Herman Miller LPPD Session at the 2016 Lean Transformation Summit

Many of us have applied basic lean concepts in our manufacturing environments, creating much improved processes and measurable results. Herman Miller recognized that it had gotten into a cycle of launching products and processes, then using lean principles on the shop floor to improve the new processes. The company realized that a way to move beyond this cycle of launch then improve was to apply lean to the product development process itself.

During this Learning Session, Ted and John will share some of the struggles that Herman Miller had and the countermeasures it developed to engage manufacturing earlier in the development process to influence product design before concepts were too far along to change. You’ll have a chance to share the gaps you see in your own organization between manufacturing and product development, and then develop some ideas to take back about what to try in order to reduce these gaps.

You can learn about the 2016 Lean Transformation Summit organized by the Lean Enterprise Institute by clicking here.

Baris Lostuvali

Baris Lostuvali is a senior project manager with Herrero Builders, a general contractor in San Francisco, California. Baris is a construction professional with hands-on experience on project management, construction management, and lean construction. Upon receiving his B.Sc. in Mechanical Engineering from Istanbul Technical University (Istanbul, Turkey), Baris began his career with the renovation of Philip Morris Tobacco Factory in Krasnodar, Russia. He obtained his M.Sc. in Project Management at Northwestern University (Evanston, Illinois).

Over the past 15 years, Baris has worked on a wide variety of construction projects including preconstruction, new construction, and building renovations for healthcare, commercial office buildings, and industrial facilities. Currently, he is practicing lean construction and IPD principles in CPMC Cathedral Hill Hospital Project in San Francisco.

Making Invisible Knowledge Visible in Product Design

In manufacturing, Lean is about ensuring efficient flow, from raw materials to finished products. When is flow efficient? When value creation happens, and when value is created unhampered continuously. Wouldn’t it be the same scenario in a product design environment? Well, almost… but there is one big point of difference. Unlike in manufacturing where “visible” material flows, it’s the knowledge that flows (or doesn’t), getting converted into the design of the product. This flow of knowledge is often “invisible”, which makes it even more challenging to comprehend the flow and ascertain the waste.

Ideally, a great product (on time release, high quality performance, stands ahead of competition) implies that the optimal, right decisions were taken during the development lifecycle. This requires great knowledge, and great handling of the knowledge, since knowledge is what drives key decisions. Many times you’ll find that defects, rework loopbacks, late products, cost overruns, and product under-performance scenarios encountered during product development can be traced back to suboptimal/wrong decisions made earlier without the required knowledge. The figure below attempts to illustrate the scenario of knowledge driving decisions in software product development.

http://www.lean.org/images/soft_pd.jpeg Figure:  Linkage: Prevalent Knowledge –> Decisions –> Great Product

Product development organizations without a sound knowledge value stream naturally fall behind their competitors who do have a sound knowledge value stream, since it’s most likely that the right decisions are not made in a timely manner. This is why the Prevalent Knowledge within the organization needs to flow efficiently in the knowledge value stream, driving not just timely decisions, but the right timely decisions.

Why do we need to get a deeper perspective on Knowledge Value Stream? While the Product Development Value Stream focuses on all the actions (both value added and non-value added) that is required to design/develop the product from concept to manufacturing, the Knowledge Value Stream focuses on how the knowledge flows to inform the decisions across the Product Development Value Streams. For instance, let’s consider the scenario of an organization with multiple LOBs (Lines-Of-Business: a set of highly related products serving a particular business need). Each LOB would be engaged in the design and development of multiple products. Each of these products have a lifecycle of their own, i.e. their own Product Development Value streams. In such large organizations, or in organizations where design teams work in silos, invaluable knowledge often reside with individuals within each Product Development Value Stream. An inefficient knowledge value stream results in multiple teams solving very similar problems, being unaware of each other’s work, and taking sub-optimal decisions, without effectively leveraging prior knowledge available elsewhere in the organization.

Hence, by examining the knowledge value streams in our organization more deeply by scrutinizing the basis of various decisions taken during the product design, we unearth many nuances on how prevalent knowledge drives the decisions across the product development lifecycle. While the different categories of wastes in a manufacturing environment are very “visible” (such as overproduction, excessive motion), wastes in Knowledge Value Streams are often veiled, causing unclear/ revisited decisions, re-learning, confusion/ incorrect understanding, and longer feedback cycles.

To counteract these problems, product development value stream owners must ask questions like: How do we go about examining the knowledge value streams? How do we identify wastes in the knowledge value stream? How do we ensure there is an efficient flow of prevalent knowledge? A lot of work needs to be done to answer these questions thoroughly and at various points over time, but for value stream owners, you start by gathering the right people together to consider them.

The views expressed in this post do not necessarily represent the views or policies of The Lean Enterprise Institute.

The Leader’s Job in Lean Product & Process Development

The role of the leadership in product development (PD) is to foster an environment that will help the organization change its habits and practices during the development process. This takes a fair amount of understanding of how things are done today, and how they should be done to create the most value for customers. But perhaps the harder thing in leading is anticipating what the triggers are behind the behaviors, and then making sure new practices are put in place to spur new behaviors.

In Lean PD, some of the key behaviors we want to change are how problems are solved, how knowledge is managed, and how quickly the team and organization learns.

To change the system, the leader can ask, What is the trigger? What is the old behavior? What is the new habit?

1.  Problem Solving

  • What are the triggers that cause people to go into problem solving mode? Is it a test failure? a new design problem? a new specification?
  • What is the old problem solving method? Is it Trial and Error?
  • How might Lean PD problem solving LAMDA model be used instead? Al Ward first identified the LAMDA (Look, Ask, Model, Discuss, and Act) method of solving problems in development.

2.  Knowledge 

  • What are the triggers that cause people to store knowledge or retrieve knowledge?
  • Are there triggers in place to encourage knowledge capture and reuse? What situations require clearly identified points to capture or reuse knowledge?
  • How might the triggers be used to ensure that teams are capturing and reusing knowledge?

3. Rapid Learning

  • When does learning drag on? When is responsiveness and solving problems quickly critical to the project success? Are all of the unsolved technical problems clearly identified? Are there unknown or fuzzy requirements?
  • What are the triggers or situations that call for rapid learning?
  • What methods are used today and where could rapid prototyping and learning cycles be used instead?

A leader who is trying to create a strong Lean PD system is constantly wondering and watching to see if the habits of the organization are changing to use the Lean PD methods.

And here is the tricky part. The target of the culture is not the culture. The target are the things that create the culture. Culture itself, per Dr. David Mann author of Creating a Lean Culture, is not the target because culture is a hypothetical construct. Basically, culture is made up of other things: the behaviors, practices, and habits of the members in the organization. To change the culture, the leader has to go back to the behaviors, practices, and habits and change those.

Habits, as we all know, are difficult to change. They are engrained and embedded in what we do everyday. And, habits are responses to triggers around us.

In the Power of Habit: Why We do What We Do in Life and Business, Charles Duhigg describes the powerful ways in which we respond to situations for no apparent reasons. The brain responds in certain ways because it is responding to the conditions that trigger our responses. Those patterns were established and learned, and each time the trigger occurs, we tend to automatically repeat the pattern. The trick to reversing a habit or replacing it is to unlearn old behavior and to switch to a new behavior when the triggers occur.

The leader can say when A happens, try C instead of B. And then create frequent opportunities for reflection and learning from these kinds of experiments and the individual, team, and organization level.

The views expressed in this post do not necessarily represent the views or policies of The Lean Enterprise Institute.

Timothy Schipper

Timothy Schipper works in the LEAN Management Office for Steelcase, Inc., Grand Rapids, MI, where he coaches leadership and teams in lean product design, lean management systems, and business transformations. He is co-author of Innovative Lean Development: How to Create, Implement, and Maintain a Learning Culture, which explores how rapid learning cycles, knowledge management, and other lean techniques apply to product development.  His articles have appeared in AME Target magazine and he is a frequent speaker at conferences on lean, innovation, and leadership.  

Timothy, who has led lean transformations in manufacturing, IT, product development, and service organizations, serves on the board of the nonprofit Lean Product and Process Exchange, Inc. He helps other businesses apply lean concepts through his company Lean Inspirations.  His teaching experience includes positions in the engineering department at Calvin College and in The Ohio State University Fischer College of Business’s MBOE Lean Leadership program. His 30-year career also includes time as a tool designer, CAD specialist, senior product engineer, and IT manager. He holds a bachelor’s in Mechanical Engineering and a Masters in Science. You can follow him at his blog or on Twitter @LeanInspirations.

Finding and Eliminating Waste in R&D

People often search for waste in R&D using the rule of the 7 wastes. This is useful, but misses the largest opportunities to remove waste and accelerate value within your development organization. Here are 7 ideas to help you think about, find and eliminate the biggest wastes in R&D.

1. Eliminate re-learning what you already know. R&D requires learning new things, typically through experimentation. Once an experiment is complete and its answer is known, there is zero value in learning it a second time. Hence, single easiest waste to identify in R&D is re-learning something that is already known. Too many scientists and engineers spend weeks in the laboratory proving known principles and designs.

2. “Failure” is not a waste. The purpose of R&D is to develop new products and processes that create customer valueWith that in mind, it is useful to recognize that nobody knows what will prove valuable to a customer until an invention is on the market. “Failed” experiments are part of learning what works and what does not work, what is valued and what is not valued. Given some caveats, failed experiments are highly value added, and in fact, necessary work. If you try to stamp out failure in R&D, the one thing that will certainly get stamped out is success.

3. Everything you have always learned about the 7 wastes applies in small measure in R&D. Yes, laboratories can be made far more efficient, especially production and testing laboratories. But in the end, these wastes pale in comparison to bad thinking. One great thought can transform an entire industry, but the wrong experiment will never generate that delight when a customer opens the box or looks at the price tag. Only good, creative thinking and experimentation will get you there.

Stamping out these wastes while preserving valuable learning is a wide subject in itself, so where can you start?

If you want to get rapid improvement in good thinking you can do two things: 

a) Get it in writing. The easiest thing you can do is to ensure that every researcher predict in writing, the outcome s/he expects from each experiment. A pharmaceutical company applied this single measure, and cut the number of experiments needed to get a quality target pharmaceutical from ~30,000 to ~400. That is a LOT of improvement in a small box.

b) Insist on structured thinking. If you want to improve thinking further, and begin to solve the “re-learning” problem, introduce A3 thinking and ensure that every experiment is part of a larger A3. By ensuring that the larger problem is known, and that every experiment supports the larger problem, and every problem is solved using a structured (scientific method) approach, you ensure that unnecessary experiments are minimized, learning is maximized towards the project’s purpose, and the results are held in one place for future reference.

At one company I worked with, the research division lost fully 40% of its staff during a layoff. Most teams, lacked a structure or historic understanding of all problems required for success, and had to rebuild their work almost from scratch. By contrast, one team held their project in a set of linked A3s. During the chaos of the reorganization, that team was able to pick up key scientists cast adrift when other teams collapsed. With A3s providing a clear structure and understanding of prior work, newly engaged scientists could pick right up where others had left off. While other teams restarted from scratch or dissolved entirely, the A3 team hardly lost a step, regaining full operational momentum within days of the layoff.

4. Begin using trade-off curves and checklists. These two devices capture and deliver optimization knowledge with a glance. There is a great body of literature and engineering coursework on trade-off curves, and I urge you to begin there. And while you implement curves and checklists, fight hard to implement sharing and storage using old fashioned hard copy processes. If you can get learning and sharing process right using hard copy processes, chances are good that you will avoid the waste of useless software when/if you do apply IT tools.

5. Finally, if you want to learn where customer preferences lie, or better yet, shape customer preferences themselves, you need to fail often, fail fast and fail cheap. This means your experiments have to be at the lowest possible scale for meaningful learning. Batching of experiments (linking the same or multiple types of experiments together in one prototype or test cycle) leads to the same wastes and failure modes as batching in a plant. Cycle times increase, complexity rises, costs increase and failures get hidden until further on when costs are higher. Breaking “large scale thinking” takes some careful thought on its own. The challenge here is to create experiments that deliver only one piece of learning, and do so with the minimal amount of cash, time, people or materials. Anything larger, slower or more costly sinks unneeded cost into failure, and rarely builds additional success.

In the end, if you are lean practitioner in R&D, minimizing re-learning, maximizing the quality of thinking, and re-casting your view of failure can rapidly improve the quality and speed of your innovation.

The views expressed in this post do not necessarily represent the views or policies of The Lean Enterprise Institute.

Terry Barnhart

Dr. Terence (Terry) Barnhart, author of Creating a Lean R&D System initiated and led the lean effort at Pfizer R&D. He has been a research scientist at GE, a consultant with McKinsey and Company, and a plant engineer at Uniroyal plastics. Terry has taught lean innovation for the Management Round Table, the US Navy, Proctor and Gamble, Nestle, and the US Marine Corps University. He currently leads the process and cultural transformation effort at Sandoz, Inc.