues. I’ve made some very minor contributions. So yea!  I’m in that core of the community, if you define that as the top 5 thousand people in the community :-).  Today’s mess ripples thru the entire complex relationship network that holds a community like this together, and it is more likely to shake off people at the periphery than those closer to the core.

For example one of the things that the WordPress community does is Pingomatic.com. One of the hubs in the ping market. Trust?

Ugo does a good job of covering many of the bases of my opinion about this. He ends with this…

Since Matt is almost exactly half my age, I don’t want to be too harsh. Who’s not done something terribly stupid in his youth? I’m sure he’ll regret this and reform his ways. Unfortunately for him, the web, and Google in particular, have very good memory, so this episode won’t be forgotten so easily.

Open source projects are very long games with many many rounds and very ambiguous end states. If a player doesn’t play nice it taints his reputation for a long time. In the end sooner or later every participant in these games makes a fool of him self. In all robust collaborative games forgiveness is an extremely necessary and critical move.

 

 

 

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>   <li><a rel="nofollow" href="http://wordpress.org/" title="Thanks! WordPress">WordPress</a>,

 

 

 

 

 

Where the eye falls

Via Gideon Rosenblatt a cool visual of where user’s eyes fall over google search results. This also answers a question I had. On a pull down menu the sweet spot is the second, not the first, item on the list. I’d wondered if that might be the case on a google search listing. This suggests not; though eye and click aren’t necessarily the same.

Intergenerational Income Patterns

One of the ways to get a El Curve is to take a population and iteratively reward the winners slightly in each round. This appears to be the model that gives rise to power law distributions in things like oil reserves. So I’m always interested in research that looks at the details of the iterative process in the vicinity of a system that exhibits an El Curve. Income for example.

From Brad DeLong

Very nicely done: very much worth reading:

Sam Bowles and Herb Gintis (2002), “The Inheritance of Inequality,” Journal of Economic Perspectives.

That really is a marvelous paper beautifully and carefully written. Fascinating.

I did not know that back in the 1960s there was a consensus that the data showed America to be the land of opportunity, i.e. that your parents’ caste did not tend to dictate your own. I gather from this paper that this was wrong due to an assortment of errors in the design of the studies.

Today we know that if you’re born poor your chance of rising is small; the poverty trap. if you’re born rich your chance of dying poor is small. The authors think it’s unlikely that this second syndrome will come to be called the affluence trap.

Under some definitions of fair the maximally fair society would give each child an equal chance at various levels of income. In American society if your parents had high incomes chances are your income will be high. A child born of parents in the top 10% has a 40% chance of ending up in the top 20%. If your parents were dirt poor then it’s very unlikely you will have a high income. Children born into the bottom tenth have a 3.7% chance of getting into the top 20%.

The paper includes this great peice of eye candy. This shows the chance a child will fall into a given 10% of the income range given his parents’ position in that range. The two peaks are the poverty/affluence traps.

The fun thing about the paper is the very careful attempt they make to tease out of the data some information about the causality of the intergenerational income status trap. The extent of the trap is really amazing. If you average income over 15 years then the correlation is .65. That means there is a 65% chance that the next generation’s income will be within 1 standard deviation of the previous ones.

Of course what one wants to know is what’s the causal chain from one generation to another. For example maybe the key driver of wealth is a sense of humor (though i doubt it) and parents tend to pass that on to their children a bit by nature and a bit by nurture. The nice thing about the paper is that they make a really substantial effort to draw out of the data as much causality as possible. This is almost impossible since there are plenty of causal chains for which the data is very very thin.

Of course all this stuff is very tangled. Wealthy parents tend to buy more schooling, for example. The trick is to condition the results so you’re getting a reasonably pure contribution from each stage. I.e. so if you doubled the schooling without changing the parent’s wealth your model would predict accurately what the change in outcome would be. That’s really hard. For example it’s common to use data about twins or brothers to try and tease out the differences between nature and nurture. But even that’s very subtle. For example we know the height is very tightly tied to genetics but we also know it varies tremendously depending on how well people are eating. We know that brothers tend to have very similar incomes, unless you partition the data by race at which point you discover that black brothers are extremely highly correlated and non-blacks much less so. They do a beautiful job of stepping thru this mine field.

Here are the numbers they manage to pull out of the data:

  • 4% IQ
  • 7% Schooling
  • 12% Wealth
  • 2% Personality
  • 7% Race

The key result of the paper is that 32% of the trap remains unexplained. It’s something else. Humor say.

I still have an affection for my five ways to get rich model (pick the rich parents, spouse, pocket, card, or trade).

Friction and the new dark ages

This article from the WSJ is interesting, it’s about using systems like pubsub to create persistent search as part of trying to get as far in front of the rumor mill around your investments as possible.

“It’s like a giant electronic driftnet,” …
Such technology may have been at work recently, when the results of a government study of a cancer drug developed by Genentech was mistakenly posted on the Web site of the National Institutes of Health. An hour after the results went live, the stock had soared nearly 20%. David Miller, president of Biotech Stock Research, based in Seattle, said a few investors using the new technology may have seen the change on the NIH site, which put the release on its RSS feed about five minutes after it appeared on its news page — and acted on it.

I really like that driftnet metaphor. Very synergistic with my talent scrapping metaphor; or that some business models are like whales.

Fun to puzzle how about how  friction is always part of the market/business design. As King Content continues to be dethroned by the distribution channels the net present value of content falls. Like money in a depression it’s interest rate is going negative. When the interest rate goes negative the incentives get pretty strong to pull the money out from under the mattress and convert it into some other capital good. Presumably that’s what’s happening to content.

So maybe I’m wrong.

I’ve been assuming that open content and owned content are in a death match. That open content will win. That the displaced culture around owned content will go dark. I call this the new dark ages – that all the content copyrighted during the 20th century will just go dark. Locked up in the vaults of the mega-content owners.

But, just maybe, like those who horde capital in a recession the content owners can be convinced to pull it out of the vault. No wonder these guys are doing everything they can to increase the friction in the information distribution networks!

El Curve

I’m thinking that it might be more useful to use the term El Curve rather than Long Tail when we talk about the things with a power-law like distribution. Long tail is a useful term when our focus is reaching out into the long tail; but it frames the discussion in a manner that ignores the role of the vertical portion of the distribution in the architecture of the systems we build.

I’m reading the cheerful provocative book “The Fortune at the Bottom of the Pyramid,” which is about this very question. How can we architect business models that span from the vertical edge down into the horizontal edge to create economic growth thru-out. The book is targeted at the leaders of multi-national corporations. It wants to sell them on the idea that selling into the long tail of the world’s poor is a great business.

Without question the most politically charged power-law curves are the distributions income/wealth curves. The data is sobering. If I pluck the data out of the book’s pyramid drawing and split the world population into two camps about .1 Billion (1.7%) make more that $50 dollars a day and 5.5 Billion make less. It’s easy to become hysterical.

This book declines to partake of that temptation; his audience doesn’t respond well to that. Instead it’s a set of case studies in classic B school style along with the grand rules of thumb required of such books.

The business models all involve elements all along the power-law curve. A distribution channel if you like, though he calls it a process design. Value generating activities along the curve are orchestrated by the firm that designs, builds, and owns a economic network implicit in the business models. This is analagous to the way a fanchise resturant chain architects a value chain that reachs from the individual store up and into centralized production and marketing facilities. Like all economically stable systems some customer problem is resolved and value is captured in exchange for solving the problem. The captured value is spread along the various stages along the power-law curve.

This book is facinating if your interested in business models that reach into the long tail. In spite of it’s overwrot enthusiastic MBA tone, I’m enjoying it.

Google News Frequencies


This chart shows the data from here as of around 3pm 3/28/05 EST plotted on a linear scale and a log-log scale. Each dot shows how many times a particular media source was selected by the news AI at Google for inclusion on their news summary page. The data doesn’t cover a very long period of time so as you get out on the long tail of sources it gets grainy.

There are 1123 sources in the list. The top 64 sources account for just under 50% of stories posted. To say that another way the elite top 5% of the news outlets generated half the stories the AI selected. The elite 1% of the sources account for 20% of the stories. The #1 source provided 4% of the stories.

Two Washington newspapers are in that top 1%. The Moonie owned and operated Washington Times out scores the Washington Post. Silly AI.

Infectious Greed

This blog is totally on a roll!

For example this wonderful example of how one metric could lead you to entirely the wrong conclusions.

What, if anything, can be drawn from any of this? Not to put too fine a point on it, but people are scandal-mongers in private and they are helpful prudes in public.

Of course this morning my questions is: while a snarky blog about silly patterns in the world of business is certainly able to attract an audience can Google’s ad placement AI find a group of advertisers that actually garner click thru? I’ll admit I was slightly tempted to click on the link offering to let me start my own hedge fund.

Advertising Channels

I was raised by wolfs, well academics actually, and so it was only very late in life I learned that all stories are required to have three legs: problem, hero, and movement toward resolution. The power of this rule is demonstrated by how far some authors will stretch to fit.  An example is a piece in the current New Yorker.  Where the heroine is an advertising professional, and her problem is the end of the Golden age of advertising.

To hear tell in the golden age of advertising little shoppes of advertising artisans lined the streets of Manhattan.  As the curtain rises, desperate mouthwash manufacturing mogels would travel to this village and step into one of these shops.  He would, of course, be carrying a few million dollars.  In the second act the shop owner would craft a campaign and place it on the three television networks. In the third act the American public would tune and discover they had an unfulfilled desire to gargle more. As the curtain goes down they are all placing bottles of mouthwash into their shopping carts at the A&P.

This golden age amuses me. On the one hand you have numerous little firms and on the hand you have three huge television networks. It’s the canonical industry structure. On the one hand you have a highly consolidated distribution channel and on the other hand you have a long tail of tiny producers. In the nostalgic telling this is a beautiful thing. The small firms were wonderful because it they gave free reign (free-range?) to the heroic creative folk. The big networks were wonderful because they had aggregated the audience in a so convenient a package that it took one dance number late in the second act to deploy your campaign.  During this scene money would rain down upon the stage.

To hear tell the golden age has ended.  The advertising industry has condensed.  The entertainment industry is more of a slush.

The article fails, in the end, to fit the required story template.  The article is reduced to an enumeration of the various species emerging in the genus advertising.  Not that, a kind of butterfly collecting, is something the child of academics can appreciate.

Here’s an interesting butterfly: 20 seconds of in-show product placement costs about the same amount as a 30 second ad.  I would have assumed it costs more.  About 40% more is spent on internet advertising than on product placement, but both are growing fast.  Here’s another butterfly: Some newspapers are custom printed at the granularity of the postal code.

Distribution channels fascinate me. Part of my fascination is the way they are fundamentally two faced; the distribution firm must balance between two strong forces. So an entertainment/advertising channel is trying to find a balance between the desires of it’s advertisers and the desires of it’s audience. Actually it’s got three faces, which is even more fun, but let’s gloss over that today.  This tension is the ecology within which these butterflies evolve.

Bewitched, the old sitcom about an ad executive living in the suburbs married to a witch, must be the perfect example of what emerges from an environment with such forces. It’s a show about the customer on both sides of the advertiser/audience channel!  And, it is also the perfect venue for product placement.

The channels in the advertising universe  – defined by the advertisers and audience it attracts – must strike a balance.  Here’s another butterfly: the article tells a story of a TV show in which one of the characters takes a job pitching a product at the local mall, his pitch is identical to the ads spots broadcast with the show.

Billions and billions of ad channels are emerging. Google’s adsense is an example of that. That creates a bloom of new species of advertising channels. Some venues try to maximize how much they serve the advertiser, some try to maximize how much they serve the audience. Some venues don’t even choose to play in this game. The nostalgia for the golden age of advertising is the usual nostalgia for a time when the rules were well understood. The networks defined the audience and the manufactures and advertisers created products and campaigns to fit. Diversity is so confusing.