Individual and Team Learning

If product development is about learning, then there must be at least two kinds of learning going on: individual learning and team learning. By their very nature, individuals and teams must learn in different ways, so our product development and management processes need to support both kinds of learning. I will lay the groundwork for future posts by looking at how people and teams learn and what sort of behaviors they engage in as part of the learning process. Learning and behavior are open fields of research, with volumes of published material. I will be brief.

Nancy Leveson, in her book Safeware: System Safety and Computers, has a couple of excellent chapters on human learning and behavior, from which I’ll borrow. I recommend her book; the first ten chapters or so are well worth reading even if you’re not involved with computers. Borrowing from Jens Rasmussen, she discusses three levels of cognitive control: skill-based behavior; rule-based behavior; and knowledge-based behavior.

Knowledge-based behavior sits at the highest level of cognitive learning and control. Performance is controlled by explicit goals and actions are formulated through a conscious analysis of the environment and subsequent planning. One of the primary learning tools used at this level is the scientific method of hypothesis formulation, experimentation and evaluation.

Rule-based behavior develops when the environment is familiar and fairly unchanging. Situations are controlled through the application of heuristics, or rules, that are acquired through training and experience, and that are triggered by conditions or indicators of normal events or states. This sort of behavior is very efficient, and learning is achieved primarily through experimentation, or trial and error, that leads to further refinement of the rules and improved identification of conditions under which to apply those rules. People transition back to knowledge-based behavior when the environment changes in unexpected ways, but only as they become aware that the rules-based behaviors are failing to produce the usual results.

Skill-based behavior “is characterized by almost unconscious performance of routine tasks, such as driving a car on a familiar road.” The behavior requires a trade-off, often between speed and accuracy, and learning involves constant tests of the limits of that trade-off. These tests are experimental in nature, but largely sub-conscious (not planned). Only by occasionally crossing the limits (making “mistakes”) can learning be achieved. As with rule-based behavior, people transition from skill-based behavior to rules-based behavior only after they become aware of a change in the environment that is having a negative impact on outcomes of the skill-based behavior.

When people learn new skills they typically progress from knowledge-based behaviors to rule-based behaviors and eventually to skill-based behaviors. A surprising amount of engineering is based on heuristics rather than knowledge. This is often a good thing, as it allows us to efficiently deal with very complex problems and systems, making it possible to arrive at approximately-correct solutions much faster than through more explicit planning and evaluation. It can also go badly wrong when signs incorrectly lead one to apply the wrong rules to a situation that appears familiar but is not.

What might not be obvious is that learning at any level is only possible through a mix of successful and non-successful experiments. Unexpected outcomes (“mistakes,” “errors” or “failures”) are a necessary part of learning. In fact, the rate of learning is maximized (learning is most efficient) when the rate of unexpected outcomes is 50%.

Teams learn when individuals communicate, sharing and synthesizing the knowledge and heuristics that they’ve learned. This occurs primarily through two behaviors or tools: assessment and feedback. Assessment involves observation and reflection on what behaviors are working or not working in pursuit of the team goals. It should be performed by both by individuals and by the team as a whole. Feedback is comprised of constructive observations provided by others and objective measurements, and is the input to assessment. Because feedback and assessment are so important to team learning and growth, they should be planned, structured and ongoing.

For assessment to be effective at generating team learning and growth, some action needs to follow. An action might be to change an existing condition (e.g. change how meetings are run, explore design alternatives, etc.), or to document a process or norm that “works” and sharing the result with team members (e.g. documenting the work flow, standardizing parts, implementing decision processes, etc.).

Repeated and effective use of both individual and team learning behaviors results in team learning cycles. In any product development project, these learning cycles occur in different domains simultaneously. The main forms of feedback in product design are testing and design review, and there are multiple ways to assess and plan those feedback loops. Project feedback comes primarily from monitoring the schedule performance. At the same time, the team should be eliciting feedback about its ability to make decisions, work together and work with the rest of the organization, and assessing that feedback.

Peter Scholtes’ The Team Handbook is a well-written and practical guide to implementing team processes and behaviors, and is geared toward both team members and team leaders. It’s the kind of book that a new team could refer to throughout a project to guide them in becoming more cohesive and effective. His The Leader’s Handbook: Making Things Happen, Getting Things Done also provides an excellent supplement, geared more toward team leaders and business managers.

To summarize, product development processes and organizations must be designed to support repeated structured and “accidental” experimentation by individuals and team processes of feedback, assessment, decision-making and actions that result in either change or standardization.

Waste in TPS vs. Lean PD

The Toyota Production System (TPS), or Lean, is widely considered a remarkable and effective system for improving operations. People naturally try to apply the same system to other product streams and other activities. However, I have found that people often struggle with the correct application of the concepts, especially to product development. For instance, Glen Reynolds, an experienced project manager, is working to understand Agile, and has recently come across the statement by some Agile advocates that “testing is a waste.” Calling testing a waste, as a general statement, is nonsense, and Glen is engaged in some excellent discussion on the subject.

I have encountered a fair number of people with experience in product development, and a fair number with experience in Lean manufacturing, but few people with sufficient overlap in the two domains to combine them. The TPS is very formulaic, laying out clear rules or guidelines that are easily followed. Unfortunately, product development is sufficiently different from manufacturing that the TPS cannot be applied directly.

The TPS defines waste as any activity (or inactivity) that does not add value to the product. Value is defined from the customer’s perspective as any activity that the customer is willing to pay for as a part of the product. Assembling the product adds value; holding the product in inventory does not. Shipping product in exchange for payment adds value; the time spent processing that payment through Accounting does not.

Testing is used in manufacturing to detect defects. The customer is willing to pay for a correctly-manufactured product; not for the rejects. From this perspective, testing is a waste, because it does nothing to add value to the product. In fact, all of product development should be considered waste, because product development does not produce any product (unless, of course, your product happens to be product designs for others to manufacture, as with Ideo).

However, in product development, testing can add value. In fact, testing is probably the only way to maximize value creation in product development.

Manufacturing is a highly repetitive activity, which takes as its input a product and process design and tooling, and produces as its output a physical product. The physical product generates revenue. Ideally, the product is manufactured exactly to specification, and there are no activities required that do not lead directly to the manufacture of the product. There is no uncertainty as to what the output should be. Waste, then, is any deviation from this ideal state. Economically, the assumption is that the product is designed to maximize revenue generation, and the process is designed to correctly manufacture the product. Since nothing is perfect, the TPS seeks to improve profit by eliminating or minimizing those activities that do not generate revenue.

In contrast, product development is a highly variable activity, with variable inputs. The goal of product development is not simply to produce product designs according to some predefined specification. If it was, then product development would be a simple exercise in transforming specifications into conforming drawings. In fact, product development operates under a high degree of uncertainty; from the start of the project, the desired outcome is not fully known. In order to overcome this uncertainty, product developers have to learn. They have to learn about the customer—the end user—and about the technology that they are working with. Value is created as the uncertainties are resolved. The goal of product development is to maximize the rate of learning, thereby maximizing the rate of value creation.

The best way to learn is through trial and error, following the scientific method of hypothesis testing. So testing not a waste if it generates new knowledge. Testing that does not generate new knowledge is a waste. If you generate data that you already had, you’re generating waste. If you generate data that you don’t use, you’re generating waste. If the organization learns something, then you’ve created value.

Notice that this definition of product development follows the same principle that is used in the TPS: do what creates (or produces) value; eliminate or minimize everything else. The details change in the presence of uncertainty about the desired outcome.

We can take this a step further, to develop a more sophisticated approach to managing product development projects, if we understand the economics of our project. The uncertainty that is reduced through testing is all technical risk that the product will not meet the market’s requirements. This means that testing translates into increased sales volumes. Testing in product development adds time, which means a later entry into the market and possibly reduced sales volumes. If we have some estimate of what the cost of delay and the cost of risk are, we can then perform a cost-benefit analysis on the proposed testing to determine whether or not it results in a net creation of value.

Such economic models do not have to be complex, and they do not have to be highly accurate. They need to be just accurate enough that they do not lead to very bad decisions and they must be usable. This suggests, as Reinertsen has advocated, that new product development projects should develop economic models as early as possible and derive decision rules that project managers and lead engineers can use on a daily basis.