I’m not the first person to say that quality is a journey, not a destination.

Viewing that old adage through my Data Head lens, I’ve concluded that individuals and organizations use data differently as they travel the quality journey. Actually, I’m convinced that the use of data on quality journey is a developmental process.  I’ve long been fascinated with human mental and emotional development models(1), so it is no surprise that I’ve come up with my own developmental model for the use of data on quality journey. The three stages are Guard, Guide, and Gain.

One thing to remember about developmental models: each stage builds on previous stages, and you have to master one stage before you move to the next. You can get stuck at one stage and never move out of it. My observation is that forty years after American manufacturing discovered Dr. Deming, many leaders are still stuck in what I call Stage 1: Guard.

Stage 1: Guard – Protect the customer and your brand

In Stage 1: Guard, your primary concern is protecting the customer and your brand from mistakes and problems. You’re probably already doing this work, or you wouldn’t be in business. It is a fundamental competency that every manufacturing company has to master.(2)

In the Guard stage, you collect data so you don’t ship crap, and to protect yourself if the customer thinks you are shipping crap. More than one quality manager has told me, “Yeah, the great thing about this system is that when the customer calls with a complaint, in a couple of minutes I can snow him with enough data to convince him that he shouldn’t be bugging me.”

When I hear that, it is a clear indicator that they’re operating at Stage 1.

There is nothing wrong with protecting the customer and your brand. It is a necessary part of the journey.

Automating Stage 1 with software like GainSeeker makes sense. Collecting and managing all that data manually is labor-intensive and expensive. Worse, once you have the data, it is usually buried in a file cabinet where it is impossible to get to. Generating reports or investigating customer complaints takes forever. The knowledge embedded in that data is out of sight and out of mind.

GainSeeker can automate this process, making it fast and easy. You can do more with less, and free up your people to do value-added work. After all, inspecting and recording data is not value-added activity.

But even more importantly, GainSeeker makes the data available in real-time. You’ll be able to respond faster and minimize the problems that you find. You’ll have all that data in a central repository so that you can easily generate Certificates of Analysis, or retrieve data if you need to respond to a customer complaint or recall.

Stage 1 usually yields Scooter Margins

In Stage 1, we typically see customers pay for the software in 18 – 24 months, what we call “Scooter Margins.” This is because most of the benefit is measured in reference to time savings due to automation. This is no small savings, but it falls short of the great benefits that we see customers getting when they get to Stage 2: Guide and Stage 3: Gain. More on those stages in upcoming posts.

In the meantime, what successes have you had with Stage 1: Guard? Do you have areas that are still at risk? Is Stage 1: Guard optimized with automation, or are their opportunities to reduce costs through automation? Add your comment below, or write to me at ejmiller [at] hertzler [dot] com. I’d love to hear from you.

 

(1) My mother was a fourth grade teacher, and she couldn’t stop talking about Piaget and his model for childhood development. Then as an undergrad, I ran into Kohlberg’s Stages of Moral Development. There have been others in between, but perhaps the most interesting recent work is Ken Wilber‘s Integral Theory, a popularization of Spiral Dynamics.

(2) Albeit to different degrees – the maker of those little plastic stands that go inside pizza boxes to keep the cardboard from collapsing on the pizza don’t have be nearly as concerned about protecting the customer from their mistakes as, say, the manufacturer of turbine blades in a jet engine or automobile brake pistons.