Necessary But Not Sufficient

Wednesday, March 4th, 2009

I finally made the time to read Goldratt’s last business novel, Necessary But Not Sufficient, which argues that new information technology is necessary but not sufficient for reaching the goal of making more money, because extra information doesn’t do you any good if you don’t do anything differently because of it.

The thin story of the novel involves an ERP software company with a major client who’s blindsided by a “weasel” on the board — a weasel who has the temerity to demand some justification for all the money spent on this enormous IT project. How does it improve the bottom line?

That’s when the ERP software company realizes that it has no case. “Better visibility into operations” doesn’t translate nicely into a dollar figure. Quicker turnaround on quarterly financial reports is also nice, but it — ironically? — doesn’t translate nicely into a dollar figure either, especially when no one from the finance department gets laid off. In fact, most time-saving improvements don’t translate into dollar savings, because, again, no one’s actually getting laid off; labor costs aren’t going down.

The real, quantifiable payoffs come from improvements in the supply chain. When the plants know how much has been sold from each distribution center three weeks sooner than they used to, that means they can carry less inventory and suffer fewer stock-outs, reducing their carrying costs and increasing their sales.

The system also reduces invoicing errors, which means they can get their money from customers sooner, and it allows them to combine purchases made by multiple plants, which means they can get better deals on raw materials.

(Incidentally, these benefits mean much less for medium-size firms with just a few plants and distribution centers, which aren’t so spread out.)

In the end, our heroes revolutionize the entire ERP software industry with their simpler, more effective solution, based on drum-buffer-rope and buffer management — which are not explained at all in the book, but which, in this fictional scenario, boost capacity by 40 percent.

But this boon has its own downside: suddenly the regional warehouses are overstuffed with finished goods. What happened?

The target inventory levels didn’t change — they stayed at four months’ inventory — but with the plant’s increased capacity, it can now fulfill requests in a timely manner, and actual inventory levels have climbed from an average of two months’ inventory to three.

With replenishment times cut in half, they cut target inventory levels in half, but this leads to shortages, because demand is still volatile, and one plant can go through two months’ inventory in one product pretty easily, even if it has plenty of inventory in other products, and other plants have plenty of inventory of that one product.

In the end, the solution is to pool inventory at a warehouse near the plant and to replenish the regional warehouses overnight from there, using pull inventory — sending them as much of a product as they’ve just sold.

Then the client realizes he can take this one step further and integrate his whole supply chain, not just the vertically integrated portion he owns — and that means our heroes can sell their ERP solution to medium-size and small firms who need to integrate with big firms. Everyone loves a happy ending.

Amazon’s Kindle for iPhone hits the App Store

Wednesday, March 4th, 2009

Amazon’s Kindle for iPhone (iTunes) hits the App Store, and it uses Whispersync to synchronize your location between readers.

The Netbook Effect

Monday, March 2nd, 2009

The OLPC project inadvertently spawned the netbook effect, yet another example of Clayton Christensen’s Innovator’s Dilemma:

Inspired (or perhaps a bit scared) by the OLPC project, Asustek — Quanta’s archrival in Taiwan and the world’s seventh-largest notebook maker — began crafting its own inexpensive, low-performance computer. It, too, would be built cheaply using Linux, flash memory, and a tiny 7-inch screen. It had no DVD drive and wasn’t potent enough to run programs like Photoshop. Indeed, Asustek intended it mainly just for checking email and surfing the Web. Their customers, they figured, would be children, seniors, and the emerging middle class in India or China who can’t afford a full $1,000 laptop.

What happened was something entirely different. When Asustek launched the Eee PC in fall 2007, it sold out the entire 350,000-unit inventory in a few months. Eee PCs weren’t bought by people in poor countries but by middle-class consumers in western Europe and the US, people who wanted a second laptop to carry in a handbag for peeking at YouTube or Facebook wherever they were. Soon the major PC brands — Dell, HP, Lenovo — were scrambling to catch up; by fall 2008, nearly every US computermaker had rushed a teensy $400 netbook to market.

All of which is, when you think about it, incredibly weird. Netbooks violate all the laws of the computer hardware business. Traditionally, development trickles down from the high end to the mass market. PC makers target early adopters with new, ultrapowerful features. Years later, those innovations spread to lower-end models.

But Jepsen’s design trickled up. In the process of creating a laptop to satisfy the needs of poor people, she revealed something about traditional PC users. They didn’t want more out of a laptop — they wanted less.

Can You Buy a Silicon Valley? Maybe.

Saturday, February 28th, 2009

Can you buy a Silicon Valley? Maybe, says Paul Graham:

A lot of cities look at Silicon Valley and ask “How could we make something like that happen here?” The organic way to do it is to establish a first-rate university in a place where rich people want to live. That’s how Silicon Valley happened. But could you shortcut the process by funding startups?
[...]
People sometimes think they could improve the startup scene in their town by starting something like Y Combinator there, but in fact it will have near zero effect. I know because Y Combinator itself had near zero effect on Boston when we were based there half the year. The people we funded came from all over the country (indeed, the world) and afterward they went wherever they could get more funding — which generally meant Silicon Valley.

The seed funding business is not a regional business, because at that stage startups are mobile. They’re just a couple founders with laptops.

If you want to encourage startups in a particular city, you have to fund startups that won’t leave. There are two ways to do that: have rules preventing them from leaving, or fund them at the point in their life when they naturally take root. The first approach is a mistake, because it becomes a filter for selecting bad startups. If your terms force startups to do things they don’t want to, only the desperate ones will take your money.

Good startups will move to another city as a condition of funding. What they won’t do is agree not to move the next time they need funding. So the only way to get them to stay is to give them enough that they never need to leave.
[...]
Suppose to be on the safe side it would cost a million dollars per startup. If you could get startups to stick to your town for a million apiece, then for a billion dollars you could bring in a 1000 startups. That probably wouldn’t push you past Silicon Valley itself, but it might get you second place.

For the price of a football stadium, any town that was decent to live in could make itself one of the biggest startup hubs in the world.

What’s more, it wouldn’t take very long. You could probably do it in five years. During the term of one mayor. And it would get easier over time, because the more startups you had in town, the less it would take to get new ones to move there. By the time you had a thousand startups in town, the VCs wouldn’t be trying so hard to get them to move to Silicon Valley; instead they’d be opening local offices. Then you’d really be in good shape. You’d have started a self-sustaining chain reaction like the one that drives the Valley.

$100 Linux wall-wart launches

Thursday, February 26th, 2009

Marvell’s SheevaPlug $100 Linux wall-wart launches:

Marvell Semiconductor is shipping a hardware/software development kit suitable for always-on home automation devices and service gateways. Resembling a “wall-wart” power adapter, the SheevaPlug draws 5 Watts, comes with Linux, and boasts completely open hardware and software designs, Marvell says.

In typical use, the SheevaPlug draws about as much power as a night-light. Yet, with 512MB each of RAM and Flash, and a 1.2GHz CPU, the unobtrusive device approaches the computing power found in the servers of only a decade ago.

Kindling a Revolution

Thursday, February 26th, 2009

Wade Roush of Xconomy interviews E Ink’s Russ Wilcox on e-paper, Amazon, and the future of publishing — starting with some history:

In 2004 Sony launched in Japan with the Librié. And it didn’t really work very well in Japan. Critics loved the hardware, but there were only 1,000 books available, and that does not make a successful publishing market. And it turns out that e-books are a tough sell in Japan because there is a thriving used bookstore market. People don’t have bookshelf space in their homes to store a lifetime of books, so they have this well-developed practice of returning books to used bookstores, so you can get any used book you want for a dollar. At the same time, people were getting used to standing on trains and reading on their little cell-phone displays. So between those two things, it was very hard to launch the Librié.

But Sony had the vision that if they added a bunch more content and brought it out in the U.S., they would have a product. And at the same time Amazon took note, and said, ‘Aha, the time might finally be right for e-books, if we were to tackle this as a service and sell the content.’ So the Sony PRS-500 launched in 2006 and Amazon came out with the wireless Kindle in 2007, and those guys have each progressively improved their products. From a business point of view, there were some tough times along the way. But since 2004, when we first saw the Librié come out in Japan, our revenues have doubled every year, because we have just been getting more and more devices out there.

He won’t disclose the cost of the Kindle’s 6-inch e-paper screen, but if you want to buy a development kit and design your own device, it’s $3,000.

10 reasons to buy a Kindle 2… and 10 reasons not to

Wednesday, February 25th, 2009


John Biggs offers 10 reasons to buy a Kindle 2… and 10 reasons not to. I like his seventh reason not to:

Flight attendants will tell you to turn it off on take off and landing. You can’t explain that it’s epaper and uses no current. You just can’t. It’s like explaining heaven to bears.

Recipe for Disaster: The Formula That Killed Wall Street

Tuesday, February 24th, 2009

Felix Salmon calls David Li‘s Gaussian copula function the formula that killed Wall Street:

In 2000, while working at JPMorgan Chase, Li published a paper in The Journal of Fixed Income titled “On Default Correlation: A Copula Function Approach.” (In statistics, a copula is used to couple the behavior of two or more variables.) Using some relatively simple math — by Wall Street standards, anyway — Li came up with an ingenious way to model default correlation without even looking at historical default data. Instead, he used market data about the prices of instruments known as credit default swaps.

D’oh!

When the price of a credit default swap goes up, that indicates that default risk has risen. Li’s breakthrough was that instead of waiting to assemble enough historical data about actual defaults, which are rare in the real world, he used historical prices from the CDS market.

All the ratings agencies needed was one variable, correlation, to rate a tranche:

As a result, just about anything could be bundled and turned into a triple-A bond — corporate bonds, bank loans, mortgage-backed securities, whatever you liked. The consequent pools were often known as collateralized debt obligations, or CDOs. You could tranche that pool and create a triple-A security even if none of the components were themselves triple-A. You could even take lower-rated tranches of other CDOs, put them in a pool, and tranche them — an instrument known as a CDO-squared, which at that point was so far removed from any actual underlying bond or loan or mortgage that no one really had a clue what it included. But it didn’t matter. All you needed was Li’s copula function.

The CDS and CDO markets grew together, feeding on each other. At the end of 2001, there was $920 billion in credit default swaps outstanding. By the end of 2007, that number had skyrocketed to more than $62 trillion. The CDO market, which stood at $275 billion in 2000, grew to $4.7 trillion by 2006.

We know it all doesn’t end well:

In finance, you can never reduce risk outright; you can only try to set up a market in which people who don’t want risk sell it to those who do. But in the CDO market, people used the Gaussian copula model to convince themselves they didn’t have any risk at all, when in fact they just didn’t have any risk 99 percent of the time. The other 1 percent of the time they blew up. Those explosions may have been rare, but they could destroy all previous gains, and then some.

Li’s copula function was used to price hundreds of billions of dollars’ worth of CDOs filled with mortgages. And because the copula function used CDS prices to calculate correlation, it was forced to confine itself to looking at the period of time when those credit default swaps had been in existence: less than a decade, a period when house prices soared. Naturally, default correlations were very low in those years. But when the mortgage boom ended abruptly and home values started falling across the country, correlations soared.

Managers didn’t understand how the black box worked:

Bankers should have noted that very small changes in their underlying assumptions could result in very large changes in the correlation number. They also should have noticed that the results they were seeing were much less volatile than they should have been — which implied that the risk was being moved elsewhere. Where had the risk gone?

They didn’t know, or didn’t ask. One reason was that the outputs came from “black box” computer models and were hard to subject to a commonsense smell test. Another was that the quants, who should have been more aware of the copula’s weaknesses, weren’t the ones making the big asset-allocation decisions. Their managers, who made the actual calls, lacked the math skills to understand what the models were doing or how they worked. They could, however, understand something as simple as a single correlation number. That was the problem.

Taleb of course proclaims, “Anything that relies on correlation is charlatanism.”

Startups in 13 Sentences

Monday, February 23rd, 2009

Paul Graham offers 13 sentences of wisdom for startups:

  1. Pick good cofounders.
    Cofounders are for a startup what location is for real estate. You can change anything about a house except where it is.
  2. Launch fast.
  3. Let your idea evolve.
  4. Understand your users.
  5. Better to make a few users love you than a lot ambivalent.
  6. Offer surprisingly good customer service.
  7. You make what you measure.
  8. Spend little.
  9. Get ramen profitable.
    “Ramen profitable” means a startup makes just enough to pay the founders’ living expenses.
  10. Avoid distractions.
    Nothing kills startups like distractions. The worst type are those that pay money: day jobs, consulting, profitable side-projects.
  11. Don’t get demoralized.
  12. Don’t give up.
  13. Deals fall through.

The Crisis of Credit Visualized

Sunday, February 22nd, 2009

Jonathan Jarvis has produced a beautiful piece, The Crisis of Credit Visualized, as part of his thesis work for the Media Design Program at the Art Center College of Design in Pasadena, California:

Not-So-Dutch Auction

Saturday, February 21st, 2009

Years ago, when Google tried its unorthodox style of IPO, the business press described it as a Dutch auction:

Google will be using something called a “Dutch auction.” It’s named after a process used in Holland to bid on flowers. Here’s how it works: You and everyone else makes a bid on what you would pay for a share Google stock and how many shares you would like. When all the bids are in, Google will allocate shares on a pro rata basis to anyone who has bid at or above the initial IPO price, which is set by a threshold price that Google will accept.

Only that’s not what a Dutch auction is:

A Dutch auction is a type of auction where the auctioneer begins with a high asking price which is lowered until some participant is willing to accept the auctioneer’s price, or a predetermined reserve price (the seller’s minimum acceptable price) is reached. The winning participant pays the last announced price. This is also known as a “clock auction” or an open-outcry descending-price auction.

This type of auction is convenient when it is important to auction goods quickly, since a sale never requires more than one bid. Theoretically, the bidding strategy and results of this auction are equivalent to those in a sealed first-price auction.

The Dutch auction is named for its best known example, the Dutch flower auctions.

The Google IPO was a kind of Vickrey auction:

A Vickrey auction is a type of sealed-bid auction, where bidders submit written bids without knowing the bid of the other people in the auction. The highest bidder wins, but the price paid is the second-highest bid. The auction was created by William Vickrey. This type of auction is strategically similar to an English auction, and gives bidders an incentive to bid their true value.

Apparently the OpenIPO methodology pioneered by WR Hambrecht + Co for Google was based on the public offering auction used for Treasury bills, which had somehow become known as a Dutch auction.

Ebay also uses the term this way, for an auction of multiple identical items, where all the winners pay the lowest winning bid.

29 business models for computer games

Saturday, February 21st, 2009

David Perry enumerates 29 business models for computer games:

  1. Retail (bricks & mortar)
  2. Digital Distribution
  3. In-Game Advertising
  4. Around-Game Advertising
  5. Pay Finder’s Fee from First Dollar
  6. Advertgames
  7. Try Before you Buy
  8. Episodic Entertainment
  9. Skill-Based Progressive Jackpots
  10. Velvet Rope
  11. Subscription Model
  12. Micro-Transactions
  13. Sponsored Games
  14. Pay per play
  15. Player to Player trading
  16. Foreign distribution deals
  17. Sell Access to your Players
  18. Freeware 
  19. Loss Leader
  20. Peripheral Enticement
  21. Player to Player Wagering
  22. User Generated Content
  23. Pay for Storage Space
  24. Pay for Private Game Server
  25. Rental 
  26. Licensing Access
  27. Selling Branded Items
  28. Pre-Sell the Game to the Players
  29. Buy Something, get the game for Free

Staff Jobs vs. Line Jobs

Thursday, February 19th, 2009

Shannon Love believes the Chinese are going to kick our asses. I don’t know to what degree I agree with that, but David Foster’s comment caught my attention:

One more thing that’s kind of worrisome is the growing preference for “staff” jobs rather than “line” jobs among the highly educated. (I use “line” here to refer to a job in which an individual has decision-making authority and accountability for the results of those decision, and “staff” to refer to a job which is basically advisory in nature.)

There are a lot of people who are more thrilled by the chance to have proximity to some galactic decision (“should our company spend $10 billion on acquisition X”) than by the chance to have actual ownership of some less-galactic decision (“how many Gerbilator units should we produce this quarter, and what should we price them at?”) To some extent, this represents an attempt to extend the habits of school into the workplace; it also has a component of sheer cowardice.

This phenomenon is at its peak in the “non-profit” world, but also exists in business (as in the example above) and in government… where many “elite” college graduates would be excited about writing a paper on “transportation alternatives for the nation in 2020?” but would be most uninterested in being the Atlanta tower manager for the FAA.

Pepsi Throwback?

Wednesday, February 18th, 2009

Beverage Industry reports that PepsiCo will be releasing versions of Pepsi and Mountain Dew that are once again sweetened with real sugar, rather than High Fructose Corn Syrup (HFCS):

Typically, the only way to get soda from the “big guys” with real sugar is to import it (i.e., Mexican Coke) or wait till Passover (Kosher Coke, Kosher Pepsi).

Pepsi has been experimenting elsewhere with sugar-sweetened drinks. We reported last February about two such entries… Pepsi Raw in the UK and Mexico’s Pepsi Retro.

I’m surprised that the UK and Mexico don’t already use sugar in their Pepsi products. The primary reason the US versions switched was price — sugar tariffs and corn subsidies convinced manufacturers to switch to corn syrup in the early 1980s:

A system of tariffs and sugar quotas imposed in 1977 significantly increased the cost of importing sugar, and producers sought a cheaper alternative. High-fructose corn syrup, derived from corn, is more economical because the American and Canadian prices of sugar are twice the global price and the price of #2 corn is artificially low due to both government subsidies and dumping on the market as farmers produce more corn annually. HFCS became an attractive substitute, and is preferred over cane sugar among the vast majority of American food and beverage manufacturers. For instance, soft drink makers like Coca-Cola and Pepsi use sugar in other nations, but switched to HFCS in the U.S. in 1984. Large corporations, such as Archer Daniels Midland, lobby for the continuation of these subsidies.

Other countries, including Mexico, typically use sugar in soft drinks. Some Americans seek out Mexican Coca-Cola in ethnic groceries, because they feel it tastes better or is healthier than Coke made with HFCS, or because they believe it will have less effect on obesity.

The Bentonville Mafia

Wednesday, February 18th, 2009

The Bentonville Mafia has taken over Microsoft, and now that these former Wal-Mart execs are in charge, they want to open retail stores — which is not a bad idea, Cringely says:

So it seems inevitable to me that as Microsoft is operated more and more by executives from a giant retailer, that Microsoft will try doing some giant retailing of its own. And sure enough they are doing just that through this new plan to open Microsoft stores — a plan that could equally be laid at the feet of Apple as yet another Microsoft tactic copied from Cupertino.

Only Microsoft stores are different from Apple, stories, we’re told, and that’s true: Apple needed distribution while Microsoft has distribution, in spades. In fact Microsoft has so much distribution that this chain of stores could be viewed very negatively by Microsoft resellers but probably won’t be because I doubt that Microsoft will be actually trying to sell much stuff, and what they do sell will be at full retail unlike everyone else. It’s like buying wine at the winery: you never get a deal, but the samples are free.

So you can try out that cool game computer at Microsoft but actually buy it at Best Buy, just as you would have before.

Why even do it, then? Why have these stores?

Propaganda.

Phil Schiller of Apple made the point back in January when he explained that Apple stores had 400,000 visitors per day or the equivalent of 20 Macworld shows every day. Microsoft wants the same thing. They want to bypass the press machine that they feel has tainted users against Windows Vista, making sure the same thing doesn’t happen to Windows 7.

If Microsoft can achieve that one goal — just that one — then the Microsoft stores will have been worth doing even if they never have a dollar of retail sales.