Why I Never Hire Brilliant Men

Tuesday, October 30th, 2007

Why I Never Hire Brilliant Men originally appeared in the February 1924 issue of The American Magazine. An excerpt:

Every year I picked up a half-dozen live young fellows who seemed to have a capacity for hard work, and shoved them in at the bottom of the pile, letting them make their way up to the better air and sunlight at the top — if they had it in them to do it.

For a time I tried picking these youngsters out of the colleges. But my experience with college men was not fortunate. If I selected good students, I found too often that their leadership had been won by doing very well what their teachers had laid out for them. They had developed a fine capacity for taking orders, but not much initiative. If I hired athletes, too many of them seemed to feel that their life work was done; that the world owed them a living in exchange for what they had achieved for the grand old school. Also, there is not much social distinction in the grocery business. Young ladies — and their mothers — are much more thrilled by bonds than by butter and eggs.

So I took most of my raw material from our delivery wagons, or other places right at hand. Out of this hard-muscled, hard-headed stuff I have built a business that has made me rich according to the standards of our locality, and has built modest fortunes for at least twenty other men. More important than that, it has stood for clean dealing and a faithful adherence to the best business ethics. Even our hottest competitors, I think, are willing to grant us that.

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Will Work With Food

Monday, October 29th, 2007

I was just discussing the logistics of Internet-based grocers with some colleagues, and I came across this Forbes piece, Will Work With Food, about FreshDirect, which is succeeding where WebVan failed:

FreshDirect’s continued success depends entirely on product quality and logistical prowess. “The challenge is for the 33 pieces to show up in the factory at the same time to get on the truck,” says Kelly McGowan, chief information officer. He still spouts the lingo of his old job on Wall Street, comparing food delivery to the electronic transmission of stock and bond trading orders.

FreshDirect worries about things as minuscule as the number of times an item gets scanned before it gets to the packing station. There, workers wearing snowsuits (parts of the warehouse are chilled to 36 degrees) take items off a conveyor, scan them and put them in a cardboard box.

If the wrong item gets sent to the packers by mistake, a runner exchanges it, holding up the order and possibly the entire refrigerated truck. Over the last few years the company invested in additional scanners so that items get scanned three times before they reach the box, providing extra places to catch mistakes. The additional 50 cents it costs to find an error is a lot less than the $6 or so it would cost if the error slipped through. “We’re eliminating human error as much as possible,” says Operations Manager Ariel Ramirez.

FreshDirect benefits from not having to arrange items as a store would, with high-profit items at eye level and low-profit bulk items down low. Instead, items on eight long shelves are arranged based on how often they’re ordered, how much they weigh and how delicate they are. Heavy jugs of Tide detergent go at the beginning of the picking process and fragile sliced breads at the end. Pickers take the items off the shelves and put them into a nine-box array that moves between picking bays on an overhead track, like a ski lift.

If orders are finished but their picking basket has to wait in line behind incomplete orders, the company wastes money. Pickers now send 35% of all orders through quicker, cutting the boxes’ travel time from 45 minutes to 30. The software creates one pick list for items stored in farther-out aisles and another for closer-in items, where most of the pickers work. Where once an order traveled an average of 1,000 feet in the warehouse, now it goes 830 feet.

FreshDirect’s 150 drivers must race to meet the two-hour window the company promises customers. Without maps or GPS, Manhattan-bound drivers have to know the intricacies of service elevators, parking spots and difficult building superintendents. That’s why new drivers deliver 35% fewer orders than experienced ones. During rush hour FreshDirect limits the number of delivery slots it offers and keeps drivers away from crowded streets, instead dispatching a bigger truck to serve as a base for deliverymen pushing handcarts to customers’ apartments.

The kitchen where FreshDirect’s executive chef, Michael Stark, prepares his packaged meals is increasingly automated, too. Stark spent two years translating his recipes into the SAP factory software. When an order for lasagna comes in, the system checks the kitchen’s inventory and orders meat, pasta, cheese and tomato sauce, routing the meat to the deli for grinding. There’s more automation to come, with machines to grill pizzas and form meatballs.

New Yorkers already turn to Stark for 1,000 rotisserie chickens a week. As the company gets bigger, squeezing costs is as important as squeezing oranges.

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Smart Complexifier

Monday, October 29th, 2007

Tom Peters argues that the analyst from hell is the smart complexifier:

Years ago, in my McKinsey days, one of my bosses was bemoaning the help we were getting from an “economic genius.” He said, “Tom, consider a matrix. One axis boils down to ‘simplifier’ vs ‘complexifier.’ The other is ‘smart’ and ‘dumb.’ Thus we are dealing with a 2X2 matrix. The analyst-from-heaven is the ‘smart simplifier.’ The analyst-from hell is ‘smart complexifier.’ He is, in fact, worse that the ‘dumb complexifier,’ who you can simply ignore, and the ‘dumb simplifier’ who might actually be of help.”

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Don’t Forget to Listen to the Ship

Monday, October 29th, 2007

David Foster shares some deep thoughts on Decision-Making in Organizations from Don Sheppard’s Bluewater Sailor:

When a decision is made in an organizational context (as opposed to a decision by an entirely autonomous individual), additional layers of complexity and emotion come into play. The person who must make the decision is often not the person who has the information/expertise on which the decision must be based. Indeed, the information and expertise are often distributed across multiple individuals. These individuals may have their own objectives and motivations, which may differ from the objectives and motivations of the formal decision-maker, and which may conflict with each other. And the making of the decision may alter power relationships within the organization, as well as influencing the phenomena about which the decision is ostensibly being made.

The above factors are illustrated with crystalline clarity in the story of a seemingly very simple decision, which had to be made onboard a U.S. Navy destroyer sometime during the 1950s.

Don Sheppard was the newly-appointed Engineering Officer of the USS Henshaw, with responsibility for its 60,000-horsepower turbine plant. But his knowledge of propulsion equipment came entirely from study at the navy’s Engineering Officer School. Reporting to Sheppard was the “Chief,” an enlisted man with no theoretical training but with twenty years of experience in the practical operation of naval power plants. When Sheppard assumed his new duties, the Chief’s greeting “bordered on rudeness.” The man clearly believed that engineering officers might come and go, but that he, the Chief, was the one who really ran things, who was the “Prince of the Plant.”

During maneuvers off the Pacific coast, a bizarre accident resulted in the Henshaw dropping a depth charge which exploded very close to its own stern. The shockwave was enough to knock down men who were standing on deck. Sheppard asked the Chief if he thought the plant might have suffered any damage:

He furrowed his brow, glaring at me. “Damage, sir? We’d know about any major damage by now if the plant suffered. i don’t think we got any problems, sir,” he answered — patronizingly — in a civil enough tone, but barely so. Who was I, an interloper, to dare question the Prince of the Plant?

But Sheppard remembered a movie he had seen in Engineering Officer School: it suggested that a shock like the one Henshaw had just experienced might have damaged the stern tube packing and the bearings through which the drive shafts ran. He mentioned this concern to the Chief, who discounted it with considerable sarcasm. “Maybe in some of them fancy movies it happened that way, sir, but nothin’s wrong here.”

Sheppard went to see the captain, and reported his concern about the possible damage. The spring bearnings could not be easily checked with the ship underway. The decision that had to be made was this: to check and possibly replace the bearings while at anchor, or to sail with the flotilla. The flotilla was comprised of eight destroyers, and the commodore was looking forward to having them all sail into Toyko Bay together. Furthermore, if Henshaw didn’t sail with the group, they would miss the rendezvous with the refueling tanker, and would have to refuel at an upleasant place called Dutch Harbor. But if they did sail and the bearings failed, they would have to be replaced while underway — a difficult and possibly dangerous task.

Legally and formally, the decision was the captain’s. But he knew little about the propulsion plant: it is doubtful that he really understood what the spring bearnings actually were. He had to depend on the opinions of his subordinates.

He asked the advice of those assembled for the conference. The Executive Officer said “sail.” The Chief recommended, “sail.” Now the captain turned to his Engineering Officer and asked very formally: “Your opinion, Mr Sheppard?”

What a dilemma the captain was in. Here, a junior officer with six days’ experience as a chief engineer is obviously wanting to pull out of the squadron sail and check all the spring bearings in direct contradiction to a professional, well-experienced engineering chief who’d been doing the job for twenty years.

If the captain said yes to the inspection and we missed the squadron sail, he’d look bad. He’d look even worse if he suspected they might be bad and they were, and they failed at sea. in rough weather he’d still be left behind and another ship would have to be used as an escort. The commodore had his dream set on his full squadron of eight destroyers steaming proudly into Toyko Bay. It hadn’t happened in a long time.

If I said we should inspect the spring bearings and the captain agreed with me, and the bearings were bad, it would injure the chief’s pride and his position in the engineering department. A wise-ass ensign would have shown him up, thereby throwing into question his professional ability.

If I said don’t sail and the bearings checked out okay, it would reinforce the opinion that officers stick together no matter how stupid the officers’ actions might be.

If I said don’t sail before a bearings check and we sailed anyway and the bearings failed, the captain’s competence would be called into quesion by the crew. He would have been wrong, and the word gets around the fleet mighty fat.

On the other hand, if I said we should sail, thereby taking a chance of a failure and the bearings were okay, it would just show my inexperience and that I didn’t really know what was going on. After all I had been a chief engineer for only six days. There would be little harm done.

Who is the real decision-maker in this scenario? The captain has the formal authority, but little relevant knowledge, either practical or theoretical. The Chief has the practical experience, but no theoretical training, and lacks the authority of officer rank. Sheppard has formal authority for the plant, together with theoretical training, but almost no practical experience.

Most likely, the true decision-maker is Sheppard. From the dynamics of the situation, I suspect that the captain would have done whatever he advised.

“Sail, Captain, I think they’ll be okay,” I answered, as the ship whispered to me that I was wrong.

As the ship whispered to him that he was wrong.

Henshaw sailed with the flotilla, and almost immediately came the report that Number 3 spring bearing was running hot. The starboard engine was stopped, and sailors began the arduous task of replacing the bearing. This involved sliding jacks under the shaft and lifting it up a few centimeters, then sliding out the 80-pound bearing and sliding a new one in. This had to be done as the ship pitched and rolled, while standing in icy bilge water. The task wasn’t complete when the report came that another bearing had failed — this time, the Number 2 bearing on the port engine. That engine had to be stopped also, and Henshaw was taken in tow by another ship of the flotilla. Sheppard pitched in with the work, and had his hand badly cut by protuding metal slivers. Others were hurt more seriously; one man had his right hand badly injured when Number 2 bearing broke loose, smashing his hand against the bearing foundation.

Glassy eyed from the painkillers…Smallwood held onto the throttle board, trying to keep his attention on the gauges. His head nodded. Chief Maclin sent him to his bunk. “I’m sorry, Smallwood,” he said, helping him up the ladder. “Goddamn, I’m really sorry.”

Chief Maclin turned to me, wiping a tear from his eyes, and without word or expression offered his greasy, bloody hand.

After everything was under control, the captain called Sheppard to his cabin for a debriefing on what had happened. First, he critized himself for the mishap that had led to the initial proble, the accident with the depth charge. Second, he criticized himself for not listening more seriously to Sheppard’s initial concerns about the bearings. But he also had something else to say:

“And third, Don, you, you’re a direct contributor.” My face dropped. I thought I was a hero. “If you thought you wre right — and you did think you were right — you should have put up more opposition, not roll over dead because of the obvious resistance of the three of us. I think, Don, that’s the greatest lesson for you to learn in this whole thing.”

The kind of political anaysis that Sheppard conducted before making his recommendation — what will be the effect of this alternative on my relationship with the Chief?..what will be the effect on the Chief’s image with his own subordinates? — is made every day by people in organizations, and must be made, given the realities of organizational life.

But while considering the political dynamics — don’t forget to listen to the ship.

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The Logic of Failure

Sunday, October 28th, 2007

I’ve been meaning to read The Logic of Failure — subtitled Recognizing and Avoiding Error in Complex Situations — for some time, but after reading this review I realize it’s even more up my alley than I imagined:

In any bookstore, you will find dozens or even hundreds of books devoted to “success.” In this book, Dietrich Doerner works the other side of this street. He studies failure. Doerner, a professor of Psychology at the University of Bamberg (Germany) uses empirical methods to study human decision-making processes, with an emphasis on understanding the ways in which these processes can go wrong. His work should be read by anyone with a responsibility for making decisions, particularly complex and important decisions.

Doerner’s basic tool for study is the simulation model. Many of his models bear a resemblence to Sim City and similar games, but are purpose-designed to shed light on particular questions. The nature of many of these models implies that they use human umpires, as well as computer processing. (Doerner uses the simulation results of other researchers, as well as his own experimental work, in developing the ideas in this book.)

Probably the best way to give a feel for the book is to describe some of the simulations and to discuss some of the conclusions that Doerner draws from them.

In the fire simulation, the subject plays the part of a fire chief who is dealing with forest fires. He has 12 brigades at his command, and can deploy them at will. The brigades can also be given limited autonomy to make their own decisions.

The subjects who fail at this game, Doerner finds, are those who apply rigid, context-insensitive rules…such as “always keep the units widely deployed” or “always keep the units concentrated” rather than making these decisions flexibly. He identifies “methodism,” which he defines as “the unthinking application of a sequence of actions we have once learned,” as a key threat to effective decision-making. (The term is borrowed from the great military writer Clausewitz.) Similar results are obtained in another simulation, in which the subject is put in charge of making production decisions in a clothing factory. In this case, the subjects are asked to think out loud as they develop their strategies. The unsuccessful ones tend to use unqualified expressions: constantly, every time, without exception, absolutely, etc…while the successful “factory managers” tend toward qualified expressions: now and then, in general, specifically, perhaps,…

The Moro simulation puts the subject in charge of a third-world country. His decision-making must include issues such as land use, water supply, medical care, etc. Time delays and multiple interactions make this simulation hard to handle effectively…a high proportion of subjects wound up making things worse rather than better for their “citizens.” Human beings, Doerner argues, have much more difficulty understanding patterns that extend over time than patterns that are spatial in nature.

Many subjects in this simulation showed obsessive behavior — they would focus on one aspect, such as building irrigation canals, and ignore everything else, without even really trying to understand the interactions.

Doerner wanted to know what kinds of previous experience would help most in this game, so he ran it once with a set of college students for subjects, and again with a set of experienced business executives. The students had probably been more exposed to concepts of “ecological thinking” — but the executives did significantly better. This argues that there are forms of “tacit knowledge” which are gained as a result of decision-making experience, and which are transferable to at least some degree across subject matter domains.

One simple but surprisingly interesting experiment was the temperature control simulation. Subjects were put in the position of a supermarket manager and told that the thermostat for the freezers has broken down. They had to manually control the refrigeration system to maintain a temperature of 4 degrees C — higher and lower temperatures are both undesirable. They had available to them a regulator and a thermometer; the specific control mechanism was not described to the subjects. The results were often just bizarre. Many participants failed to understand that delays were occurring in the system (a setting does not take effect immediately, just as an air conditioner cannot cool a house immediately) and that these delays needed to be considered when trying to control the system. Instead, they developed beliefs about regulator settings that could best be described as superstitious or magical: “twenty-eight is a good number” or, even more strangely, “odd numbers are good.”

One very interesting angle explored by Doerner is the danger, in decision-making tasks, of knowing too much — of becoming lost in detail and of always needing one more piece of information before coming to a decision. He posits that this problem “probably explains why organizations tend to institutionalize the separation of their information-gathering and decision-making branchs” — as in the development of staff organizations in the military. (It may also, it seems to me, have much to do with the hypercritical attitude that many intellectuals have toward decision-makers in business and government — that is, they fail to understand that the effective decision-maker must reduce a problem to its essences and cannot be forever exploring the “shades of gray”)

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Costs for Simulations

Saturday, October 27th, 2007

Clark Aldrich goes over the costs for simulations — which can vary quite a bit:

Branching story:

Simulation in which students make a series of decisions via a multiple choice interface to progress through and impact an event.

  • Custom short (Less than 10 minutes): 30K
  • Custom medium (Between 10 minutes and 30 minutes): 100K
  • Custom long (Between 30 minutes and 2 hours): 500K
  • Off the shelf short (per user): $30
  • Off the shelf medium (per user): $100
  • Off the shelf long (per user): $500

Interactive spreadsheets:

Simulation in which students typically try to impact critical metrics by allocating resources along competing categories and getting feedback of their decisions through graphs and charts.

  • Custom short (Less than 1 hour): 30K+
  • Custom medium (Between 1 hour and 4 hours): 100K+
  • Custom long (Between 4 and 8 hours): 500K+
  • Off the shelf short (per user): $30*
  • Off the shelf medium (per user): $100*
  • Off the shelf long (per user): $500*

+ plus cost of facilitation, * including cost of facilitation

Mini games:

Small, easy-to-access game built to be simple and addictive, which often focuses on mastering an action and can provide awareness of more complicated issues.

  • Custom short (5 minutes): 10K
  • Custom medium (10 minutes): 15K
  • Custom long (30 minutes): 40K
  • Off the shelf short (per user): n/a
  • Off the shelf medium (per user): n/a
  • Off the shelf long (per user): n/a

Virtual product or virtual lab:

A series of challenges/puzzles to be solved using on-screen representations of real-world objects and software.

  • Custom short (30 minutes): 30K
  • Custom medium (1 hour): 75K
  • Custom long (4 hours): 150K
  • Off the shelf short (per user): $10
  • Off the shelf medium (per user): $30
  • Off the shelf long (per user): $100

Practiceware:

Real-time, often 3D sims that encourages participants to repeat actions in high fidelity situations until the skills become natural in the real-world counterpart

  • Custom short (1 hour): 100K+
  • Custom medium (5 hours): 500K+
  • Custom long (20 hours): 1000K+
  • Off the shelf short (per user): $100*
  • Off the shelf medium (per user): $400*
  • Off the shelf long (per user): $1000*

+ plus cost of facilitation, * including cost of facilitation

Increasing Cost

Here are some items that typically and significantly increase costs:

Note: All genre links include examples of the genre in [brackets]. Go to mini games and launch a few [examples].

He also shares an exasperating example of trying to sell a simulation project to a corporate training person:

Training Person: I can’t do simulations. They are too expensive.

Me: Not necessarily. There are many simple models. There are branching stories, virtual products, interactive spreadsheets, game based models, just to name a few.

Training Person: And are these more effective in achieving learning goals?

Me: Yes. They have very impressive long term productivity benefits.

Training Person: Those are great. But how about multiplayer ? Do you have any examples of multiplayer?

Me: OK. Here they are.

Training Person: Those are cool. But you have any with better scoring and coaching built in as well?

Me: Sure. Here are a few other examples.

Training Person: Animations and advanced graphics are really important to me. Do you have any examples of sims also with really great, smooth animation?

Me: Yup, I have a few right here.

Training Person: Our corporate colors are blue and red? Is it possible to customize it?

Me: Yes.

Training Person: Wow, that is so fantastic. That really blow me away. It’s too bad, really.

Me: What is?

Training Person: I can’t do simulations. They are too expensive.

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Why Some People Are Lucky

Saturday, October 27th, 2007

Watch this video. (It’s a Java applet.) When viewing the video, try to count the total number of times that the people wearing white pass the basketball. Do not count the passes made by the people wearing black.

Watch the video. I’ll wait.

I’ve commented on that video before, but it turns out that it’s also a favorite of Richard Wiseman, who recently explained to Forbes
why some people are lucky:

The human brain is amazingly good at detecting what it wants to find. When you are hungry, your brain focuses on finding food. When you are thirsty, it looks for liquid. The problem is, your brain can become so focused on seeing what it expects to see, it misses things that are obvious but unexpected. Lucky people tend to have a somewhat relaxed view of life. They are less concerned with mundane details and more prone to look at the bigger picture. Ironically, by trying less, they see more.

Exactly the same principle applies to the opportunities that bombard us in everyday life. In another experiment, I gave some volunteers a newspaper and asked them to look through it and tell me how many photographs were inside. What I didn’t tell them was that halfway through the newspaper I had placed an unexpected opportunity. This “opportunity” took up half a page and announced, in huge type, “Win £100 by telling the experimenter you have seen this.” The unlucky people tended to be so focused on counting the photographs they failed to notice the opportunity. In contrast, the lucky people were more relaxed, saw the bigger picture and so spotted a chance to win £100.

There’s more. “Lucky people possess a whole host of opportunity-attracting traits.”

You will quickly exhaust your potential opportunities if you keep talking to the same people, taking the same route to and from work and going to the same places on holiday. But introducing new or random experiences is like visiting a new part of the orchard–suddenly you are surrounded by hundreds of apples.

Lucky people had developed various interesting ways of introducing such variety. One noticed that whenever he went to a party, he tended to talk to the same type of people. To help disrupt this routine, he randomly chose a color before arriving at the party, and then only spoke to people wearing that color of clothing at the party.

Yet another trait:

Lucky people experience a large number of seemingly chance encounters. They bump into someone at a party, discover that they know people in common, and from these connections end up getting married or doing business together. Or when they need something, they always seem to know someone who knows someone who can solve their problem.

I wondered if these “small world” experiences were due to knowing a large number of people, and being tied into more elaborate social networks than most. To discover if this was the case and quantify the nature of these networks, I employed a method described by Malcolm Gladwell in his book The Tipping Point. To explore the notion of social connectivity, Gladwell carried out an informal study in which he presented people with a list of surnames and asked them to indicate if they knew people with that surname. Similarly, I asked hundreds of lucky and unlucky people to look at a list of 15 common surnames, and indicate if they were on first-name terms with at least one person with each surname.

The results were dramatic and demonstrated the huge relationship between luck and social connectivity. Almost 50% of lucky people ticked eight or more of the names, compared with just 25% of unlucky people. Further work has shown lucky people tend to be extroverts who both meet a large number of people and keep in contact with them. The building and maintaining of such social networks significantly increases the likelihood of having a “lucky” chance encounter.

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Five Easy Ways to Fail

Thursday, October 25th, 2007

Joel Spolsky explains Five Easy Ways to Fail when managing a big software project:

Mistake No. 1: Start with a mediocre team of developers.
Designing software is hard, and unfortunately, a lot of the people who call themselves programmers can’t really do it. But even though a bad team of developers tends to be the No. 1 cause of software project failures, you’d never know it from reading official postmortems. In all fields, from software to logistics to customer service, people are too nice to talk about their co-workers’ lack of competence. You’ll never hear anyone say “the team was just not smart enough or talented enough to pull this off.” Why hurt their feelings? The simple fact is that if the people on a given project team aren’t very good at what they do, they’re going to come into work every day and yet — behold! — the software won’t get created. And don’t worry too much about HR standing in your way of hiring a bunch of duds. In most cases, I assure you they will do nothing to prevent you from hiring untalented people.

Mistake No. 2: Set weekly milestones.
Say you’re remodeling your kitchen. That guy you hired to do the work has done a lot of kitchens before, and can estimate the cost of the job without having detailed blueprints. But software developers are building things that they’ve never built before. If they had, they’d just sell you another copy of the CD-ROM. So rough estimates are impossible. They need to draw up detailed plans before they start writing code. Whether you’re the customer or the developers’ manager, your job is to make sure they come up with that blueprint. When you ask developers for one, however, many of them will respond by creating a schedule that breaks pieces of the process into weeks. This may seem perfectly reasonable, but it’s not. If you let a software team submit a schedule with big chunky estimates of time (by big I mean more than two days of work), you can be almost certain that they’re not considering every detail that needs to be implemented, and those details will add up to a huge delay.

Mistake No. 3: Negotiate the deadline.
What’s worse than accepting a schedule that breaks down a software project by the week? Demanding that a team commit to completing its work much sooner than forecast. In my experience, most developers are optimists and will take your cue and engage in split-the-difference bargaining. You’ll have a nice, agreed-upon schedule that you’ll never stick to.

Think of it in these terms: Mama walruses deliver their calves at the end of a 15- to 16-month pregnancy. You might ask the mother to commit to 15 months and she might say, “No problem!” Or you might say, “Fifteen months? Are you crazy? We need this in eight months!” Of course, haggling like this can’t possibly make things happen any faster, and even if you get the walrus to agree to an eight-month timetable, I’ll let you in on a little secret: It’ll never happen. You can have a schedule that says 11 months, but you’ll still ship in 15 months, because that is how long it takes to make a baby walrus. Sixteen, sometimes.

Mistake No. 4: Divide tasks equitably.
Here’s a great way to torpedo any project. Make a list of all the work people have to do, and then reassign things to different people to balance the project. If Mary has too much work, give some of her tasks to John. This sounds completely sensible, so you won’t be challenged.

But I promise you, in the long run it’s sure to cause problems. That’s because when one developer steps in to replace another, it’s reasonable to assume that the new one will work at about one-tenth the speed. John’s going to have to spend untold hours figuring out all the things that Mary already knows about her area of code. And John can’t fix Mary’s bugs as fast as Mary can because Mary knows where all the hidden traps are.

Mistake No. 5: Work till midnight.
Let’s say a project should take six months at 40 hours a week to complete. If you told everybody to work 60 hours a week, you could finish the development in four months flat. The software team might even embrace this challenge because it will make them look like heroes (“How great is that Walrus team? They’re here every weekend!”). This should work, right? Guess again. There’s a whole body of literature establishing that working more hours doesn’t produce software any faster. Edward Yourdon, the software entrepreneur and author, dubbed this kind of project the “death march.”

Software development takes immense intellectual effort. Even the best programmers can rarely sustain that level of effort for more than a few hours a day. Beyond that, they need to rest their brains a bit, which is why they always seem to be surfing the Internet or playing games when you barge in on them.

Compelling them to spend even more hours sitting in front of a computer won’t really translate into more output–or if it does, it will be the wrong kind of output. When their brains are completely fried, software developers are almost certainly going to do more damage than good, writing unusable code and introducing bugs galore. And if you do ban the Internet and multiplayer games to force them to keep writing code past their natural bedtimes, well, they’ll probably start quitting on you. Running a death march is not the only way to make a project late and a budget buster. But it is a surefire way to do so.

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MySpace Seeks to Create A Destination for Games

Thursday, October 25th, 2007

The Wall Street Journal notes that MySpace is seeking to create a destination for casual gamers by hiring Oberon Media.

Casual games are very popular, but they aren’t bringing in as much money as “hardcore” games yet, because they’re typically free:

Casual games accounted for just $380 million in revenue last year in the U.S., compared with $4.78 billion in sales of console games, according to estimates by Pacific Crest Securities and NPD Group Inc.

The growth rate for the business is more than double that of the console business, with casual-games revenue expected to jump 35% to $512 million this year, predicts Pacific Crest.

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Video games train new miners in Peru

Friday, October 19th, 2007

Simulators and “serious games” have been popular with the military for decades. Now video games are being used to train new miners in Peru:

Giant video games with throaty diesel engines powering monster-sized earth movers, excavators and dump trucks have hardened miners at a metals conference this week in Peru giggling like children.

Far more than just a gimmick to attract customers to the Caterpillar Inc. stand, the video games are actually simulators designed to help teach people to use massive, multimillion-dollar heavy mining equipment.
[...]
Caterpillar says the simulators allow companies to train people without having to take costly equipment out of service, or risk expensive accidents.

Dump trucks of 180 tones sell for around $2.5 million and excavators in the mining industry can cost up to $20 million.

The simulators at the 28th biannual mining conference in Peru’s colonial city of Arequipa are modeled after similar ones used to train airplane pilots.

Players struggle at first to use a blinking and buzzing mix of pedals, levers and buttons to motor around huge plasma screens.

One test has players pick up dirt with an excavator and deposit it in a dump truck.
[...]
The simulators require drivers to pass through timed obstacle courses in simulated mining pits, being careful to avoid wrecking multimillion-dollar rigs and causing the games to crash.

The driver’s cabin in the dump truck bounces over the rough road of mines and some players enjoyed backing the truck up to a ravine and pulling a lever to dump the dirt load.

With skilled equipment operators in short supply, the simulators could also help fill a hole as new mines come into operation.

“There are some real shortages of people in the mining industry right now, so anything involving training is useful,” said John Capehart of Automated Positioning Systems, which makes sensors that help show excavators where to dig.

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The Strategy of Technology and Project Management

Tuesday, October 16th, 2007

Stefan Possony, Jerry Pournelle, and Francis Kane wrote the original draft of The Strategy of Technology from 1968 to 1970 — “a time when the Cold War was real and the outcome still very much in doubt” — and then updated it over the years.

It argues that the US should have a clear strategy for winning the Technological War, and in the process it makes some points about project management:

Apollo

The Apollo program of manned exploration of the Moon was certainly the outstanding achievement of this Century. It is a landmark of what the U.S. could achieve given a challenge to the scientific and engineering community.

The Apollo program was also the most complex action ever undertaken by the human race. It is interesting to note that the second most complex activity in history was Overlord, the Allied invasion of Normandy in 1944. Although Apollo was accomplished outside the Department of Defense, it was no accident that many of the key leaders, such as General Sam Phillips, were highly experienced managers of advanced military technology programs.

The Apollo program was mission oriented. Its management structure closely resembled a military organization. Instead of micro-management from the top, there was delegation of authority. Tasks were narrowly defined, and responsibility for achieving them was spelled out in detail. As with the ICBM program, parallel processes were set up to investigate alternate ways of achieving critical tasks.

The result was that technology was produced on demand and on schedule. Setbacks and even tragedies such as the capsule fire did not halt the program. On 20 July, 1969, the Eagle landed on the Moon, a little more than eight years after President Kennedy began a task which much of the scientific community said could not be accomplished in two decades.

Military Aircraft

In 1962 Project Forecast identified a requirement for new military aircraft. Systems designs began shortly thereafter.

Unlike the Apollo program, both the fighter and bomber programs were micromanaged from the top. There were endless reviews and appeals.

As a result, the first of the new generation of fighter aircraft was not rolled out until the mid-70′s, and were not in the operational inventory in numbers until considerably later; and both the Navy and Air Force are now flying aircraft whose basic designs are twenty years old.

The B-1 fared even worse. Not only was there micromanagement, review, and appeal, but the program itself was cancelled by political authorities. The first operational B-1 was delivered in 1983; we now have a full inventory of 100 B-1 bombers.

The B-1 bomber and the F-14, F-15, F-16, and F-18 fighters are probably the most advanced aircraft of their kind in the world; but the contrast between the 8 years from conception to operation of Apollo, and the 16 and more years from design to operation of these aircraft, is worth noting; particularly when contrasted with the rapid development and deployment of the P-51 and P-47 aircraft during World War II. Recall that the P-51, then the world’s most advanced fighter, went from drawing board to combat operation in under a year.

Note also that the reviews and delays characterizing the development and procurement of the B-1 and the new fighters did not save money. The total program costs were considerably higher than they would have been had we set up a management structure similiar to Apollo; indeed, the total costs of these programs exceeded that of Apollo, which was brought in on time and under budget.

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Toward a History-Based Doctrine for Wargaming

Friday, October 12th, 2007

Despite its unwieldy title, Matthew Caffrey’s Toward a History-Based Doctrine for Wargaming is a fascinating piece with a lot to say about leadership and organizational change:

Today we think of Napoléon as a great military genius, but other factors also played a part in his military success. One factor was that the French Revolution produced a meritocracy. Previously, only children of officers could become officers. Now, half of Napoléon’s marshals had once been common soldiers. Also, a democracy could field a far larger army than a similar-sized monarchy. Genius, meritocracy, and numbers — Prussia would invent modern wargaming while endeavoring, successfully, to overcome all these French advantages.

[...]

While Prussia had used nationalism to overcome France’s advantage in recruiting, it found that adopting a meritocracy was more difficult. Prussia’s solution was to pair commanders selected for their nobility with chiefs of staff selected by merit. Because the only chance even members of the petty nobility had of attaining high rank was selection for the staff corps, virtually all officers wanted to be selected. However, only graduates of the War College were eligible. Moltke now required that each application package include a letter from the applicant’s commander, evaluating his performance as the senior umpire for a wargame. It worked.

When the successful applicants became War College students, Moltke saw to it that they did a great deal more wargaming. Wargaming appears to have always been part of the curriculum at the War College, but Moltke added several innovations collectively called the “staff ride.”

Periodically, Moltke would take the entire student body of the War College to one of the actual invasion corridors into Prussia. Moltke would then describe the most likely first clash between invading and Prussian forces. He would then turn to the most junior student present and ask for his plan of battle. Next he would ask the second most junior, then the third, and so on. Why? If the most senior spoke first, would any disagree?

After arriving at a consensus battle plan, they then played a map-based wargame. Moltke would then name the senior ranking general (aside from himself) to command the invading forces and the second-ranking general to command the Prussian forces. He continued thusly until they were split into two equal teams. Why? Moltke believed that if their plan could succeed against some of their smartest strategists, it would probably also succeed against any enemy strategist. Also, with two equal-sized teams, more officers could participate meaningfully. The next day, he would contact the local garrison (remember the staff ride was being conducted in an actual invasion corridor, so there would always be a garrison). He would direct the garrison commander to march a few hundred soldiers where the plan called for thousands to march. This was done to test the marching times and other details of the plan. When all this was done, the plan went on the shelf as the actual plan for an invasion along that corridor.

Now let us think about all this for a minute. Moltke started with an “off site” (to an environment conducive to candor and free thinking), had a team brainstorm to reach a consensus, tested the resulting plan against a world-class adversary, and finally tested the results with a field exercise. Essentially, he used many smart people and effective procedures to create a plan worthy of a genius, eliminating Napoléon’s final advantage of genius. With all our technology, are we really this conceptually sophisticated today?

Moltke’s politically astute processes did not last:

A series of books published between 1873 and 1876 argued persuasively for a radically different type of wargame. The concept was simple. Wargames have always been unpopular due to the cumbersome, time-consuming rules of adjudication. Therefore, combat-experienced officers were allowed to substitute their military judgment for many of these rules. This would result in games that were faster and thus more popular, hence played more often.

At first, Free Kriegsspiel seemed to work well. At its best, the professional judgment of experienced combat veterans could produce more accurate outcomes in less time. There were two problems, however. First, Germany’s veterans of 1871 gradually aged, retired, and died. Their replacements could not adjudicate with the same authority. The second problem is today called “command influence.” When one of the players outranked the umpire, that player tended to value his professional judgment over that of the umpire.

Nowhere was this problem more visible or more damaging than in the case of Kaiser Wilhelm II. Thinking himself a great military genius, Kaiser Wilhelm never missed a staff ride. The rides still started on a hill overlooking a possible invasion corridor. Just when Moltke would have asked the most junior officer for his opinion, the kaiser would immediately announce the “perfect” battle plan. You can imagine the level of debate. Then, during the actual wargame, instead of having the teams split evenly, everyone wanted to be on the kaiser’s team. The results were predictable; the kaiser’s side always won. It was Germany’s loss.

[...]

Arguably the most decisive wargames of all time were played in 1905. That was the only year Count Alfred von Schlieffen’s plan for a wide-turning movement through neutral Belgium and Holland was wargamed before his retirement. Virtually all present were on the kaiser’s (German) team, while two first lieutenants played on the side of the armies of France, Britain, Belgium, and Holland. The wargame concluded with the destruction of the French army so quickly that the British did not have time to come to the aid of France. The kaiser was pleased.

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Solar’s Day In The Sun

Wednesday, October 10th, 2007

Solar’s Day In The Sun will have arrived when solar power costs less than 10 cents per kilowatt-hour — and new solar concentrators may be about to reach that goal:

The parabolic troughs work well. But the mirrors, among other things, have to be very precise, making them difficult and expensive to build. The original series of plants in the Mojave managed to bring the cost down from 28 cents per kwh to 16 cents, while the newer ones are a penny or two cheaper. But O’Donnell was determined to start at 10 cents and go down from there.

So was there something better and less costly?

O’Donnell stumbled on the answer thumbing through a scientific journal at an engineering society meeting in May, 2006. A paper by University of Sydney professor David Mills described a field of almost flat mirrors focusing the sun’s rays on fixed tubes held by poles above the mirrors (diagram). Such mirrors are easier and cheaper to build than the parabolic troughs, and can be made strong enough to withstand Florida’s hurricanes. And rather than using the troughs’ oil-filled tubes, which sap power to pump the oil, Mills uses the sun’s heat to turn water directly into steam. “It just riveted me. I thought: ‘Whoa, Mills is either a genius or a madman,” O’Donnell recalls. “If it can compete with coal even at the beginning of the learning curve, it will change the world.”

The more he learned, the more intrigued he became. Mills had been working on solar technologies for three decades. In 2002 he had hooked up with local businessman Peter Le Lièvre, who had been building vehicles with liftgates that ranchers use to hoist and transport sheep.

In a rented garage, Le Lièvre bolted together the parts for the first mirror. His team barely got it out between the garage’s pillars. But it worked. “That first mirror had great focus,” says Le Lièvre. “It would burn the hairs off the back of your hand.” On a shoestring, they assembled 60 mirrors into a 1-MW array next to a coal plant in Liddell, New South Wales. When they flipped the switch, steam gushed out. “Everyone was aghast that it worked the first time,” says Mills.

Here’s the finance angle:

Coal plant builders have been able to count on 80% to 90% debt at an interest rate of 5.5% to 6%. Their equity investors expect about an 11% return on equity. That puts the average cost of capital at about 7%. But since no one has built a giant solar plant, investors demand a risk premium. O’Donnell’s equity investors want a richer 20% rate of return. Plus, he can get only 50% debt, at an interest rate of 7.5%. As a result, the overall cost of capital for Ausra’s first plants is 12%.

The hope, therefore, is that the first few large plants show investors that the risk is low, causing the future cost of capital to drop. That would enable Ausra to lower the price below the current 10.4 cents. “Once people build one or two units, the financial risk premium goes away,” explains Jim Ferland, senior vice-president at New Mexico utility PNM.

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Concord Music puts a new spin on classic records

Tuesday, October 9th, 2007

Concord Music puts a new spin on classic records — a lucrative new spin:

It should come as no surprise that a company backed by Norman Lear knows how to make creative use of television. Lear, the TV superproducer who created “All in the Family,” “One Day at a Time,” and other hit shows, is one of the owners of Concord Music Group.

Concord funded a documentary that ran recently on PBS called “Respect Yourself: The Stax Records Story,” about the groundbreaking Memphis label that released albums by Otis Redding, Isaac Hayes, the Staple Singers, and others. What most viewers didn’t know was that Concord had recently bought the rights to the Stax recordings. Sales jumped after the documentary aired.

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Laptop With a Mission Widens Its Audience

Friday, October 5th, 2007

In Laptop With a Mission Widens Its Audience, David Pogue raves about the XO:

In November, you’ll be able to buy a new laptop that’s spillproof, rainproof, dustproof and drop-proof. It’s fanless, it’s silent and it weighs 3.2 pounds. One battery charge will power six hours of heavy activity, or 24 hours of reading. The laptop has a built-in video camera, microphone, memory-card slot, graphics tablet, game-pad controllers and a screen that rotates into a tablet configuration.

And this laptop will cost $200.

The computer, if you hadn’t already guessed, is the fabled “$100 laptop” that’s been igniting hype and controversy for three years. It’s an effort by One Laptop Per Child (laptop.org) to develop a very low-cost, high-potential, extremely rugged computer for the two billion educationally underserved children in poor countries.

The marketing is equally clever:

O.L.P.C. slightly turned its strategy when it decided to offer the machine for sale to the public in the industrialized world — for a period of two weeks, in November. The program is called “Give 1, Get 1,” and it works like this. You pay $400 (www.xogiving.org). One XO laptop (and a tax deduction) comes to you by Christmas, and a second is sent to a student in a poor country.

Let’s look at the technology:

In the places where the XO will be used, power is often scarce. So the laptop uses a new battery chemistry, called lithium ferro-phosphate. It runs at one-tenth the temperature of a standard laptop battery, costs $10 to replace, and is good for 2,000 charges — versus 500 on a regular laptop battery.

The laptop consumes an average of 2 watts, compared with 60 or more on a typical business laptop. That’s one reason it gets such great battery life. A small yo-yo-like pull-cord charger is available (one minute of pulling provides 10 minutes of power); so is a $12 solar panel that, although only one foot square, provides enough power to recharge or power the machine.

Speaking of bright sunshine: the XO’s color screen is bright and, at 200 dots an inch, razor sharp (1,200 by 900 pixels). But it has a secret identity: in bright sun, you can turn off the backlight altogether. The resulting display, black on light gray, is so clear and readable, it’s almost like paper. Then, of course, the battery lasts even longer.

The XO offers both regular wireless Internet connections and something called mesh networking, which means that all the laptops see each other, instantly, without any setup — even when there’s no Internet connection.

With one press of a button, you see a map. Individual XO logos — color-coded to differentiate them — represent other laptops in the area; you connect with one click. (You never double-click in the XO’s visual, super-simple operating system. You either point with the mouse or click once.)

This feature has some astonishing utility. If only one laptop has an Internet connection, for example, the others can get online, too, thanks to the mesh network. And when O.L.P.C. releases software upgrades, one laptop can broadcast them to other nearby laptops.

Some other clever bits:

The built-in programs are equally clever. There’s a word processor, Web browser, calculator, PDF textbook reader, some games (clones of Tetris and Connect 4), three music programs, a painting application, a chat program and so on. The camera module permits teachers, for the first time, to send messages home to illiterate parents.

There are also three programming environments of different degrees of sophistication. Incredibly, one keystroke reveals the underlying code of almost any XO program or any Web page. Students can not only study how their favorite programs have been written, but even experiment by making changes. (If they make a mess of things, they can restore the original.)

There’s real brilliance in this emphasis on understanding the computer itself. Many nations in XO’s market have few natural resources, and the global need for information workers grows with every passing day.

Most of the XO’s programs are shareable on the mesh network, which is another ingenious twist. Any time you’re word processing, making music, taking pictures, playing games or reading an e-book, you can click a Share button. Your document shows up next to your icon on the mesh-network map, so that other people can see what you’re doing, or work with you. Teachers can supervise your writing, buddies can collaborate on a document, friends can play you in Connect 4, or someone across the room can add a melody to your drum beat in the music program. You’ve never seen anything like it.

The article includes a short video.

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