Vampires, Tooth Fairies, Santa Claus, IT Projects

I don’t believe in IT projects. Well, mostly not, but I’ll get to that later. First, here’s Ars Technica on a failure of the Romney Campaign: its app, Orca:

The goal was to put a mobile application in the hands of 37,000 volunteers in swing states, who would station themselves at the polls and track the arrival of known Romney supporters. The information would be monitored by more than 800 volunteers back at Romney’s Boston Garden campaign headquarters via a Web-based management console, and it would be used to push out more calls throughout the day to pro-Romney voters who hadn’t yet shown up at the polls.

Here’s the failure part:

When the Romney campaign finally brought up Orca, the “killer whale” was not ready to perform. Some field volunteers couldn’t even report to their posts, because the campaign hadn’t told them they first needed to pick up poll watcher credentials from one of Romney’s local “victory centers.” Others couldn’t connect to the Orca site because they entered the URL for the site without the https:// prefix; instead of being redirected to the secure site, they were confronted with a blank page, Ekdahl said.

And for many of those who managed to get to their polling places and who called up the website on their phones, there was another, insurmountable hurdle—their passwords didn’t work and attempts to reset passwords through the site also failed. As for the voice-powered backup system, it failed too as many poll watchers received the wrong personal identification numbers needed to access the system. Joel Pollak of Briebart reported that hundreds of volunteers in Colorado and North Carolina couldn’t use either the Web-based or the voice-based Orca systems;  it wasn’t until 6:00 PM on Election Day that the team running Orca admitted they had issued the wrong PIN codes and passwords to everyone in those states, and they reset them. Even then, some volunteers still couldn’t login.

Someone fire the IT department for effing this up. Right? Yet, consider this:

IT projects are easy scapegoats for organizational failures.


IT projects, academia aside, are chasing a business objective. All business projects involve technology, it’s just that normally the technology is very familiar (paper, pencils, telephones).

Unfamiliar technology, on the other hand, can create problems…

Hey, learning on the fly is hard. New technology doesn’t evolve gradually to fit your business. It ‘tips’ into the mainstream after furious validation and iteration in some other sector of the economy then gets chucked at new industries by startups.

Usually it doesn’t stick; that’s why startups are risky. But when startups don’t stick, the business still gets done (it just goes to someone else). It’s the tech that dies, useless.

Startup failures are failures to compete, not failures of technology, per se. The thing that irritates me about “IT projects” is the implicit dissociation of the technology from the business.

Most managers don’t understand the pitfalls of implementing new technology because most new technology doesn’t matter. In the real world we observe that incumbent firms are conservative, reacting “too late” to ideas already validated by the marketplace.

But we also know that business advantage is precious and risking your business on a new idea is insane.

Also remember something Peter Drucker taught: innovation is what matters and that is definitely not the same thing as what we think of as being technology. It’s about process. This can mean smartphone apps, sure, but can also mean weekly internal meetings. Linus Torvalds says: “Bad programmers worry about the code. Good programmers worry about data structures and their relationships.” The tool doesn’t matter, the process matters.

So let’s walk though what the Romney campaign’s process idea:

  1. You need a list of for-sure GOP voters. Easy, already do that.
  2. You need a bunch of people on-site to note which for-sures have voted. Easy, got volunteers everywhere.
  3. Now cross off those that voted and contact those that did not. Wow, interesting idea, we should have been doing that all along.

Ok, give cell phones and pencils to the volunteers and they can make the calls. Right?

Nope, we need to build something that has never been done before. And give it to… seniors? With no instructions? This is a project run by someone who does not know what they’re doing. Because, I’d suggest, it was not run by the person in charge.

To me, the leader of an organization has two qualities: first, he/she is the person that best understands the value that the organization creates. Said another way: the leader has the power to set the priorities of the organization because he/she understands what they should be.

There’s a tradeoff in undertaking a big new project: distraction exchanged for a new competitive edge. A sure cost for an uncertain benefit. The leader, who is best positioned to understand the upside of this trade, makes the call.

But here’s another quality of the leader: he/she is probably the most competent executive as well. And think about the root of the word ‘executive’: execute. An important project must be run by an outstanding operator who can never lose sight of the organization’s priorities in the million of little decisions that go into execution.

Big failures land on the CEO’s desk. If they’re big enough to matter, he was in charge. If he wasn’t, he’s an idiot.

Will Google Write Catastrophe Insurance?

Catastrophe insurance is the sexy part of my industry: lots of data and “analytics” and in tune with the information age. It’s also alternated between the most and least profitable line of business in the business.

Here’s what you need to write the stuff:

  1. A really good map of where buildings are.
  2. Some knowledge of what those buildings are made of and, just as importantly, what they’re worth.
  3. An idea of the susceptibility of each region to natural catastrophes.

In my experience, people in the insurance business put a bit too much emphasis on #3, which a cursory understanding of is easy to get but a deep understanding of is currently beyond any intelligence yet discovered. The reality is that all of the science in the underwriting is in #s 1 and 2: where are the buildings and what are they worth?

What if Google just suddenly realizes it can probably do this better than anyone else?

“We already have what we call ‘view codes’ for 6 million businesses and 20 million addresses, where we know exactly what we’re looking at,” McClendon continued. “We’re able to use logo matching and find out where are the Kentucky Fried Chicken signs … We’re able to identify and make a semantic understanding of all the pixels we’ve acquired. That’s fundamental to what we do.”

More here.

I like imagining an even more tantalizing project: open source cat underwriting. Open Street Maps does most of what Google does except for free.

Will some actuary use this public data to check an industry-changer into Github one day? Might Index Funds (capitalizing this automated underwriting platform) and governments (subsidizing coastal homeowners) one day split all catastrophe insurance between them?

The Yudkowsky Ambition Scale

1) We’re going to build the next Facebook!

2) We’re going to found the next Apple!

3) Our product will create sweeping political change! This will produce a major economic revolution in at least one country! (Seasteading would be change on this level if it worked; creating a new country successfully is around the same level of change as this.)

4) Our product is the next nuclear weapon. You wouldn’t want that in the wrong hands, would you?

5) This is going to be the equivalent of the invention of electricity if it works out.

6) We’re going to make an IQ-enhancing drug and produce basic change in the human condition.

7) We’re going to build serious Drexler-class molecular nanotechnology.

8) We’re going to upload a human brain into a computer.

9) We’re going to build a recursively self-improving Artificial Intelligence.

10) We think we’ve figured out how to hack into the computer our universe is running on.

Source here. Here is more on Eliezer Yudkowsky. Here is wikipedia on Eliezer. He used to blog with Robin Hason, a powerful signal of quality.

THUMP [PG’s head into the sand]

There’s this old joke that I really like:

One night a police officer sees an economist looking around a park bench near a light.
“What happened?” asks the police officer.
“I lost my keys but I’m having a really hard time finding them” replies the economist.
“Here, let me help” and they look for the keys awhile.
After not getting anywhere, the police officer asks, “where did you drop them?”
“Oh, replies the economist, way over there” and he gestures vaguely towards a nearby park, drenched in darkness.
“Well, then why on earth are we looking here?” asks the police officer.
“Because this is where the light is”

A powerful lesson. Sometimes we are so desperate for an answer we look for it in a very unlikely place and try to extrapolate back to the thing we want. Sometimes this works, but it can be devilishly hard. And it can also be stupidly useless.

Meanwhile, the one thing you can measure is dangerously misleading. The one thing we can track precisely is how well the startups in each batch do at fundraising after Demo Day. But we know that’s the wrong metric. There’s no correlation between the percentage of startups that raise money and the metric that does matter financially, whether that batch of startups contains a big winner or not.

…I don’t know what fraction of them currently raise more after Demo Day. I deliberately avoid calculating that number, because if you start measuring something you start optimizing it, and I know it’s the wrong thing to optimize.

That’s the inestimable Paul Graham. Perhaps economists should spend more time thinking about what they should and should not be measuring.

In a related discussion he says this:

The counter-intuitive nature of startup investing is a big part of what makes it so interesting to me. In most aspects of life, we are trained to avoid risk and only pursue “good ideas” (e.g. try to be a lawyer, not a rock star). With startups, I get to focus on things that are probably bad ideas, but possibly great ideas. It’s not for everyone, but for those of us who love chasing dreams, it can be a great adventure.

And we also get this interesting tidbit:

thaumaturgy: Off-topic, but something I’ve been chewing on lately: what’s it like to have your every written (or spoken!) word analyzed by a bunch of people? Esp. people that you end up having some form of contact with. It seems like it would be difficult to just have a public conversation about a topic. Do you think about that much when you write?

PG: It’s pretty grim. I think that’s one of the reasons I write fewer essays now. After I wrote this one, I had to go back and armor it by pre-empting anything I could imagine anyone willfully misunderstanding to use as a weapon in comment threads. The whole of footnote 1 is such armor for example. I essentially anticipated all the “No, what I said was” type comments I’d have had to make on HN and just included them in the essay. It’s a uniquely bad combination to both write essays and run a forum. It’s like having comments enabled on your blog whether you want them or not.

The Keys To Being Awesome

Step 2, which everyone goes on and on about (particularly when talking about Steve Jobs) is to never settle for anything less than awesome. If it isn’t great, personally insult the person that suggested it and send it back.

Step 1, though, is that you need to KNOW WHAT AWESOME IS:

Please, please, please spend time hanging out in the latest and greatest apps, regardless of their personal relevance or interest to you. If you do, your expectations of a “good experience” will be raised. Archaic team communication tools are often a good indication of what the decision makers believe qualifies as “good.” (Hint: it’s often a very low bar relative to what’s possible!)

Desire and drive are certainly precursors to success. But there’s a reason why awesome farms pop up only rarely. Awesomeness isn’t easy and unfortunately few people are exposed to greatness in a manner than teaches them to be great.

To the extent possible, expose yourself to awesome stuff. Otherwise, how do you know what awesome is?

The Angry Birds Era Is Over

I mean that in a commercial sense. The game will obviously live on.

Buying a game is a thing of the past because developers have figured out the revenue model that lets games be free.

Right now, 18 of the top 25 grossing of all apps are Free To Play Games (72%).  Also, it should be noted that 22 of the 25 top grossing apps are in the games category (88%), confirming the fact you need to be into games if you want to have the biggest potential payout.  The reason for this is people have a stronger emotional attachment to games than any other type of app, therefore they are more likely to spend money.

How are these Free to Play games crushing it?

After digging deeper in these top grossing apps, you can see they consist of nearly every free to play genre there is… Social games, click games, gambling games, turn based games, card games, etc but all of these have TWO things in common:  They each have lots of in app purchases and they encourage the user to buy stuff (a call to action).

This is the basics, but it’s SUPER IMPORTANT, here’s how:

A very small percentage of people buy stuff in games.  Of this small percentage you have people who will spend a LOT.

More here.

As many note on the HN discussion, this is really really annoying. But so are television commercials.

Hardware Fantasy Links (hey hey hey, keep it clean)

I am a big fan of computer programming but deep in my heart I’m a frustrated electrical engineer. I am captivated by the fundamentals of computing and hardware interaction.

Here are some things I’ve enjoyed.

Code (by Charles Petzold, published in 1999). This book winds up in all kinds of “best programming books” lists and what a revelation it is. Mostly it’s concerned with answering the question: “how would you build a computer with 19th-century technology?”. The rest is an extremely detailed look at what computer hardware actually DOES and how software interacts with it. Far more readable than it sounds.

Once you get through the basics of how computers work, Petzold machine-guns you with a quick explanation for just about every acronym, file format, compression technique and common technology in 1999. What is a bitmap? How do scanners work? What is an analog signal and how is it converted to digital? Where did MS-DOS come from? How do modems work? Just about every paragraph of the last 20 pages gave me an “ah-HA!” jolt.  I haven’t put a book down and wished for more in a while but an update on Internet technologies and perhaps a chapter on mobile hardware/software are surely in the works!

Programming Throwdown podcast – Specifically the ones on Assembly and C. I’m throwing C into the low-level programming boat because I can. Not that I really understand this link (yet?), but you can write linux device drivers with it!

Technometria (podcast). These guys are doing a series on the “Internet of Things”, discussing trends in hardware programming, specifically as it connects to the web.

Personal data ecosystem (podcast). This is an interesting series on ways that personal data is being collected and used. Some of it has to do with business models, much of it has to do with privacy, which is boring.

One interesting aspect of the Internet of Things phenomenon is that it is most closely associated with home automation but home automation as a business idea died a long time ago. Nobody will pay for it. People in this field are constantly trying to distance themselves from those applications.

The real advances in the Internet of Things are typically concerned with automating processes that already are fairly well automated, squeezing the last few drops of human input (cost) from things like building cars or monitoring traffic. The revolutions in these fields happened a long time ago

So the Internet of Things is a very 20th century pursuit. A 21st century engineering challenge would be about cracking the human to human economy (ie beating Turing tests). If you can make computerized social workers you’ll change the world.

What Is A Good Company? A Bad One?

In good organizations, people can focus on their work and have confidence that if they get their work done, good things will happen for both the company and them personally. It is a true pleasure to work in an organization such as this. Every person can wake up knowing that the work they do will be efficient, effective and make a difference both for the organization and themselves. These things make their jobs both motivating and fulfilling.

In a poor organization, on the other hand, people spend much of their time fighting organizational boundaries, infighting and broken processes. They are not even clear on what their jobs are, so there is no way to know if they are getting the job done or not. In the miracle case that they work ridiculous hours and get the job done, they have no idea what it means for the company or their careers…

That’s Ben Horowitz. There is also a discussion about a company called Go, which you’ve never heard of but are about to learn something from:

When I first met my friend Bill Campbell, he was chairman of Intuit, on the board of Apple and a mentor to many of the top CEOs in the industry, including Steve Jobs and Jeff Bezos. However, those things did not impress me nearly as much as his time running a company called GO Corporation. GO essentially attempted to build an iPhone in 1992. The company raised more money than almost any other venture capital back startup in history and lost nearly all of it before selling itself for nearly nothing to AT&T in 1994.

Now that probably doesn’t sound impressive. In fact, it probably sounds like a horrible failure. But I’d met tens of GO employees in my career, including great people like Mike Homer, Danny Shader, Frank Chen and Stratton Sclavous, and the amazing thing was that every GO employee that I’d ever met counted GO as one of the greatest work experiences of their lives. The best work experience ever despite the fact that their careers stood still, they made no money and they were front-page failures. GO was a good place to work.

My favorite test for whether a company is excellent company or not is whether the people who were a part of it go on to do extraordinary things. Think of the Paypal mafia.  It’s not clear to me that GO passes this test.

In the (re)insurance business, there are two Paypal mafias that come to mind: AIG’s actuarial department in the 80s and F&G Re. The top ranks of my business have over the last 20 years been massively over-represented by people with one of these two lines on their resume.

There is also an interesting discussion on HN about a rather controversial passage in the piece. Here’s the setup:

At Opsware I used to teach a management expectations course because I deeply believed in training. In it, I made it clear that I expected every manager to meet with her people on a regular basis. I even gave instructions on how to conduct a 1:1 meeting so there could be no excuses.

Then one day while I happily went about my job, it came to my attention that one of my managers hadn’t had a 1:1 with any of his employees in over six months.

Ben threatened to fire this manager and the manager’s boss if they didn’t fix this in 24 hours. A commenter thought that was harsh and perhaps a bit arbitrary. Another one responded with this:

It’s even worse than that, the people that work for you will make their number one priority not getting fired.

I’ve worked at a company like that before. Management worked hard on whatever problem the CEO noticed last, while doing their best to hide any other problems from him.
As a manager you do much better at aligning everyone’s interests so that your staff does what they want to do, which just happens to work towards the outcome you want. It’s more about gentle course corrections ahead of time than grabbing the wheel from them.

This is evocative to me of the hardest management problem in insurance. In insurance, like in all businesses, there is pressure for companies to grow. In insurance, also like in other businesses, growing by cutting your prices to the point where you lose money is one self-defeating option.

Unlike in other businesses, though, the break-even price for insurance is basically unknowable when you charge it. So you charge something that is probably close and work out differences across time.

This means insurance managers can be a schizophrenic bunch. One day they’re focused on growth, the next day they’re worried that they’re cutting their prices too much to grow profitably. The worst managers expose their employees to the full horror of this uncertainty. The best find a balance and help their subordinates find their own balance.

I’m not sure this criticism is justified in the story, but the lesson still stands: understand your management priorities and be consistent in applying them.

And one of those priorities is that your turf should be a good place to work.

Self-Driving Cars Approach? Doubt It.

Geekdom is a-flutter over Google’s self-driving car project.

Google announced a new phase of its self-driving car project Tuesday. The test vehicles, of which there are “about a dozen on the road at any given time,” have so far logged 300,000 miles of road testing without a single accident under computer control. In the next phase of testing, team members will start commuting to work solo, with the robot at the wheel.

Google also showed off a new vehicle type added to the program, the Lexus RX450h SUV. Now that the self-driving car software is comfortable in a variety of traffic conditions, the next phase will test snowy roads, temporary construction signals and other unusual terrain.

More here. Via MR under a very optimistic headline. An optimism I don’t share, unfortunately, but not because of the technology.

What I’m worried about is whether our society is genuinely capable of putting the most lethal weapon on earth in the hands of AI.

Remember that the auto liability insurance market is the largest in the world by an order of magnitude. This is so because everyone who can drive has the power to maim and destroy a lot of property and life around him/her. Auto insurance works because agents have control over their actions and are responsible for those consequences. Each person pays premium.

Who pays when Google’s driver hits a schoolbus full of children and sends it rolling down a cliff? What if Google’s driving algorithm isn’t at fault but a court pins the blame anyway? Remember Google’s car need never cause an accident for people to scream “Skynet!” and pull the plug.

Like with Kickstarter, Google’s car will only truly be tested when someone gets effed over. You tell me how long Kicktarter will last when someone commits genuine fraud and everyone’s confdience evaporates. Caveat Emptor? Yeah right.

It is our liability system (which mostly reflects an underlying extreme risk aversion) that will probably kill these technologies.