The Data Heads

Quality Magazine picked up my blog post on the Voice of the Process loop. I’m really interested in your comments on the questions posed in the post, either at the Quality Mag site, or here.

I mentioned in yesterday’s post announcing the release of GainSeeker Suite Version 8 that I have been working on a case study about the new report writer.

You can read the case study here, and download a PDF version to share with others.

A little bit of the back story:

This project came about during a training class we held for Valeo (the subject of the case study) early in the new year. During the class, Stacey (who is quoted extensively in the case study) made the comment “You’ll never find a kid who wants to grow up to be a data jockey.”  What a great comment.

Mel (the guy from our staff doing the training) was intrigued and scratched away at it. What did he mean by data jockey? Why had he become a data jockey? Who cared about the results of his data jockey work? What difference would it make if we could eliminate the data jockey work? What would it take to eliminate the work?

At the time, Version 8 hadn’t been released, and Mel had had only minimal exposure to the power of the new Dynamic Reports module. He came back and started asking his colleagues “So this is what they really want. Could Dynamic Reports handle it?” Dale, one of our senior developers whom I sometimes call Obi-Wan Kenobi, put together a prototype and we were off to the races.

In manufacturing circles it not at all uncommon to talk about “The hidden factory.” The hidden factory is rework. Another case study about our customer Titleist includes this analogy from the rubber and plastics industry:

Another benefit of reduced scrap is that equipment is freed to do productive work. A shop with a 5 percent scrap rate and 20 molding machines has one machine dedicated to making scrap. Using real-time production data to eliminate scrap is the equivalent of buying a new machine.

Working as a Data Jockey is a hidden factory in our offices. Like a machine producing scrap, it is not value added. Eliminating the data shuffle – freeing the data jockey – pays huge benefits to your organization. The case study outlines some of them.

What about you? What is your experience as a Data Jockey? What have you done to eliminate this hidden factory in your office? Use the ShareThis button below to mark this page, leave a comment, tweet me, schedule a conversation, or call 800-958-2709.

For the last 18 months we’ve been working on the latest release of GainSeeker Suite, Version 8. We released it last week and you can read all about it here.

I can’t decide which is the coolest feature in the release: the new Dynamic Reports module or .Launch.

In beta testing, Dynamic Reports has proven to be very powerful and very cool.  Every time somebody has come up with a request for some special report I think “No way. That’s just too much to hope for…”

Then someone digs into it a little bit and the next thing I know we have a working solution that goes beyond my wildest imagination. I’ll be publishing a case study in the next few days to show you what I mean.

But .Launch (“dot launch”) … what a little sweetheart of an application. There aren’t any fancy stats or charts, and it doesn’t integrate with your ERP system. But it puts a really nice UI on all the command line parameters that our geeks have built into system that nobody has time to figure out. If you want to launch a specific desktop in Charts & Reports, with a specific user name (and not have to type in the password everytime), .Launch can take care of it. Plus you can launch any other application on your system and organize all of them in Groups.

I’ll be using .Launch to organize presentations. In my world, I’m often flipping between a PowerPoint slide show (maybe two or three different files), and Excel spreadsheet, and several GainSeeker Suite modules. .Launch gives me a single place to drop all those shortcuts. It significantly unclutters my desktop.

So for raw power, I vote for Dynamic Reports. But for the module that I’ll be using on a daily basis to make life more convenient, it’s .Launch all the way.

We put together a micro-site on GainSeeker Suite V8. Take a look and let us know which features you’re most happy to see added. Use the ShareThis button below to mark this page, leave a comment, tweet me, schedule a conversation, or call 800-958-2709.

In a recent post I described the difference between the Voice of the Customer (VOC) and the Voice of the Process (VOP). I used a simple Input => Process => Output diagram to explain that both the VOC and VOP have an important role in evaluating our systems and processes. I said that it isn’t a case of one being right and the other wrong, or one being better or worse than the other. Both approaches have their place. But they are different.

It seems to me that the biggest issue comes when we confuse the two approaches.

I suspect someone is confusing the two approaches when they point to a control chart with subgrouped data plotted on it and say something like:

“When I see a point out near our limits then I know we’re getting close to going out of spec.”

On the surface this seems like a reasonable thing to say. And it must be reasonable because I hear it so often. So why do I get all worked up when I hear it?

(Because I do get worked up. I have a hard time not jumping up and down and raising my voice. )

“When I see a point out near our limits…”

The issue is that the point is the average of the data in a subgroup.

Lets look at a picture:

We’re looking at three subgroups of data.

What is your vote?
Specs are 25 plus or minus 5, we have no problem, right?
Specs are 25 plus or minus 1, we should worry, right?

Here is the actual data:
Sample A: 24.9, 25.0, 25.1
Sample B: 20.0, 25.0, 30.0
Sample C: 20.0, 20.5, 33.0

And here is what it looks like plotted on the same run chart:

Plotting subgroup averages on an X-Bar chart and then comparing those average points against the specifications is misleading. You’re blurring the use of VOC and VOP. Don’t stop using either loop – but don’t try to use them at the same time.

Have you ever seen the VOC and VOP loops confused? What issues has it raised for you? Use the ShareThis button below to mark this page, leave a comment, tweet me, schedule a conversation, or call 800-958-2709.