How to Find Gun Owners Fast

This is a wonderful piece by Jeanne Marie Laskas, writing for GQ magazine. It’s about a strange little federal agency in the US that runs traces on guns that are associated with a crime, trying to figure out who bought it. It’s long, but well worth reading in it’s entirety. There’s a few parts worth highlighting and looking into a little further. Let’s start with the results:

 Despite no increase in budget, no new technology, no new staff: “I’m doing twice as many guns, twice as fast, and almost twice as accurately as we did when I got here in 2005.”

There are plenty who may think this is sorcery, or even enabled by some hidden computerised system (which are verboten, thanks to the paranoia of the gun lobby). It’s actually quite simple though. If you look at most end-to-end processes for delivering value in organisations you typically find something that looks like this:

Value Stream Map for a change for which the Cost of Delay was $200,000 per week. (Maersk Line)

It doesn’t take a huge amount of insight to spot the problem here. Almost all of the waiting time is caused by queues in the system.

Understanding this doesn’t require a man – or a human computer.

Here’s the part where I get a bit angry.

The writer does a wonderful job of drawing you into the story and making you care about the people. It’s an easy read and the character development of Charlie Houser, in particular, is compelling. Charlie is a federal agent who came to the agency in 2005 and seems to have led the transformation of the way the work works. It’s a shame though, that she does a hack job of explaining how the results were actually achieved.

There’s a passing mention of ISO9000 and Six Sigma, sounds kinda scary. Then there’s a wonderful part in which Charlie does his best to convey just how easy it is to learn this stuff. No need to go to some fancy university. No machine learning or any (shudder) computer programming involved. It came out of a book. From a book store.

“I just found it at Barnes & Noble,” he says, in a tone suggesting that this shit is basic.

What the writer is implying here is that this isn’t basic. That Charlie has some special gift. That Charlie is actually a genius (despite him attempting to explain how accessible this is).

Now, I get it – people might be turned off if you attempt to explain even the basics of queueing theory to them. There’s a good chance they’ll get lost and stop reading. But to ascribe the genius to a man (surrounded by a bunch of “ladies”) is just sloppy. Would it have been so hard to do a bit more homework?

Instead, we get one sentence about the rate at which gun descriptions can be typed up, in which Charlie proves that he (or was it one of the “ladies”?) can operate a stopwatch and do basic division. Charlie goes on to compare one queue with three servers vs three queues with one server each. Before we get to the point:

“There’s a whole science of mathematics behind queuing theory. So what we did was, I sat around trying to figure out what would be the best way to queue the traces up and punch them through….

“Let’s say yours is one hour, 60 minutes. Yours is one minute, yours is one minute, and yours is one minute, right? One minute, one minute, one minute, one minute…one, two, three minutes…”

In these moments, I realize that during his tenure here at the tracing center, and faced with the obstacle of no computerized search technology, Charlie went ahead and turned himself into the computer.

No. Charlie did not turn himself into a computer. He learned a bit about statistics and queuing theory. Then they did some analysis of the demand and designed and implemented a better system. The new system sounds like it was focusing on shortening cycle time, constraining the amount of work in process and managing queues better. It may be counterintuitive, but it is not voodoo. And Charlie did not “turn himself into a computer”.

Getting to More, better, Faster

From the scant details provided, the algorithm sounds similar to CD3 – Cost of Delay Divided by Duration. We hear a few stories of traces that were categorised as highly valuable and highly urgent: San Bernardino, Boston Marathon – basically anything that would feature as “breaking news” in the media is probably one of the “Very High Cost of Delay” traces, for which they probably drop other work, to punch these Black Swans through as quickly as possible. For other lower Cost of Delay traces, they’re clearly also taking into account an estimated Duration in working out an optimum order to process requests:

“…So now it’s 69, 72 minutes, divide by 4…4 goes into that once…32, 80…My turnaround time just became 18 minutes! I just shuffled you around in a different order. Average turnaround time. Right?”

It doesn’t matter if I follow; he’s so happy about all this I want to clap. For five years Charlie took it upon himself to create a new workflow system for the tracing center, breaking down each step in the tracing process into equations, doing time-motion studies for actions as minute as how long on average it takes the ladies to go from their desks to the roll room. Every step was analyzed and rethought, the numbers crunched.

 Yes, it really does matter if you don’t follow! You owe it to us, your readers, to do a better job of explaining how, with the same budget, this team of people manage to do twice as much, twice as fast and with half the number of errors as before. It’s not magic. And ascribing this result to the innate genius of Charlie, the “human computer” is just plain wrong. It’s available to everyone, if they care to know.
I know this because we published quite similar results applying the very same understanding of queueing theory in using CD3 at Maersk Line. They halved their cycle time, increased their throughput by more than 20% and reduced errors by over 80%). We didn’t do that because I, or any of my team, is a human computer, at all.
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Yes, contrary to what you may have been told, or believe, this “shit” really is quite basic.
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