Most engineers like structure, process, and standardized forms; especially as a way of applying order when situations seem to be losing theirs. It is this element of standardization that many find appealing — confidence and comfort amid familiarity. Some people also like “one-size-fits-all” tools but they are not always happy with the fit.
When we first learned and implemented six sigma in Goodyear’s R&D function, I tried to awkwardly force the Define, Measure, Analyze, Improve, Control (DMAIC) process onto any problem I confronted. I see the same thing happening today with the use of A3s, leaving many dissatisfied and abandoning the problem-solving approach. Many people at Goodyear walked away from the DMAIC process, pointing out the waste and misdirection of trying to put every problem on a common DMAIC denominator, and then fell into the same frustrating habits of forcing A3s.
Not every tool is a hammer, and not every problem is a nail. Not every situation warrants the use of an A3.
I learned about A3 thinking and how to complete an A3 by reading John Shook’s Managing to Learn. I think most people familiar with A3s understand the technical process as well as we do, but they still fail to use them effectively. For insights on when and why to use an A3, we looked to the Cynefin framework presented by Dave Snowden and Mary Boone. The two scholars write in A Leader’s Framework for Decision Making, “Good leadership is not a one-size-fits-all proposition.” The same can be said for the use of A3s.
Cynefin basically consists of four cause-and-effect domains that leaders confront and must resolve, each requiring a different type of response. I find the four domains also give direction for when to pull out an A3:
- Simple: Decisions are based on best practices, standards, and repeating patterns. An A3 would be a tireless overworking of the problem. “Just do it” is the action in most of these cases, for which answers are already known: standardized work, ethical morals, family values, athletic techniques, etc.
- Complicated: This is the realm of the known unknowns. Decisions are based on clear cause-and-effect relationships and expert knowledge, and there can be more than one right answer. You don’t need an A3 to explore these complicated problems and solutions: mathematical relationships in R&D, geologists plotting drilling locations, material scientists developing a new rubber formulations, etc.
- Complex: This is the realm of unknown unknowns. Decisions may not yield a single right answer, and things can only be understood in retrospect. Here experimentation is necessary and solutions emerge from the investigative process. The A3 leads one through the process of investigation and experimentation, sets the threshold for an acceptable outcome (the goal), and establishes the actions to get there. You may find, as is often the case in R&D, that one complex problem requires the development of multiple A3s. A leadership temptation with complex problems is to impose order, which often leads to a simple solution that rarely solves the real problem. An A3 forces problem solvers to rigorously explore many potential causes of complex problems: inadequate lab turnaround times, an unexpected consumer response to a new product launch, a sudden drop in customer retention, etc.
- Chaotic: You cannot A3 your way out of chaos. Decisions and actions are intended to reestablish some sense of order and security amid high turbulence and high tension. In business this is comparable to responsive troubleshooting. Quickly stop the conditions for chaos, and then apply the right tools to the simple, complicated, or complex issues behind it. No individual or group can solve chaos, but they can respond and prevent the escalation of chaos: a fire in a manufacturing plant, a terrorist attack, aftermath of a natural disaster, economic collapse, etc.
The A3 process – or the more general process used by Goodyear that I describe in Lean-Driven Innovation – is highly flexible (maybe too flexible), and I could probably squeeze any problem onto an A3 if I put my mind to it. But why would I? Think about the problem domain before you pull out the paper or at least when starting the A3. Based on my A3 coaching experience, struggling with the left side of the A3 (problem background, current condition, and goal) is a clue that the problem is simple or complicated and not really complex and applicable to an A3.
Like most companies, we had some early challenges using A3s, but today A3s are widespread in Goodyear product development and elsewhere. We teach the process and coach engineers, who apply the process to solve real problems, much as Sanderson coached Porter in Managing to Learn. Our engineers use A3s daily, such as when formulating a complex product development iteration (learning cycle); the experiment is run, and the results are documented on the A3.
Our A3s are simple and kept to a single sheet of paper or a whiteboard. I often get requests for our “A3 form,” and I encourage people to find and develop their own. I also tell them to use Shook’s work to guide them through the technical steps, and Snowden and Boone’s to understand when to pull it out. I would strongly advise you to do the same.
