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I’ve moved!

May 30, 2011

You can see the new improved version at–check out The Half-Life of Data.

Systems: a prescription

March 23, 2011

NOTE: You may only read this if you are trying to understand a current system, design a new system, or implement a system change, or have done so in the past. Because only you will believe this:

Systems thinking is an art, not a science.

But just as Wolfgang Mozart had to start by learning to squeak out a song on his father’s violin, you must learn a few basics.

1) Start with the scope

Success is defined by the beholder [1], not by you. It is critical, then, to identify what constitutes measurable success, and get the stakeholders to agree to it–especially the ones that hold the pursestrings.  The first part of this is identifying the system boundaries.–a surprisingly hard task. Think about what you have the ability to influence or change–those you do not probably belong outside of your system.

2) Model the system

If you can’t explain the system in 5 minutes, either you don’t understand it, or it doesn’t work [2]. Modeling the system, whether using software tools like Microsoft Visio or just a whiteboard and markers, helps you understand the system. Many frameworks are available, each with their list of pros and cons. For sophisticated analysis, use UML or one of its variants; for simple analysis, use a standard workflow. This can seem daunting, but it really isn’t. You’ve already identified what isn’t in the system, so all that’s left is to classify what is in the system. In many business systems, it helps to think about money, as it is a data flow that everybody understands. Where does money come into the system? Where does money leave the system? How are the inflows and outflows triggered?

Often this step is blown out of proportion compared to its usefulness. The main purpose of a model is to provide a layer of abstraction so that you and others have a better understanding of the system. It should not be an end result, but rather a step in a process. Beware of overly complex models–and remember that the complexity of the model should always be less then the complexity of the system. (This is where some of the readers are saying “Duh!” and slapping their foreheads)

3) Simplify the system

The easiest way to get good results is by making things more elegant. Pick areas in your model that look complex or daunting. Make them less so through brainstorming, through conversation, through interviews, or through insight. Beware of second system syndrome, where a successful system designer or leader ends up bloating his second with all the features and do-dads he always wished he had had time to put in the first.

Also trust your gut–if it doesn’t look right, try again.

4) Implement the system

Implementing the system is the best way to get it right. Despite all your best efforts, you will likely screw something up–a button won’t work, a scripted answer will sound corny, a critical component will be installed upside down. The quickest way to find this out is to get it in front of as many eyes as possible as soon as possible. Don’t overdo it by pushing out large failure after large failure,  but neither should you plan for so long that your system is obsolete by the time you’re ready to ship it.

5) Remodel the system

This may sound like unnecessary work, and it is–if you’re perfect. But you aren’t, so do it–now that you’ve spent the time to introduce the system to the critical world around you, map it out again. This time use even less detail–remember, modeling is a tool to help you with your understanding of the system.

6) Tweak and repeat step 4 and 5

Certain situations require more planning than others, but for most a “Ready, Fire, Aim fire aim fireaimfireaim…”  mentality will get you further, faster, and with better quality than spending too much time planning. Unless you are designing a nuclear bomb, or handling the medical records of 300 million people, test your system as publicly as politically possible. You may not be able to rescue your honor, but you will be able to get a better system.

Final note: That which is measured, improves. Be careful what you measure in any system. If you measure how many leads a salesman is gathering, he will gather thousands of garbage leads. If you are measuring how fast a project is finished, you’ll have a non-working project tomorrow.


[1] Rechtin, E Systems Architecting: Creating & Building Complex Systems, 1991
[2] Darcy McGinn, 1992 from David Jones

The price of data

March 8, 2011

There seems to be a standard belief that keeping data is free. And I’m not talking about the so-called “big data” such as Google’s web caching activities, Walmart’s RFID warehousing activities, or NASA’s meteorological and astronomical surveys. I’m talking about  keeping old, poorly named excel files. Or a database of leads from 1995. Or unread email in your inbox. Or a gob of unfiled receipts on your desk. I’m talking about signing up for blog feeds you never read. Or newsletters to organizations that you’ve never actually attended. Or an subscription that you never catch up on. I’m talking about categorizing and itemizing and tracking every part and piece and component of everything in your life, only to stick it, unused, in the files with the previous year’s records. I’m talking about the old phone number for your best friend that you KNOW isn’t correct, but you can’t bring yourself to erase.

Data is not free. Clutter costs head space.

I’ve worked in many organizations that had a shared file system. The standard MO is this: everybody dumps their files in shared folder. At some point, users can’t find the stuff they dumped there, so they create a folder of their own (“John’s folder”) and instruct other people to never touch it unless asked. Soon everybody and every department has a folder. Some people have one folder under their department’s folder, and another one under in the main folder. Soon somebody get’s sick of it, and reorganizes it themselves (making everybody mad) or calls a general meeting in which everybody disagrees about the correct way to organize it.

Customer Relationship Management (CRM) programs are some of the worst offenders. Each contact (or company, or lead)  in the program represents a possible or past sale. Which means that everybody is valuable, right? Nope! If you can’t find them, what good are they? Databases of leads that are 10 years old are worse then useless–if they weren’t there, you wouldn’t have to spend a second thinking about them. But since they are there, and there might be a spec of gold you could sift out, you keep them.

Data storage is nearly free–you can get massive amounts of storage for very little money. And this compounds the issue. “I might want to look at those pictures sometime.” “I really don’t know if I’ll ever listen to those audio books, but I’ll keep them in my library just in case.” “So what if we lost the prospect? Let’s hold on to the proposal files. We might need em’ again someday.” And none of this is bad–if well organized.

Don’t fall into the trap of associating data with value. Organized data can be valuable, if relevant. Data on its own is not.

You know the packrat whose garage is so full of stuff that you can’t walk in? I’ll let you in on a secret–the technology revolution has enabled thousands, tens of thousands, of secret packrats. People who keep their desk clean, but their computer desktop cluttered. Deleting old information is surprisingly liberating. Try it. You’ll like it.


January 31, 2011

Warning: Wikipedia rehash alert: the following post relies heavily on this article.

The QWERTY keyboard was invented in 1873 by Christopher Latham Sholes for his typewriter, which subsequently sold to Remington. Sholes developed the layout into a similar design as is common today, through a series of renditions that were aided by an acquaintance’s work on letter-pair frequencies. Though other alternatives were available, Sholes found that to avoid physical clashes in the works of the machine, he could space the commonly used letters far apart. Further, he spaced the rows of keys so one was not directly over another for the same reason. Remington made QWERTY popular with the commercial success of their Remington 2 (the first typewriter with a shift key) sold first in 1878. Typists quickly became so familiar with the layout that competitors had to follow suit to sell their product.

Today, 137 years after its introduction, I am typing this blog post on an iPhone’s QWERTY keyboard, complete with the upper row staggered from the middle. Even though I am using two thumbs to type, I find it comfortable and natural to find the keys in their “proper” positions.

For many years I have gone through Dvorak phases, where I’ll attempt to teach myself to use the keyboard invented by Dr. August Dvorak. The Dvorak layout has led to new speed typing records, lower cases of repetitive stress syndrome and carpal tunnel, and in some circles, no doubt, a cure for cancer. With a Dvorak keyboard, 70% of the keystrokes used in typing (such as vowels) are kept within the home row, or that row that your fingers rest on naturally. With the QWERTY, it drops to 32%. Further, far fewer words are typed with only one hand on the Dvorak, which increases normal typing speed. So why don’t we all use Dvorak?

A personal note–I’ve never broken 17 words per minute on the Dvorak, which even my 80-year-old grandma would be ashamed of. The finger-moving part of my brain doesn’t like it when I try to keep my fingers on the home row for so much of the time. And the rational, logical (and some say greedy) part of my brain tells me to learn it in the alleged “spare time” that some claim to have, and to just get on with my work.

But the fact that a bad system is implicitly accepted by all the keyboard manufacturers, operating system developers, and elementary school typing teachers makes me take pause. Even though as far back as 1873 there existed other ways to type, still the QWERTY has persevered.

Successful systems and standards follow a normal life cycle: introduction, acceptance, dependency, stagnation, and replacement. Due to a host of human factors, a system as seemingly simple as a keyboard to a system as complex as a space shuttle seem to follow these steps. In the case of QWERTY, the network effect (the exponential reinforcement of ever larger groups of people) made users dependent on the standard early on. Since then, the same network effect has held even relatively innovative companies hostage–witnessed by the loud debate not on the layout of the keys, but whether the familiar layout is better as a soft keyboard or a tactile one.

We have long since entered the stagnation phase of our keyboards. And we are just now entering the long and drawn out replacement phase, driven by dedicated individuals and new technology.

What systems do you find yourself dependent to? Why? When, do you suppose, is it better to ignore the others and make your own standards? When is “good enough” holding you back?

2010 in review

January 3, 2011

The stats helper monkeys at mulled over how this blog did in 2010, and here’s a high level summary of its overall blog health:

Healthy blog!

The Blog-Health-o-Meter™ reads Wow.

Crunchy numbers

Featured image

A helper monkey made this abstract painting, inspired by your stats.

A Boeing 747-400 passenger jet can hold 416 passengers. This blog was viewed about 2,100 times in 2010. That’s about 5 full 747s.


In 2010, there were 19 new posts, not bad for the first year! There were 4 pictures uploaded, taking up a total of 57kb.

The busiest day of the year was October 30th with 156 views. The most popular post that day was Success is in the eye of the beholder.

Where did they come from?

The top referring sites in 2010 were,, Google Reader,, and

Some visitors came searching, mostly for silvertrek systems, silvertrek battle ground, michael on systems wordpress silvertrek systems, and silvertrek systems 98604.

Attractions in 2010

These are the posts and pages that got the most views in 2010.


Success is in the eye of the beholder October 2010


When do you quit? July 2010


Where are your people at? November 2010


Details September 2010


Quote August 2010

Federal express measures how fast every package gets from every shipper to every receiver. McDonalds measures how fast every customer receives their Big Mac and Coke. Disney measures how long
every guest stands in each line at Disneyland. And most small businesses don’t know if they were profitable until just before April 15th, proclaimed National IRS Day. Are they lazy? Nope. Stupid? Rarely. Can’t use computers? Maybe, but it shouldn’t matter. They have no system.

Fritjof Capra wrote that a system is an integrated whole whose properties cannot be reduced to those of its parts. Without a system, the individual players act randomly, coming into contact with one another by chance, and reactively responding to each other. The companies mentioned above are able to measure their businesses only because they have a repeating, dependable system in place. FedEx loses packages. McDonald’s employees are often uninspired, plodding sullenly through their task serving 38-second french fries. Of 40-ish total rides, the average Disneyland rider manages 10 per day, due to obscenely long lines. All, in some eyes, have a bad system. But they have a system against which they can measure, allowing them to make positive change.

In the absence of a system, you could only make component-level changes and hope for the best. You could use your gut to understand an employee’s performance and replace or promote on that measure. But the success of your change could again be measured only on gut feel. It is therefore better to make a system sooner and changes later. Measure first and change second. And, of course, have a system for measurement and a system for change. Do not be afraid of mistakes. And do not be afraid of change.

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