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LAMDA and TRIZ: Knowledge Sharing

Lamda and TRIZ: Knowledge Sharing Across the Enterprise

| On 06, Apr 2009

By Ellen Domb and Katherine Radeka


Few companies know how to use knowledge systematically. Fewer companies know how to reuse that knowledge and even fewer know how to bring knowledge from outside the enterprise in order to bear challenges and opportunities.

The mission of The Theory of Inventive Thinking (TRIZ) is to give people the ability to analyze problems and reuse knowledge systematically so individuals can develop effective, innovative solutions to difficult problems.

Lean product development helps companies use its knowledge more effectively within product development. The look, ask, model, discuss, act (LAMDA) in problem solving is part of the Lean product development toolkit, which provides an accessible process to help individual people, departments and companies ensure that they are able to reuse the knowledge they have and make it more accessible to others. Lean product development and TRIZ work together to make a person a better problem solver at any position in an organization.

The Waste of Reinvention

The waste of reinvention is rife in organizations. Many people have difficulties sharing knowledge across organizational boundaries and sometimes even with the person in the next cubicle. Decision making, therefore, fails to take advantage of the knowledge an organization already has, much less bringing in knowledge from outside the company. In this environment, the wheel can be reinvented over and over and the solutions that result from this process do not reflect the best attributes an organization has to offer. Rapid decision making, however, is often seen as a way to help the organization move more quickly. Unanticipated implementation problems slow an organization down by costing precious time and money to fix.

The Theory of Inventive Problem Solving is founded on the concept that: “Somebody, someplace has already solved your problem or one a lot like it.” TRIZ contains a large and diverse toolkit for developing innovative solutions to problems that emerge from a deep pool of available knowledge about similar problems and solutions. The systematic approach to problem analysis in TRIZ helps practitioners decide which TRIZ tools are best to apply to a particular problem.

The tools reside within a simple framework for problem analysis:

  • Analyze the problem,
  • Select the tool,
  • Apply the tool,
  • Evaluate concepts and
  • Improve the concept or implement.

This framework does not include all of the steps that a person needs to solve a problem. It omits observation and data gathering. It also excludes the process of gaining commitment and buy-in from decision makers and implementers.

In problem solving, LAMDA is a comprehensive framework that explicitly seeks to avoid the waste of reinvention. It incorporates the data gathering, feedback and decision making steps to address the entire process of solving a problem and implementing the solution. By using TRIZ tools in a LAMDA framework, the problem solver can make more effective use of organizational knowledge and eliminate the waste of reinvention.

LAMDA: PDCA for Knowledge Workers

The idea of LAMDA is new, but the ideas behind the framework have a long history. Companies such as Toyota and GE are recognized as being best in class for knowledge-driven decision making. They have all developed frameworks for problem solving that derive from the Shewhart cycle: plan-do-check-act (or PDCA).1PDCA asks the problem solver to slow down long enough to collect data, develop a plan and test ideas before moving ahead with a full implementation. Oftentimes, individuals are great at developing plans, but they do not usually test ideas before putting them into action. The PDCA helps prevent all of the unintended side effects by surfacing them with thorough analysis and testing before full-scale implementation. The ideas that make it to the act stage are ready for prime time.

Despite its history, the PDCA is not the best framework for all companies. In 2002, Allen Ward of the University of Michigan’s Japan Technology Education Program, began to teach PDCA to his product development clients. He found that PDCA was not sufficient in describing what Toyota and other leading Japanese firms actually did when they set out to solve a problem. When Ward’s American clients tried to use PDCA, they did not get the same results as Toyota. Ward looked more deeply at this and recognized that just like the simple problem analysis framework in TRIZ there were some missing steps. Ward developed LAMDA to close the gap.2,3,4

Figure 1: LAMDA Cycle

The LAMDA Cycle

When one depicts LAMDA as a cycle, the steps follow a logical sequence:


Look at the problem. Get direct and hands-on experience with it if possible. If the problem is on the manufacturing floor then go there. Talk to the operator. Try out the operation yourself if possible. If you cannot see the problem for yourself, interview the people who can. Ask them for video or a photograph. Finally, after learning as much as you can from looking, gather any indirect data, especially data from similar problems.


Ask two questions:

  1. What do we already know about this?
  2. Why?

Who are the experts? Who has already solved this problem before? What is already known? Why is this happening? Use the Five Whys (5W) tool or some other root cause analysis tool to deeply understand why.


Create simple models to help articulate thinking. For most people these models will be physical models, like prototypes or visual models, such as sketches, pictures, charts and graphs. These models help overcome the difficultiesof putting thoughts into words, making it easier to avoid miscommunication and have rich discussions.


Discuss the problem and the proposed solution with a wide variety of people including identified experts, the people impacted by the problem (and the solution) and the person who will ultimately decide what to do. These discussions help refine ideas and gain buy-in for implementation.


Now, it is ready to act or put the implementation plan into place. But the cycle does not stop here.

Look Again

After an individual takes action, take a step back. What is seen? Did it meet expectations? What does one need to do now?

In practice, LAMDA does not always proceed in such a linear fashion. The steps overlap and look back on each other. The PDCA is two LAMDA cycles done in sequence:

  1. To develop and test a hypothesis
  2. To review the results of the test, adjust the plans if needed and then implement the plan.

Figure 2: The PDCA and LAMDA


This chart shows how the major tools in the TRIZ toolkit apply in different components of the LAMDA cycle:


Use these tools to deepen understanding of the current state that one is observing and why it is not the desirable state:
• Ideal final result (IFR)
• Functional analysis – defining
• Resources – identify current state and constraints


Use these tools to help understand what is happening and why:
• Zones of conflict
• System operator
Use these tools to help identify reusable knowledge:
• Contradictions
• Effects and benchmarking
• Patterns of technology evolution


Use these tools to help develop and analyze alternative solutions:
• Functional analysis – trimming
• Resources – options for future state
• 76 standards
• Patterns of evolution
• 40 principles and separation principles for contradiction elimination


Review all of the above with experts, those impacted and decision makers then revise as necessary. Improve ideas usingthese tools
• Ideality
• Feature transfer (frequently done with the Pugh concept matrix or the morphological box)


Gather data to evaluate the hypotheses developed through TRIZ.
• Lessons learned analysis to improve next TRIZ project

How This Works in Practice: A Hypothetical Example

A company producing marine robots experienced high field failures from galvanic corrosion at a key joint. Galvanic corrosion is caused when two types of metals are placed in an electrolytic bath with a current running through them. Depending on the combination of metals, one of them will begin to corrode, sometimes rapidly. Seawater is a wonderful electrolytic bath. Here is how the team used LAMDA to solve the problem:

Look: The team observed what they saw, comparing it to the IFR. The functional analysis helped the team identify the interfaces between the failing part and the rest of the system.

Ask: The first answer to “Why is the part failing,” seemed obvious. The part is corroding because there is an electric connection between this part and some other part that is causing galvanic corrosion.The function analysis and the system operator helped the team understand the various sources of electrical connection that could cause corrosion in the part. It turned out that an incomplete seal between this part and the main body of the robot was the source of the connection. The team hypothesized that the seal became too rigid and contracted under cold temperatures and lost its ability to fit into the space it was supposed to seal.

The next ask question is “Who knows?” There is a wealth of literature available about possible sources and solutions to galvanic corrosion. The team, however, found an interesting alternative by identifying the core contradiction in the system where the seal needed to be cold yet adaptable so that it would maintain its integrity in circumstances where it was being buffeted by chilling ocean waves. The team looked at two technical (trade-off) contradictions:

  1. Temperature gets better, but reliability gets worse
  2. Temperature gets better, but adaptability gets worse

The team found the answer in principle 2, separation and principle 3, local quality, which were the most frequently used principles to solve these two contradictions, according to the classical contradiction matrix. By placing the electromagnetic seal inside the robot, where ambient heat from the robot’s computers would keep it warm and insulating it from the outside chill, the seal would do its job with minimal redesign of the sub-system.

Model: Along the way, the team built models or sketches of the problem and potential solutions as well as a physical model that immersed the problematic part’s sub-system in a salt water bath for testing.

Discuss: The team discussed its solution with a broad group of experts including external experts in galvanic corrosion resistance. They also discussed the approach with maintenance technicians, sales representatives and engineers for major customers. Through these discussions, the new design was refined until it was easy to switch out with the current part.

Act: The team fabricated a test part and tested it in an experimental field robot. The part showed only a small amount of slow corrosion and not the large amount the team had seen before. Since this slow corrosion is normal in a marine application and will not require maintenance before the end of the robot’s duty cycle, this was an acceptable fix.

The team ran through another quick LAMDA cycle to exchange the parts on all robots in the field:

  • Look – the new part showed greater reliability in pilot testing, but it still needed to fix the problem in all robots in the field.
  • Ask – in this case, it was important to ask “Who Knows?” How to manage customer communications, scheduling and resources to get the new parts installed.
  • Model – schedules, timelines and risk analysis models helped the team plan.
  • Discuss – the team discussed the plan with a wide variety of stakeholders including its largest customer and the company’s marketing department so that they could get this done quickly and communicate effectively with its customers.
  • Act – replace the parts.

The team continued to look again by tracking field failures on this part to ensure that the solution had worked.


By using the TRIZ toolkit within the framework of LAMDA, problem solvers can deepen understanding of the current state, identify reusable knowledge and develop more innovative and effective solutions. Both LAMDA and TRIZ help practitioners remember the importance of direct observation, data collection, visual and physical models, discussion and buy-in. The Theory of Inventive Problem Solving gives LAMDA practitioners some powerful tools for understanding the problem and developing innovative solutions.


  1. Walter Andrew Shewhart, Statistical Method from the Viewpoint of Quality Control. New York: Dover. ISBN 0-486-65232-7, 1939.
  2. Allen C. Ward, The Lean Development Skills Book, Ward Synthesis, Inc., 2002.
  3. W. Edwards Deming, “Out of the Crisis,” MIT Press, USA, 2000.
  4. W. Milliken, “Using the tools” Appendix inM. Cowley and E. Domb, “Beyond Strategic Vision,” Butterworth-Heineman, USA, 1997.