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Double Loop Learning in Organizations

by Chris Argyris

Several years ago the top management of a multi-billion dollar corporation decided that Product X was a failure and should be dropped. The losses involved exceeded $ 100 million. At least five people knew that Product X was in serious trouble six years before the company decided to stop producing it. Three were plant managers who lived daily with the production problems. The two others were marketing officials, who perceived that the manufacturing problems could not be solved without expenditures that would raise the price of the product to the point where it would no longer be competitive in the market.

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Home » Learning Theories » Double Loop Learning (C. Argyris)

Double Loop Learning (C. Argyris)

Argyris (1976) proposes double loop learning theory which pertains to learning to change underlying values and assumptions. The focus of the theory is on solving problems that are complex and ill-structured and which change as problem-solving advances.

Double loop theory is based upon a “theory of action” perspective outlined by Argyris & Schon (1974). This perspective examines reality from the point of view of human beings as actors. Changes in values, behavior, leadership, and helping others, are all part of, and informed by, the actors’ theory of action. An important aspect of the theory is the distinction between an individual’s espoused theory and their “theory-in-use” (what they actually do); bringing these two into congruence is a primary concern of double loop learning. Typically, interaction with others is necessary to identify the conflict.

There are four basic steps in the action theory learning process: (1) discovery of espoused and theory-in-use, (2) invention of new meanings, (3) production of new actions, and (4) generalization of results. Double loop learning involves applying each of these steps to itself. In double loop learning, assumptions underlying current views are questioned and hypotheses about behavior tested publically. The end result of double loop learning should be increased effectiveness in decision-making and better acceptance of failures and mistakes.

In recent years, Argyris has focused on a methodology for implementing action theory on a broad scale called “action science” (see Argyris, Putnam & Smith, 1985) and the role of learning at the organizational level (e.g., Argyris, 1993; Schon & Argyris, 1996).

Application

Double loop learning is a theory of personal change that is oriented towards professional education, especially leadership in organizations. It has been applied in the context of  management development  .

Here are two examples from Argyris (1976, p16). A teacher who believes that she has a class of “stupid” students will communicate expectations such that the children behave stupidly. She confirms her theory by asking them questions and eliciting stupid answers or puts them in situations where they behave stupidly. The theory-in-use is self-fulfilling. Similarly, a manager who believes his subordinates are passive, dependent and require authoritarian guidance rewards dependent and submissive behavior. He tests his theory by posing challenges for employees and eliciting dependent outcomes. In order to break this congruency, the teacher or manager would need to engage in open loop learning in which they delibrately disconfirm their theory-in-use.

• Effective problem-solving about interpersonal or technical issues requires frequent public testing of theories-in-use.
• Double loop learning requires learning situations in which participants can examine and experiment with their theories of action.
• Argyris, C. (1976). Increasing Leadership Effectiveness. New York: Wiley.
• Argyris, C. (1993). On Organizational Learning. Cambridge, MA: Blackwell.
• Argyris, C. & Schon, D. (1974). Theory in Practice. San Francisco: Jossey-Bass.
• Argyris, C. (1982). Reasoning, Learning and Action. Individual and Organizational. San Francisco: Jossey-Bass.
• Argyris, C. (1993). Knowledge for Action. San Francisco: Jossey-Bass.
• Argyris, C., Putnam, R. & Smith, D. (1985). Action Science. San Francisco: Jossey Bass.

Related websites

While not directly about Argyris or his theory, there are many web sites that focus on management development and organization learning which are related to his work. Relevant resources are the  Society for Organizational Learning  or the web pages of  Yogesh Malhotra  .

A bibliography of Argyris’ work can be found at  http://www.actionscience.com/argbib.htm

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Double Loop Learning: Download New Skills and Information into Your Brain

We’re taught single loop learning from the time we are in grade school, but there’s a better way. Double loop learning is the quickest and most efficient way to learn anything that you want to “stick.”

So, you’ve done the work necessary to have an opinion , learned the mental models , and considered how you make decisions . But how do you now implement these concepts and figure out which ones work best in your situation? How do you know what’s effective and what’s not? One solution to this dilemma is double loop learning.

We can think of double loop learning as learning based on Bayesian updating — the modification of goals, rules, or ideas in response to new evidence and experience. It might sound like another piece of corporate jargon, but double loop learning cultivates creativity and innovation for both organizations and individuals.

“Every reaction is a learning process; every significant experience alters your perspective.” — Hunter S. Thompson

Single Loop Learning

The first time we aim for a goal, follow a rule, or make a decision, we are engaging in single loop learning. This is where many people get stuck and keep making the same mistakes. If we question our approaches and make honest self-assessments, we shift into double loop learning. It’s similar to the Orient stage in John Boyd’s OODA loop . In this stage, we assess our biases, question our mental models, and look for areas where we can improve. We collect data, seek feedback, and gauge our performance. In short, we can’t learn from experience without reflection. Only reflection allows us to distill the experience into something we can learn from.

In Teaching Smart People How to Learn , business theorist Chris Argyris compares single loop learning to a typical thermostat. It operates in a homeostatic loop , always seeking to return the room to the temperature at which the thermostat is set. A thermostat might keep the temperature steady, but it doesn’t learn. By contrast, double loop learning would entail the thermostat’s becoming more efficient over time. Is the room at the optimum temperature? What’s the humidity like today and would a lower temperature be more comfortable? The thermostat would then test each idea and repeat the process. (Sounds a lot like Nest.)

Double Loop Learning

Double loop learning is part of action science — the study of how we act in difficult situations. Individuals and organizations need to learn if they want to succeed (or even survive). But few of us pay much attention to exactly how we learn and how we can optimize the process.

Even smart, well-educated people can struggle to learn from experience. We all know someone who’s been at the office for 20 years and claims to have 20 years of experience, but they really have one year repeated 20 times.

Not learning can actually make you worse off. The world is dynamic and always changing. If you’re standing still, then you won’t adapt. Forget moving ahead; you have to get better just to stay in the same relative spot, and not getting better means you’re falling behind.

Many of us are so focused on solving problems as they arise that we don’t take the time to reflect on them after we’ve dealt with them, and this omission dramatically limits our ability to learn from the experiences. Of course, we want to reflect, but we’re busy and we have more problems to solve — not to mention that reflecting on our idiocy is painful and we’re predisposed to avoid pain and protect our egos.

Reflection, however, is an example of an approach I call first-order negative, second-order positive. It’s got very visible short-term costs — it takes time and honest self-assessment about our shortcomings — but pays off in spades in the future. The problem is that the future is not visible today, so slowing down today to go faster at some future point seems like a bad idea to many. Plus with the payoff being so far in the future, it’s hard to connect to the reflection today.

The Learning Dilemma: How Success Becomes an Impediment

Argyris wrote that many skilled people excel at single loop learning. It’s what we learn in academic situations. But if we are accustomed only to success, double loop learning can ignite defensive behavior. Argyris found this to be the reason learning can be so difficult. It’s not because we aren’t competent, but because we resist learning out of a fear of seeming incompetent. Smart people aren’t used to failing, so they struggle to learn from their mistakes and often respond by blaming someone else . As Argyris put it, “their ability to learn shuts down precisely at the moment they need it the most.”

In the same way, a muscle strengthens at the point of failure, we learn best after dramatic errors.

The problem is that single loop processes can be self-fulfilling. Consider managers who assume their employees are inept. They deal with this by micromanaging and making every decision themselves. Their employees have no opportunity to learn, so they become discouraged. They don’t even try to make their own decisions. This is a self-perpetuating cycle. For double loop learning to happen, the managers would have to let go a little. Allow someone else to make minor decisions. Offer guidance instead of intervention. Leave room for mistakes. In the long run, everyone would benefit. The same applies to teachers who think their students are going to fail an exam . The teachers become condescending and assign simple work. When the exam rolls around, guess what? Many of the students do badly. The teachers think they were right, so the same thing happens the next semester.

Many of the leaders Argyris studied blamed any problems on “unclear goals, insensitive and unfair leaders, and stupid clients” rather than making useful assessments. Complaining might be cathartic, but it doesn’t let us learn . Argyris explained that this defensive reasoning happens even when we want to improve. Single loop learning just happens to be a way of minimizing effort. We would go mad if we had to rethink our response every time someone asked how we are, for example. So everyone develops their own “theory of action—a set of rules that individuals use to design and implement their own behavior as well as to understand the behavior of others.” Most of the time, we don’t even consider our theory of action. It’s only when asked to explain it that the divide between how we act and how we think we act becomes apparent. Identifying the gap between our espoused theory of action and what we are actually doing is the hard part.

The Key to Double Loop Learning: Push to the Point of Failure

The first step Argyris identified is to stop getting defensive. Justification gets us nowhere. Instead, he advocates collecting and analyzing relevant data. What conclusions can we draw from experience? How can we test them? What evidence do we need to prove a new idea is correct?

The next step is to change our mental models . Break apart paradigms. Question where conventions came from. Pivot and make reassessments if necessary.

Problem-solving isn’t a linear process. We can’t make one decision and then sit back and await success.

Argyris found that many professionals are skilled at teaching others, yet find it difficult to recognize the problems they themselves cause (see Galilean Relativity ). It’s easy to focus on other people; it’s much harder to look inward and face complex challenges . Doing so brings up guilt, embarrassment, and defensiveness. As John Grey put it, “If there is anything unique about the human animal, it is that it has the ability to grow knowledge at an accelerating rate while being chronically incapable of learning from experience.”

When we repeat a single loop process, it becomes a habit. Each repetition requires less and less effort. We stop questioning or reconsidering it, especially if it does the job (or appears to). While habits are essential in many areas of our lives, they don’t serve us well if we want to keep improving. For that, we need to push the single loop to the point of failure, to strengthen how we act in the double loop. It’s a bit like the Feynman technique — we have to dismantle what we know to see how solid it truly is.

“Fail early and get it all over with. If you learn to deal with failure… you can have a worthwhile career. You learn to breathe again when you embrace failure as a part of life, not as the determining moment of life.” — Rev. William L. Swig

One example is the typical five-day, 9-to-5 work week. Most organizations stick to it year after year. They don’t reconsider the efficacy of a schedule designed for Industrial Revolution factory workers. This is single loop learning. It’s just the way things are done, but not necessarily the smartest way to do things.

The decisions made early on in an organization have the greatest long-term impact. Changing them in the months, years, or even decades that follow becomes a non-option. How to structure the work week is one such initial decision that becomes invisible. As G.K. Chesterton put it, “The things we see every day are the things we never see at all.” Sure, a 9-to-5 schedule might not be causing any obvious problems. The organization might be perfectly successful. But that doesn’t mean things cannot improve. It’s the equivalent of a child continuing to crawl because it gets them around. Why try walking if crawling does the job? Why look for another option if the current one is working?

A growing number of organizations are realizing that conventional work weeks might not be the most effective way to structure work time. They are using double loop learning to test other structures. Some organizations are trying shorter work days or four-day work weeks or allowing people to set their own schedules. Managers then keep track of how the tested structures affect productivity and profits. Over time, it becomes apparent whether the new schedule is better than the old one.

37Signals is one company using double loop learning to restructure their work week. CEO Jason Fried began experimenting a few years ago. He tried out a four-day, 32-hour work week. He gave employees the whole of June off to explore new ideas. He cut back on meetings and created quiet spaces for focused work. Rather than following conventions, 37Signals became a laboratory looking for ways of improving. Over time, what worked and what didn’t became obvious.

Double loop learning is about data-backed experimentation, not aimless tinkering. If a new idea doesn’t work, it’s time to try something else.

In an op-ed for The New York Times , Camille Sweeney and Josh Gosfield give the example of David Chang. Double loop learning turned his failing noodle bar into an award-winning empire.

After apprenticing as a cook in Japan, Mr. Chang started his own restaurant. Yet his early efforts were ineffective. He found himself overworked and struggling to make money. He knew his cooking was excellent, so how could he make it profitable? Many people would have quit or continued making irrelevant tweaks until the whole endeavor failed. Instead, Mr. Chang shifted from single to double loop learning. A process of making honest self-assessments began. One of his foundational beliefs was that the restaurant should serve only noodles, but he decided to change the menu to reflect his skills. In time, it paid off; “the crowds came, rave reviews piled up, awards followed and unimaginable opportunities presented themselves.” This is what double loop learning looks like in action: questioning everything and starting from scratch if necessary.

Josh Waitzkin’s approach (as explained in The Art of Learning ) is similar. After reaching the heights of competitive chess, Waitzkin turned his focus to martial arts. He began with tai chi chuan. Martial arts and chess are, on the surface, completely different, but Waitzkin used double loop learning for both. He progressed quickly because he was willing to lose matches if doing so meant he could learn. He noticed that other martial arts students had a tendency to repeat their mistakes, letting fruitless habits become ingrained. Like the managers Argyris worked with, students grew defensive when challenged. They wanted to be right, even if it prevented their learning. In contrast, Waitzkin viewed practice as an experiment. Each session was an opportunity to test his beliefs. He mastered several martial arts, earning a black belt in jujitsu and winning a world championship in tai ji tui shou.

Argyris found that organizations learn best when people know how to communicate. (No surprise there.) Leaders need to listen actively and open up exploratory dialogues so that problematic assumptions and conventions can be revealed. Argyris identified some key questions to consider.

• What is the current theory in use?
• How does it differ from proposed strategies and goals?
• What unspoken rules are being followed, and are they detrimental?
• What could change, and how?
• Forget the details; what’s the bigger picture?

Meaningful learning doesn’t happen without focused effort. Double loop learning is the key to turning experience into improvements, information into action, and conversations into progress.

Improving critical thinking ability using e-modules based on double loop problem solving on thermodynamic materials

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Happy Komikesari , Ardian Asyhari , Pramita Sylvia Dewi , Sodikin , Ajo Dian Yusandika , Nadya Intan Herawati; Improving critical thinking ability using e-modules based on double loop problem solving on thermodynamic materials. AIP Conf. Proc. 5 April 2024; 3058 (1): 020015. https://doi.org/10.1063/5.0206424

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The purpose of this research is developing teaching materials in the form of e-modules based on double loop problem solving in order to improve critical thinking ability. The research and development (R&D) method was used in the study. The ADDIE model was used in this development research, which included analysis, design, development, implementation, and evaluation. This study resulted some findings, they are: (1) Media experts have an e-module feasibility quality of 77.9%, material experts have 84.5%, and IT experts have an quality of 92.6%. (2) The small group trial of e-modules results received an 87.50% and the field trials received an 89.55%, with 92.3% of educators responding. (3) There is an increase in critical thinking ability with the availability of e-module teaching materials based on double loop problem solving, as indicated by the average value of the normalized N-Gain score, as follows: The average N-Gain score for small group trials is 0.53 in the medium category, while the average N-Gain score for field trials is 0.48 in the medium category.

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Field guide to change management frameworks >, what is double loop learning, 1. person or firm who created the framework.

Double Loop Learning was developed by Chris Argyris.

2. Description of the framework

Double Loop Learning is a concept in organizational learning that involves challenging and changing underlying assumptions, norms, and policies to achieve deeper and more effective learning. It contrasts with Single Loop Learning, which focuses on making incremental adjustments without questioning underlying assumptions. Double Loop Learning consists of two loops:

• Single Loop Learning : Making adjustments to actions and strategies to correct errors and improve performance without questioning underlying assumptions.
• Double Loop Learning : Challenging and changing underlying assumptions, norms, and policies to achieve deeper and more transformative learning.

3. The framework's "secret sauce"

The distinctive feature of Double Loop Learning is its emphasis on questioning and changing underlying assumptions and norms. By addressing the root causes of problems and challenging the status quo, organizations can achieve more significant and lasting improvements.

4. Situations for which the framework is particularly well suited

• Organizational learning and development initiatives
• Cultural change initiatives
• Continuous improvement and innovation efforts
• Strategic planning and problem-solving
• Any situation requiring deep and transformative change

5. Practical instructions for using this framework

Step 1: identify issues and challenges.

• Identify the key issues and challenges facing the organization.
• Use data and feedback to understand the symptoms and impacts of the problems.
• Analyze the current actions and strategies used to address the issues.
• Identify the limitations and shortcomings of these responses.

Step 2: Apply Single Loop Learning

• Make incremental adjustments to actions and strategies to correct errors and improve performance.
• Monitor the impact of these adjustments and gather feedback.
• Assess the effectiveness of the adjustments in addressing the issues.
• Determine whether the problems have been resolved or if deeper changes are needed.

Step 3: Apply Double Loop Learning

• Identify the underlying assumptions, norms, and policies that drive current actions and strategies.
• Question and critically evaluate these assumptions to determine if they are valid and effective.
• Develop new assumptions and strategies that address the root causes of the problems.
• Ensure that the new assumptions are aligned with the organization’s values and goals.
• Implement the new assumptions and strategies to achieve deeper and more transformative change.
• Monitor the impact of these changes and gather feedback.

Step 4: Foster a Culture of Double Loop Learning

• Foster a culture of critical thinking and continuous learning within the organization.
• Encourage employees to question assumptions, challenge the status quo, and seek innovative solutions.
• Provide training and resources to help employees develop the skills needed for Double Loop Learning.
• Use workshops, coaching, and mentoring to support learning and development.
• Create a safe and supportive environment where employees feel comfortable expressing their ideas and challenging assumptions.
• Recognize and reward individuals and teams who demonstrate Double Loop Learning behaviors.

6. Further Reading

• Double Loop Learning in Organizations by Chris Argyris
• “Organizational Learning: A Theory of Action Perspective” by Chris Argyris and Donald A. Schön

Download the complete Field Guide to Change Managment Frameworks

List of frameworks:.

• 4D Model of Appreciative Inquiry
• ACMP’s Standard for Change Management
• ADAPT Model
• ADKAR Model
• Agile Change Management
• AIM Change Management Methodology
• Balanced Scorecard
• Beer and Nohria’s E & O Theory
• Bridges’ Transition Model
• Burke-Litwin Model
• Business Process Reengineering
• Capability Maturity Model Integration
• Carnall’s Change Management Model
• Change Journey Map
• Change Kaleidoscope
• Change Leader’s Roadmap
• Congruence Model
• Cultural Web Model
• DICE Framework
• Disruptive Innovation Model
• Double Loop Learning
• Enterprise Agility Model
• Five Dysfunctions of a Team
• Fogg Behavior Model
• Formula for Change
• Four Frames of Change
• Herzberg’s Motivation-Hygiene Theory
• Hoshin Kanri Process
• Innovation Diffusion Theory
• Kanban Change Management
• Kotter’s 8-Step Change Model
• Kubler-Ross Change Curve
• Learning Organization
• Lewin’s Change Management Model
• Management by Objectives
• McKinsey 7-S Model
• McKinsey Four-part Influence Model
• Momentum Model
• Nadler-Tushman Congruence Model
• Nudge Theory
• Organizational Capacity for Change
• Organizational Network Analysis
• Pathfinder Model
• Positive Deviance
• Power/Interest Grid
• Prosci’s Change Management Process
• Resistance Management Framework
• Scenario Planning
• Schein’s Change Model
• Seven Levels of Change
• Six Sigma Change Acceleration Process
• Six Sources of Influence
• Stacey Matrix
• Stakeholder Analysis Matrix
• Strategic Change Matrix
• Switch Framework
• System Dynamics Model
• Three Box Solution
• Three Horizons Framework
• Tipping Point Leadership
• Trans-theoretical Model of Behavioral Change
• Transformational Leadership Model
• Virginia Satir Change Model

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Problem-Solving as a Double-Loop Learning System

• Jeff Dooley
• Published 1999
• Education, Computer Science

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Synthesis as conception shifting, the influence of double loop problem solving learning models to senior high school learners spatial thinking ability, some reflections on the teaching of mathematical modeling., undergraduate representative erin cain jessie rieber a note from the editor dear tme, effect of dlps (double loop problem solving) learning strategy on entomology cognitive learning outcomes of the students of biology education in faculty of teacher training and education mulawarman university, investigation and problem identification mathematical formulation of the model collect data and obtain a mathematical solution to the model interpret the solution compare with reality implement the solution and report writing, information systems foundations: constructing and criticising, iamot 2009 proceedings a systems dynamic approach to channel management h.g.dirker, how has guinea learnt from the response to outbreaks a learning health system analysis, penerapan double loop problem solving untuk meningkatkan kemampuan literasi matematis level 3 pada siswa kelas viii smpn 27 bandung.

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Principles of systems, creative problem solving: total systems intervention., dealing with complexity, modeling for learning organizations, how to make meetings work, theory in practice., introduction to system dynamics modeling with dynamo, organizational health in the systems age: a renaissance systems perspective, knowledge in action, elements of the system dynamics method, related papers.

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Unearthing the Mystery of Toyota’s Success

I f you’re involved in lean work in any capacity, whether in management, as a coach, or as a participant in lean events, the book Toyota Kata: Managing People for Improvement, Adaptiveness and Superior Results (McGrawHill, 2009) by Mike Rother is a game changer. Rother unearths a deep mystery about Toyota’s success—the secret of what makes it a real-life example of a learning organization, not just at the senior level, but all the way to team leaders and team members. In a research tour de force, he succeeds in capturing the double-loop learning mechanism that Toyota has developed. To cap it off, Rother illustrates Toyota’s vaunted managerial practices simply and with great examples.

Beyond shedding light on lean, this book offers deep insight into how learning mechanisms can feed into business strategy to avoid the problem of creating grand visions that turn out to be grandly wrong. I suspect (or at least hope) that Rother’s insights will open the door to another form of strategy formulation for organizations of all kinds.

Toyota As a Learning Organization

As a student of organizational learning, I find it hard to resist the attraction of Toyota’s management model; over the years, the firm has developed a unique approach explicitly based on learning, both at the detail and strategic levels. In particular, it has developed practices and processes to:

Linking the quality of problem solving and learning to the presence of a coach sheds a new light on why Toyota is so much better than any other company at solving both detailed and strategic problems.

• Contextualize learning by constantly insisting on genchi genbutsu: going to the real place to see the facts at their source. Indeed, it’s well known that true information needs both context and data, just as knowledge needs both information and understanding. By making “go and see” the cornerstone of its managerial approach, Toyota has developed a process deeply imbedded in reality, in which decisions are based on the understanding of problems and their real-life impacts.
• Create learning labs in the day-to-day work environment. As with double-loop learning, the learning lab is a recurring feature in organizational learning approaches, but the many attempts have mostly been tried offline as simulations (either real-life or with computers). Toyota, on the other hand, has developed a practice of structuring any working environment as a “learning lab” through its knowhow of visual management. Any operator can see from her environment whether she is ahead or late, doing a good job or not, and how to call for help if the slightest thing seems strange. In this way, she can either learn her job in greater detail or make a suggestion for improvement.
• Use the systemic nature of supply chain environments as a key to learning rather than suffer from endemic Forrester effects (growing oscillation over time). By developing “pull systems,” Toyota has learned to link all steps of the chain in a smooth flow, along with the discipline to do so. Pull systems across the value stream act both as an architecture to improvement and as platforms for cross-functional problem solving.
• Share knowledge. The practical understanding of systemic interactions in the company has led it to focus explicitly on knowledge sharing both up and down the line and across functions. Most of this knowledge sharing occurs though joint problem-solving sessions in which people from different locations and backgrounds confront their perspectives and develop new ones.
• Constantly create knowledge, from detailed kaizen (continuous improvement) to radical innovation. To a large extent, it can be argued that kaizen in its many forms is Toyota’s management method; it is applied all the way from operators improving their workstations to top executives committing to develop the car of the future. This fundamental commitment to the scientific method of observation (genchi genbutsu), theory formulation (standards), focusing on anomalies (problems), experimenting (kaizen), measuring (check), and reformulating and generalizing (yokoten) is the engine of progress in the firm’s management approach.

In Toyota Kata, Rother touches on these various aspects of organizational learning. He argues that the way Toyota implements this framework is by having standardized its problem-solving approach and teaching its employees how to use it again and again, under various conditions, in the pursuit of an ideal or “true north.”

This is quite a profound take on the learning process, one that has already been illustrated in various ways by other Toyota observers (and Rother himself in other writings). To my mind, Rother’s deepest contribution is in highlighting the importance of coaching in problem solving (turning single loop learning into double-loop learning). Toyota’s problem solving does not occur in a vacuum, but under the guidance and control of a coach who makes sure the problem-solving process itself progresses with every cycle.

This insight explains many enigmatic aspects of Toyota’s organization, such as its use of senseis or “coordinators.” It also illuminates a share of its current difficulties, as it has grown much faster than its capacity to grow a stock of such coaches. Linking the quality of problem solving and learning to the presence of a coach sheds a new light on why Toyota is so much better than any other company at solving both detailed and strategic problems.

In many ways, this book can be seen either as the result of 20 years of research on Toyota and the Toyota Production System or as one of the breakthrough stepping stones that will usher in a new era of management thinking. Thumbs up!

Michael Ballé is associate researcher at Telecom ParisTech and managing partner of ESG Consultants. For the past 15 years, he has focused on how companies use lean techniques to develop a lean culture as part of his research on knowledge-based performance and organizational learning. He has written several books and articles about the links between knowledge and management (Managing With Systems Thinking, The Effective Organization, Les Modèles Mentaux), and more recently, co-authored two business novels, The Gold Mine and The Lean Manager. Michael is co-founder of the Projet Lean Entreprise and the Institut Lean France.

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The Influence Of Double Loop Problem Solving Learning Models to Senior High School Learners Spatial Thinking Ability

The purpose of this research is to know the influence of the using Double Loop Problem Solving (DLPS) learning models to Spatial thinking ability.This research is an experimental design. Data collected in this research consisted of interviews, field observations, and written test. Experimental research involves two classes of senior high school as a research subject, namely Social Class XI 5 as experimental class and Social Class XI 4 as control class. The results of this research showed the presence of gain score in experimental class and control class. Experiment class gain score is 15.8 while control class gain score is 9.5. There is a difference gain score between both of classes. Experimental class showed higher average of gain score. It can be noted that the use of models learning DLPS in learners give significant effects againts tha spasial thinking ability. Introduction Updates in the world of education are an action that has the goal to improve the quality of Human resources. Updates in the world of education can include several aspects, namely, the curriculum, the improvement of the quality of learning, as well as the application of appropriate learning models. In terms of the use of appropriate learning models, there is a wide selection of learning methods. This research chose DLPS models learning. DLPS learning models is a learning models based on problems as well as Problem Based Learning, but has some variations. Variations on DLPS are located on the issue which is used as a learning base has been examined deeper. There are two procces at DLPS problem examined. The purpose of examining the issue to find causal or cause major problems. Its mean, not only seing the issue superficially just on the cause seemed. On this models also analyzed other causes that allow the emergence of these problems. DLPS models its also learning models that's use feedback from past. Feedback from that has from some observation guide to understand problem that happen today. So the problem solution can be found clearly. Learning with DLPS models, not only prioritizes the base issue as it special fiture. This learning also has a characteristic form of decision making towards the solution of the problem with very well (Aminah 2016 [1] ; Argyris 1978 [4] ; Dooley 2009 [10] ; Kantamara and Ractham 2014 [17]). Learning with the DLPS models is one approach that can create a reliable solution. In contrast with learning are usually to do, this approach gives influence on how effectively we can anticipate changes, adapt to new situations and generate new solutions to the challenges faced. DLPS learning models can be like that because there is a step on DLPS learning models that guided learners to observer the problem faced correctly. Most efforts are focused on the process of problem solving the work is intended to make the process more efficient and more reliable. This DLPS models has a systematic structure in problem solving, as well as the steps that must be followed so that the solutions implemented to solve the problem is the main solution. These steps are writing down the problems of the beginning, classify the symptoms of problems, make improvements in the writing problems, identifying the causal or cause, solution implementation, identification of the main causes of early, find the right solutions, options and main solutions imlementasi (Lucky:2015 [20] ; Dooley 2009 [10]) DLPS have some advantages that can encourage learners to showed mathematical ideas through writing, oral or demonstration it. In addition this models approach is through learners can comprehend, interpret and evaluate mathematical ideas orally, in writing or other visual forms properly. Another advantage owned by DLPS, that is, first, DLPS is learning that is based on the issues. Problem based learning, can sue the learners to always pay attention to the environment, as well as increase sensitivity to surroundings. Second, DLPS have a step which Scientific Approach. Third, DLPS is learning that aims to assist learners in finding answers to the issues

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