Table of Contents:
Law of Diminishing Returns
Before we move through the things that can help, a review of the law of diminishing returns is in order. The law of diminishing returns will first require we talk about marginal or increment of some variable. Let’s say we have a field of wheat and we have no automated equipment, so the field needs to be harvested manually. We gather up our friends and commence harvesting and we average 10 bushels of wheat per person, per day. We add one more person to our harvesting team, and we again see that the amount we are harvesting per day is 10 bushels of wheat per person per day. That additional person is an increment, and that increment of labor was still able to harvest 10 bushels of wheat. With the need to get the fields harvested, we get one more person to help work the field, and at the end of the day we then have an average of 8 bushels of wheat per person per day. This incremental addition of labor does not yield the same results as the previous increments. This is a demonstration of the law of diminishing returns and it is an important thing to know as we explore the actions we need to take to improve our organization.
The reason we need to know about the law of diminishing returns is that there are times when the course we are taking to improve the organization will come to an end. There are limits to what can be achieved with one approach.
Figure 2.11 Adding resources adds output until a point where it adds less output, diminishing returns.
Theory of Contraints
There are limits to any system, and businesses are a collection of systems. These systems interact with each other, a system the consists of subsystems. This system is only as capable as the slowest or weakest point. This is why local optimization is not the answer. It is important to understand the entirety of the system: where are the constraints then address those limits, continually moving to the next limit. In the graphic below, x is the starting point, followed by 2, and then maybe 3 will be next depending upon where 3 fits in the system flow. When we make decisions about the organization’s way of working we must decide what to prioritize. If we are
Figure 2.12 Care should be taken not to dwell on local optimization.
prioritizing the correct thing, we improve throughput and capabilities, but only to find there is another restraining factor.
Tlie first step is to recognize that every system was built for a purpose. We didn’t create our organizations just for the sake of their existence. Thus, every action taken by any part of the organization should be judged by its impact on the overall purpose. This immediately implies that, before we can deal with the improvement of any section of a system, we must first define the system’s global goal; and the measurements that will enable us to judge the impact of any subsystem and any local decision, on this global goal.
To improve the capabilities or throughput requires a systematic approach to the constraining factor at any given time in the organization’s process or organization’s structure. According to Goldratt, there are five steps to addressing these constraints.
In this way, whatever the constraining factor is for the organization is constantly explored to find ways to elevate the constraint’s impact on this attribute on the entire system. At some point, what was a constraining factor will eventually not be the limiting element. Then the new constraining attribute will need to be under this recurring scrutiny.
Processes Make the Best Lessons Learned Repositories
When done well, process management, especially the documentation portions of the work, make great lessons learned repositories. We move from the anecdotal, not knowing what set of circumstances precipitated that observable result. We may see that either a project or set of tasks produced a win but have no idea what was done nor how it may have been done to any level of detail. What can we say about that specific approach, when we do not know how or what set of circumstances?
We also discussed that processes require system knowledge to be effective as the procedures which build them are only small; this begs the question of why processes make the best repositories for lessons learned. To answer that question, we must look at the application of the lessons learned. When you apply any lesson to one small part it is trapped to that part, but if you can show the relationship to the greater function, the process, it can be associated to several other items (the procedures) within that group. This provides us with some recorded history and associations limiting reliance upon human recall that is plenty fallible. This is both an example of systems thinking and true root cause analysis.
Benefits of Capturing
To provide the maximum benefit, lessons learned need to be captured in a manner wherein data is is easily deposited and equally easily recovered. This is commonly a function of either understanding the true issue(s) which caused the lesson or the ability to look at how the system as a whole could gain from what was learned. While these two hurdles inhibit using lessons learned to their full potential the most common failure of applying lessons learned is tribal knowledge and information brokerage. Tribal knowledge and information brokerage both go hand in hand as is discussed in the book “Tribal Leadership.”* As we discussed in the section on Inhibitors to Communication and in Tacit (Tribal Knowledge) we can see how the control of information is or can be used to support the position or perceived position of the individual. This type of office politics is without a doubt the largest inhibitor to an effective lesson’s learned program as the sharing of this information would diminish the position or perceived position for some people. At this point you are probably asking why we keep saying, “position or perceived position.” That would be because if the individual’s position was based on reality rather than perception, the sharing of this information would be automatic. It would be what is discussed in stage 4 tribal leadership, “We’re Great,”1' rather than the sporadic dissemination of information as with most office politics. Elimination of this malady will lend to codification of learning and, therefore, become explicit knowledge.
Organizing Lessons Learned by Process Helps Codify Knowledge
Processes are not stagnant, as we do the work; we learn and try permutations or wholesale modification of the process or processes based upon prioritization and objectives - process improvement. We begin with the review of the process data, that is, the metrics generated by the work. Armed with performance metrics and the specific methods (the process documentation) we can start to work through any connection (correlation) between the process and the results. We will perhaps use a process similar to the Deming cycle to work through these improvements. The plan step is where we identify the area for improvement and the experiment we want
Figure 2.13 The Deming cycle is a structured way to continuous improvement.
to conduct to make that improvement. The do phase, we execute the experiment recording the results. Upon completion of the do, we will check the data generated from the experiment: Did what we thought would happen actually happen? If not then we need to rework our experiment. If things are better and we know why, we will enAct the change to the process across the organization.
Understanding how we got the results, a track record of the the adaptations we made, culminating in the understanding of the process limitations and the range of variation that the process as it presently exists produces. If the organization does not like the variation, or finds the variation impacting in ways that are not acceptable, then it is time to adapt the process. These processes are then tested out (via TQM tools for example), and if the tests prove the adaptation is the way for the organization to move, then the process documents are updated, thereby codifying the learning at least on paper. This type of action—evaluate, change, evaluate— can be viewed as either single loop, double loop learning, triple loop learning, or organizational learning.
Single Loop Learning Theory
Single-loop learning is the most basic type of learning and behavioral change that can take place within a system and is also described as incremental learning. Single-loop learning describes the type of learning that takes place when the objective is to fix problems within the present organizational structure so that the system will function better and does not attempt to alter the structure of the system."
You will note that in the description of single loop learning, it states that the objective is to “Fix Problems.” While problems will always arise, even within a learning organization, a proactive stance of seeking the problems before they become a physical manifestation is the true goal of a learning organization. From experience, we note that fixes to problems are focused on the end result or the manifestation of the problem, rather than proactively exploring improvements before the poor performance is visible. In that we mean that a fix is determined to allow progression of the tasks or item and little thought or concern is given to the long-term effects of that action or its ramification on other projects using the process or procedure that was modified to restore operations.
Double Loop Learning Theory
Double-loop learning, also known as refraining, contrasts with singleloop learning by questioning the purpose and function of work being done within an organization and does not take existing organizational structures for granted. Double-loop learning is concerned with understanding the basis for the tasks being completed, rather than a more efficient process for completing them
This approach is more refined than single loop learning because it looks into the basis of the actions undertaken, which promotes systems thinking, an important part of a learning organization as discussed by Peter Senge in his book “The Fifth Discipline.” This understanding of the basis of an action allows for a deeper understanding of how changes could affect the process as a whole and thus reduce the potential for untended consequences, an archetype which we will discuss in the appendix. The double loop learning theory as stated in the above quote is not focused on the efficiency of the process upon which the evaluation is being completed. Thus this type of learning is more informational than active. However, the information garnered using double loop learning almost always facilitates enough information to initiate some form of change action.
Triple Loop Learning Theory
Triple-loop learning is the third type of learning that is compared with single-loop and double-loop learning. Also known as transformational learning, triple-loop learning involves the questioning not just of work
processes and the basis for tasks within an organization, but also the reflexive examination of the individual’s attitudes and point of view
It is not until we get to triple loop learning that we see the inclusion of the individual’s attitude and view point. It is this dynamic shift that brings the individual into the equation and appears to start the valuation of the people conducting the tasks. While this addition may seem small in nature it plays toward many of the motivational theories in the respect of individual’s value or self-worth, a key component in motivation.
Organizational learning (OL) is the broader field of study in which single-loop learning was developed. OL has been defined in multiple ways over the past several decades by organizational theorists. The most basic definition of organizational learning is the process of finding and correcting errors in organizations, but organizational learning also has come to include other processes for understanding the culture and behaviors of organizations.1
Last but not least, we come to organizational learning. This approach is more a summation of all the different types of loop learning with a slant to cultural and behavioral aspect that are fostered within the organization itself. The cultural and aggregate behavior of an organization is not the sum of its personnel, but something with a life of its own. While it is comprised of the aspects of all its members, the results presented are not always demographically divisible into its components: the people who comprise it.
Theory of Action
Argyris formulated single-loop and other learning theories based on his theory of action, which claims that individuals have a theory or mental map for the actions they perform. These theories are enacted in an unspoken way through theories-in-use, or in a verbalized way that is used to explain actions to others through espoused theories.
Espoused theory according to Argyris and Schon is the world view and values people believe their behavior is based upon.
Theory-in-use according to Argyris and Schon is the world view and values implied by the behavior of people, or the maps they use to take action.1
As we saw from our discussion of triple loop learning and organizational learning, the aggregate of the organizational perspective that is the sum of the individual’s perspective has come into play. Since perspectives can be some measure of distortion from the actual, it is important to understand the underlying sources for any distortions. We would not want to undertake unreviewed assumptions and perspectives as doing so starts the exploration falsely. Communication is how we get past the facade that is perspective, and explore the true circumstances. This open and truthful discussion brings us to mental models, part of the learning organization as discussed by Peter Senge in his book “The Fifth Discipline.” While he calls it a “mental model,” we prefer to call it an “Open Mental model” as this better infers a willingness to listen and change based upon information gathered during the discussion and other perspectives.