Book Summary: Improve — The Next Generation Of Continuous Improvement For Knowledge Work

Book Summary: Improve — The Next Generation Of Continuous Improvement For Knowledge Work

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June 27, 2020
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Improve: The Next Generation of Continuous Improvement for Knowledge Work presents lean thinking for professionals, those who Peter Drucker called knowledge workers. It translates the brilliant insights from Toyota’s factory floor to the desktops of engineers, marketers, attorneys, accountants, doctors, managers, and all those who "think for a living." The Toyota Production System (TPS) was born a century ago to an almost unknown car maker who today is credited with starting the third wave of the Industrial Revolution. TPS principles, better known as lean thinking or continuous improvement, are simple: increase customer value, cut hidden waste, experiment to learn, and respect others. As simple as they are, they are difficult to apply to the professions, probably because of the misconception that knowledge work is wholly non-repetitive. But much of our everyday work does repeat, and in great volume: approvals, problem-solving, project management, hiring, and prioritization are places where huge waste hides. Eliminate waste and you delight customers and clients, increase financial performance, and grow professional job satisfaction, because less waste means more success and more time for expertise and creativity.

This book is a valuable resource for leaders of professional teams who want to improve productivity, quality, and engagement in their organizations.

Other Interesting Tidbits

  • Author spent 5 years and 5,000 hours with three major rewrites on the book. He was the head of innovation at one of the top practitioners of lean.
  • Waste in the organization is about 85%.
  • We can reduce waste by a modest amount, perhaps 5% each year.
  • Because waste is large, a 2% or 3% decrease in waste makes room for a 10% or 15% expansion of value.
  • The central premise in this book is that waste diminishes value by stealing effort.


Big Ideas

8 Wastes Of Knowledge Work (DIMINISH)


Regular Team Standups

The regular team stand-up is a short, high-cadence meeting used to update the Visual Action Plan, identify delays, and continuously reconfirm the project schedule forecasts. The meeting can be held daily to weekly and can be as short as 15minutes. It should normally include the main team members, basically the people who work in the project enough to own a lane in the Visual Action Plan. There are often others whose role is small enough that their work is organized by main team members; those people normally do not need to attend the stand-up meeting.


Stop-Fix seems like a really interesting forcing function to work on the system rather than the work. It’s a way of saying long-term productivity is better than short-term productivity.

Stop-Fix guides the development of machines and processes to identify defects quickly and then stop the process until the conditions that caused those defects have been corrected. It is “Stop-Fix” that led to the famous behavior at Toyota whereby assembly workers would pull a cord to stop the line when they found a defect. Stop-Fix alarms are as applicable in knowledge work as they are on the factory floor. Stop-Fix is perhaps just common sense: in our work, we define the errors we cannot tolerate and then don’t tolerate them. While it may seem obvious, few people appear to grasp how to apply this simple principle. Stop-Fix alarms will be discussed throughout this text. So, does lean manufacturing work? There is virtually no doubt that it does. The first example is Toyota, a one-time insignificant automobile manufacturer which is today probably the most successful car company in the world. But that story took more than half a century to develop.
Granting that level of authority to assembly workers was unheard of at the time— not just because the rest of the world’s car makers didn’t think the people putting together their products had enough judgment but because stopping the line was expensive. [24]. —Joel Kurtzman, HBR


Chapter 1: 30% of what you think is wrong

Lean Thinking errors

  • Failing to define goals clearly
  • Failing to identify errors and resolve them
  • Failing to solve problems at their root
  • Failing to communicate with colleagues or customers

Most common and dangerous assumptions

  • This is how we’ve always done it and it works fine.
  • Someone I trust told me, so I don’t need to see it myself.
  • It seems logical, so it probably works.
  • It’s not working because other people are not trying hard enough.

Assumption qualities

A small misunderstanding of a customer’s need or a problem’s root cause can render a large effort entirely wasteful.
  • Right or wrong
  • Severity if wrong

Challenges with assumptions

You must make assumptions to function, but many of those assumptions will be wrong and you have no idea which ones.

Solutions to assumptions

The only way to find them is to experiment: measure the results and compare them to what you expected.
  • Experimentation

Chapter 2: A Brilliant Insight


This chapter presents evidence that lean thinking applies to knowledge work—that is, it works across domains, across a range of functions, and for organizations small and large. The discussion starts with a brief history of the birth of lean in Toyota in the middle of the 20th century. Using lean health care, the discussion then bridges from manufacturing to knowledge work; health care is unique in lean thinking because it has large portions of both operationally demanding procedures (those ideal for lean manufacturing techniques) and knowledge workflows that are among the most demanding of individual expertise. The discussion then moves to other proven areas of lean knowledge:

  • Lean product development derived mostly from the auto design industry
  • Lean startup, a method of managing entrepreneurship
  • Critical Chain Project Management (CCPM), one of the first structured approaches to lean knowledge work outside the auto industry
  • Agile Software Management, lean thinking applied to software product and IT development.

Lean In Knowledge Work

  • Lean health care [4]
  • Lean product development [5]
  • Lean entrepreneurship [6]
  • Lean organization management [7]
  • Lean sales [8]
  • Lean legal [9]
  • Lean accounting [10]
  • Lean nonprofit management [11]
  • Lean UX
  • Lean Analytics
  • Lean Branding

Creator Of Lean—Taiichi Ohno

Taiichi Ohno developed the production systems “that helped make the Toyota Motor Company one of the most powerful automobile producers in the world” [12]. He is sometimes called the father of lean thinking. His methods were used in Toyota, where they “helped transform Toyota from a small car maker near bankruptcy in the late 1940s into the third-largest auto maker” [12]. His wisdom in lean thinking is broad, which is why he’s quoted here so often. His contributions earned praise, including this small sample: “He ranks among the production geniuses of the 20th century,” said Michael A. Cusumano, Asst. Prof. at the Massachusetts Institute of Technology, an author on Japanese manufacturing. Norman Bodek, President of the Productivity Press (who translated Mr. Ohno’s books into English), said, “His contribution to modern manufacturing ranks with the work of Henry Ford” [12].
Lean thinking began at the Toyota Motor Company in the 1930s and 1940s. In the years after World War II, Japan’s economy was nearly destroyed. Toyota was producing cars in small numbers. For example, in the early 1950s, Toyota was averaging a few hundred automobiles per month, where as Ford and Chevy were each producing that many on a daily basis [13–15]. Toyota was forced to develop techniques that cut costs and raised quality without the massive economies of scale enjoyed by its Western rivals. Unable to spend its way to higher efficiency through tooling and other capital-intensive methods, Toyota began a journey that it is still on: continuously improving using the reduction of hidden waste to fund increased focus on customer value. Every company knows that there is a certain amount of hidden waste within its walls. The brilliant insight of Toyota was that there was so much hidden waste that the company could be transformed by reduction of this. Of course, it was hidden—ordinary thinking will remove revealed waste. But it was genius to recognize that most of what every person does every day creates waste.

Applying Lean To Knowledge Work

Reduced repetition is just one of many differences between factory and knowledge work; knowledge work has orders of magnitude higher reliance on tacit knowledge, takes longer to execute (often years to complete complex initiatives), and has obscure workflows. Yet there is an important similarity: knowledge work has subprocesses that repeat almost exactly, including: • approval processes; • progress reporting; • customer service contracts; • formal problem solving; • tracking metrics and key performance indicators (KPIs); and • patent and trademark applications.

Lean Product Development

Lean Startup


Critical Chain Project Management

Agile Software Development



This chapter has sought to provide a brief history of lean thinking and present evidence that lean knowledge works, and that it dramatically improves organizations in a broad range of domains. The remainder of the book will present a structured approach to lean thinking as it applies to knowledge work, along with dozens of tools and techniques to help you accelerate your journey in lean knowledge.

Chapter 3: Creating value from knowledge work


In this chapter, we will look at how a knowledge organization creates value for its customers. The connection of effort to value is complicated because of the large variety of value that knowledge work creates and the indirect ways in which end customers pay for them. But the connection is certain and those organizations that increase it enjoy substantial benefits over time: better customer and client experience, more engaging work, and ultimately better financial performance.


Knowledge staff create value in highly varying ways, from heads-down, diligent work to comply with the regulations to exciting moments of creating an innovative solution. And value traverses from the concrete metrics of delivering something to the schedule to sometimes a years-long journey to generate financial benefit. There are many things knowledge work does that cannot be monetized in the time frame necessary to aid a decision; for example, patents often reach their full value a decade after the patent is issued and, even then, are usually difficult to monetize. So, we will proceed understanding that our purpose is to create value, even though the quantification of value will often be subjective.

Chapter 4: The Lean Equation


Chapter 2 presented Taiichi Ohno’s brilliant insight that only a small portion of our effort creates value and the rest creates hidden waste. The lean equation takes us one step further: that we should separate all we do—every effort in every day—into two unambiguous classes, those that create value and those that create waste. This chapter will present the lean equation, the simple truth that effort is the sum of value and waste. It begins with a discussion about waste followed by differences between effort and value, two elements that are often confused. This leads to a discussion about opaque workflows, which are common in knowledge work. It ends by exploring the consequence of waste taking such a large portion of our effort: if we want a sustained increase in value, we should start not by increasing effort, but rather by cutting waste.

Effort vs Value

It’s commonly stated that 85% of the energy of an organization is spent generating waste.

Trying Harder Only Works Temporarily. It Doesn’t Solve The Root Cause, Which Is The Methodology

If we assume most waste comes from people doing their jobs poorly, our first inclination will be to push harder: to demand more time, to micromanage, or even to ridicule people for poor results. That approach can work in the short run, as shown in Fig. 4.4. Demanding people “try harder” may create a bump of effort and that effort may bring a temporary bump in value. But it doesn’t reduce waste. In fact, when people just try harder in a wasteful system, waste increases. And whatever modest gain is achieved is fleeting. As management’s focus moves to other areas over the weeks and months that follow, effort will likely return to its initial level.

Examples Of Waste

  • Arguing and complaining
  • Task switching
  • Working while tired
  • Half measures (not putting enough resources to projects / doing too many projects)
    • Resolving projects
  • Waiting for approval
  • Recovering from mistakes
  • Solving the wrong problems
  • Disappointed customers (communication, refund)
    • Defects
    • Over-promising in marketing
    • Poor experience
  • Too late
  • Customer support (confused customer accidentally specified the wrong thing or couldn’t get something to work or just misunderstood confusing instructions)
  • Damages from injuries to end users, clients, and patients
  • Staff worn out from dealing with waste
  • Miscommunication
  • Good employees leaving

How Waste Hides In Opaque Workflows

  • Most waste comes from good people trying to do the right thing.
  • People are generally unaware of the amount of waste their activities generate.
  • The people generating waste are often powerless to improve the workflow.

Three ways to expend effort in knowledge work

  • Creativity - Applying expertise to solve, invent, design, and evaluate
  • Diligence - Finishing what we started in a moment of creativity
  • Creating Waste -

A Sustainable Way To Increase Value



The first step in reducing waste is to recognize it. If we settle for the assumptions of Fig. 4.2, that everything is fine like it is, we will never see the waste that hides in plain sight. As Taiichi Ohno said, “If you are going to do kaizen continuously, you’ve got to assume that things are a mess” [7]. This chapter has presented the lean equation, a visualization of the relationship between effort, value, and waste. The lean equation is more mindset than math, helping us see the opportunity to direct our energy away from wasteful activities, and this will produce dramatic and sustainable increases in the creation of value. The next chapter will present the 8 Wastes of Knowledge Work to sharpen the ability of knowledge staff to identify the hidden wastes in knowledge work.

Chapter 5: DIMINISH—Recognizing The 8 Wastes Of Knowledge Work


Chapter 4 presented the idea that lean thinking is a journey of ever-increasing value made possible by relentlessly cutting waste. It madethe casethat because most of our efforts create waste, modest cuts in waste create large opportunities to increase value. The problem is that those opportunities are unseen because most of the waste we create is hidden. This chapter focuses on the skills needed to recognize the waste that “hides in plain sight” using the “8 Wastes of Knowledge Work,” a categorization of wasteful activities. The 8 Wastes of Knowledge Work are intended to create a common language and thus make it easier to identify and communicate about hidden waste.

The Wastes Of Lean Manufacturing

  • Defect Creation;
  • Overproduction (producing more than is needed or before it’s needed);
  • Waiting;
  • Transportation (of materials);
  • Motion (of workers);
  • Inventory; and
  • Extra Processing (spending resources on something a customer doesn’t value).
  • Unused Creativity
  • Stress
  • Uneven Workflow

Waste Diminishes Value

The central premise in this book is that waste diminishes value by stealing effort. In this view, the total available effort is constrained so that every hour that goes to waste is not available for creating value. Our starting assumptions are that knowledge staff are good at what they do, and that a lack of competence or dedication is rarely the upper limit to the value a team creates.

The 8 Wastes Of Knowledge Work


Teams working without coordination or in opposition to each other and/or to the larger organization
• misalignment with team leaders or other team members • misalignment to the organization’s leadership • misalignment to other functions within the organization • misalignment to the customer
• Lack of common purpose • Conflicting priorities • Sense of being excluded, lack of trust
• Lack of passion in knowledge staff • Work waiting on a support group • Bitter or persistent disagreements
1. Engagement Wheel 2. Five steps to high function 3. Socialization and sticky note aggregation

Information Friction

Oversized time or effort to move information from one part of the organization to another
• Interpersonal conflict • Fear of being found out • Physical distance • Disorganized information storage • Knowledge silos • Unintentional disincentives to share
• Frustration and misdirection from working “in the dark” • Waiting for information or approval • Someone in marketing who knows that there isn’t time to create a scheduled ad campaign, but keeps it quiet to avoid conflict. • A team in France that isn’t telling the team in Japan something because they don’t talk often. • Two service managers that don’t like each other and so hide facts to make the other look uninformed.
1. Single Point of Truth 2. Visualization Techniques 3. The Canvas View

More-is-Better Thinking

Being satisfied with progress vs achieving goals
• Easier at the outset • Seems safer than confronting a potential failure • Avoids accountability
• Delivering “ASAP” • Responding to delay by trying “harder” but without a goal • Accepting new work into an already overloaded system
1. Action Plans 2. Bowlers 3. Success Maps 4. Helicopter Views

Inertia To Change

Individual behavior (intentional or not) that slows the pace of change
• “We tried that and it didn’t work” is a common complaint. • Some people focus on similarities to past failed initiatives. • Some people may be unwilling to try a method they don’t fully understand.
• Lack of confidence • Aversion to change • Change is hard work • Hidden agenda
• Unwilling to commit • Avoiding accountability • Catastrophizing
1. New behaviors change culture 2. Change Model 3. Right sizing challenge vs skill

No-Win Contest

Demotivating the team by demanding unachievable goals
• Assumption that asking for more gets people to do more • Easy at the outset • Lack of trust and/or transparency in knowledge work
• Adding new priorities to team without negotiation • Systemic oversubscription of knowledge staff
1. See bottlenecks 2. Prevent oversubscription 3. Negotiate commitments 4. Escalation skills

Inferior Problem Solving

Solving the wrong problem or solving the right problem poorly
• Lack of diligence forming/managing problem statement • Lack of expertise applied to problem • Driving solutions without diligence
• Solving subordinate problem • Missing root cause • Ineffective or unsustained countermeasures.
1.“See it Broken” 2. Formal problem solving 3.Problem-Solve Canvas

Solution Blindness

Power through a solution even when the evidence suggests it’s not working
• Embracing a solution with insufficient or contrary evidence • Narrowing focus from strain • Sunk-cost fallacy
• Continuing a project or initiative when customer/user is unsatisfied • Unwilling to listen to other voices after starting down a path (Page 84).
1. "Watch it Work" 2. Trystorm 3. Minimal Viable Product (MVP)

Hidden Errors

Failing to build barriers to the hidden errors that are inevitable
• Difficulty accepting the likelihood of errors in one’s work • Difficulty of maintaining an experimental mindset
• Incomplete response to a need • Unvalidated assumptions and insights
1. Error containment 2. Stop-Fix error with playbook 3. Mistake-proofing


This chapter has presented a first look at the 8 Wastes of Knowledge Work and provided places to look for these wastes. Chapters 7–24 present dozens of waste-cutting tools and techniques from lean thinking, some well-known and some novel. But before we start reviewing individual methods, let’s frame a general approach structured along three dimensions: Simplify, Engage, and Experiment.

Chapter 6: Simplify, Engage, And Experiment


In Chapter 5, we discussed the 8 Wastes of Knowledge Work, a broad set of sources of waste. In this chapter, we will respond to those wastes. The responses are many, as demonstrated by the right-hand column of each of the eight diagrams in Chapter 5 that detailed waste (Figs. 5.2–5.9), but each can be viewed along three dimensions as shown in Fig. 6.1:

  • Simplify workflows: Reduce the effort required for a workflow.
  • Engage staff: Maximize and focus the effort of knowledge staff.
  • Experiment systematically: Constantly learn, adapting to new information, especially identifying gaps and mistakes in order to prevent their reoccurrence.

5 Ways Simplify workflows

  1. Eliminate ambiguous calls to action, often called “signals.”
  2. Shorten long task queues that leave open a large number of partially completed tasks.
  3. Simplify overly complex workflows.
  4. Speed up knowledge transfer, removing Information Friction.
  5. Remove unnecessarily varying workflows, where different people work in different ways without clear reasons.

Five common examples of waste that respond well to simplification

Ambiguous Signal
Long delay in receiving information
Stop-Fix alarms. Stop-Fix alarms are unambiguous signals that demand an immediate response, often within a day or two. Test Track. The Test Track is a simple visualization that measures early deployment such as the first few times a product or service is delivered to a customer or the initial use of a new workflow. It is a tool that helps the organization gain traction when something new is first deployed. Success Map. The Success Map creates a smooth continuum from the Action Plan early on in projects and initiatives, to the Test Track, which measures traction, and finally to the ultimate value the work provides, such as revenue or reduction in work product errors. Success Maps provide a clear path to success with a series of defined points for Stop-Fix alarms; this minimizes the effort for managers and leaders to identify issues, and thus maximizes the time to address those issues.
Information Friction
Long delay in receiving information
Visualize. Visualization speeds knowledge transfer by converting the knowledge from narration, usually the most tedious means of communication. Single Point of Truth or “SPoT”. Creating a Single Point of Truth for the knowledge staff and other stakeholders simplifies the process of collecting needed information. It also draws creativity and expertise from the whole team because it provides a comprehensive view for all. Canvas View. The Canvas View tells the whole story in one picture. When a person sees (literally) the whole context, understanding the flow of logic is dramatically easier. We will use the Canvas View extensively in this book.
Long Task Queues
1. Creates intrusive thoughts that make each of us less efficient, a phenomenon sometimes called the Zeigarnik effect. 2. Stakeholders and customers of the task are likely to ask for status updates; when tasks are inactive, status updates are wasteful.
Cut multitasking. Multitasking is a wasteful behavior that is demanded by workflows with many open tasks. Some level of multitasking is required in most knowledge work—for example, working on one thing while awaiting test results from another. However, more multitasking than is necessary creates waste because of the inefficiencies inherent in multitasking. Ruthless Rationalization. There is only so much work that can be done in a day. To ask for more than that is to oversubscribe, creating a No-Win Contest for each oversubscribed person. Rationalizing is a simplifying constraint for prioritization and “Ruthless Rationalization” is the practice of consistently rejecting oversubscription according to the following principle: never accept work that, when properly done, exceeds the team’s capacity. Just-In-Time Prioritization. Just-In-Time prioritization such as the Kanban board draws a sharp line between what’s active and what’s not, and “what’s not” needs no status updates. On-demand prioritization also pushes the decision for resourcing as close to the date work starts as possible, to ensure that the maximum amount of information is used in the decision.
Varying Workflows
Using workflows that take longer and are less effective than the best
Standardize workflows. Our primary means of reducing variation is creating standard ways to do common tasks such as approvals, reviews, and problem solving. The first step to create a standard is to study the ways the task is accomplished today, devising measures of waste in the workflow, and then selecting the method that has minimal waste. This brings an immediate advantage in that everyone uses the least wasteful method known. But this also leverages the entire organization: any user or stakeholder of the workflow can invest energy to improve it and then that improvement is deployed broadly to cut waste across the organization. Mistake-proofing. Mistake-proofing is the design of workflows so that common error modes are either prevented or so obvious that they stop the process until the error is corrected. A simple example is entering a credit card number on a modern commercial website. The error mode of entering fewer than 16 digits is prevented (the “Next” key can be disabled until 16 digits are entered), as is the error of the name on the card not matching the name entered (the sale is stopped until the name is corrected). Checklists and expert rule sets. Checklists and expert rule sets capture the wisdom of the organization. Consider the approval process, which can be improved first with mistake-proofing (for example, the approval template with key questions like “When is approval needed?” and “What budget will this expense be charged to?”). Of course, not all requirements are black and white. For example, the expected answer to a question like “Did you get two quotes?” might be yes, so an explanation might be needed if the answer is no. The template could then provide one or two guidelines on common cases where two quotes are not required. This thinking extends from a simple approval form to the most complex workflows of knowledge work. The more often experts and leaders write their advice down, the easier it is for those that follow them to learn.
Overly Complex Workflows
Root Causes 1. One reason is they are iterated, adding new requirements and not always removing outdated ones. (Page 92). 2. People often hastily bolt together workflows, unaware of how complex practical implementation will be; multiperson approvals are a common example, since getting five or seven people to review something can take weeks if each reviewer lets an email sit in their inbox for a just few days. 3.
Break workflows into multiple steps. When steps are overly coarse, they add complexity because each user must interpret for themselves what to do and how to check that it’s done well. When we break workflows down to a workable granularity, we bring consistency and simplicity. Enabling constraints. Enabling constraints can be added to simplify workflows and decisions. They work by removing from consideration any alternatives that do not meet the constraint. For example, Stop-Fix alarms are a set of demands that must be satisfied to turn “off” the alarm; there’s no need for the team to expend energy on solutions that fail to meet those demands. Control granularity. Workflows comprise multiple tasks to create work product. Controlling granularity means managing those task definitions so that all tasks are of about the same complexity. When highly detailed tasks are mixed with more general tasks, workflows become bloated.

Hawthorne Effect

Finally, as you search for the right place to expend effort, be wary of the Hawthorne effect: the tendency of people who are aware they are subjects of performance experiments to display a temporary improvement. The phenomenon was first recognized in the 1950s by Henry Landsberger. He analyzed a series of manufacturing productivity experiments that had been run decades earlier at the Hawthorne Works, which was part of Western Electric. The most famous experiments are those where worker productivity was analyzed at various levels of lighting. While the research was attempting to discover the relationship of productivity vs lighting levels, they demonstrated an improvement in productivity when lighting levels were changed, whether incrementally brighter or dimmer. Ultimately, it was the change in lighting because when lighting changed it revealed to people that they were being studied, and they strove harder [44]. More recent research has confirmed the effect, but has also discovered that it may have been overstated by Landsberger. Even so, the term is still used in industrial research to describe an unsustainable improvement in productivity, resulting from people who are aware they are subjects in a productivity experiment. When we create systematic learning, every person in the workflow is part of a continuous series of experiments. We are constantly measuring, comparing, and improving. Perhaps the original Hawthorne effect can be explained in part because people were more engaged during experiments—made part of the process to improve rather than simply workers doing what they were told. The Hawthorne effect adds a precaution to measuring improvement: don’t be hasty in accessing improvement from change. Real improvement will sustain over time, but the Hawthorne effect dissipates quickly.


The techniques in the following chapters present solutions that combine simplify, engage, and experiment to address common problems in knowledge work. Effectively addressing problems that constrain the organization will create sustained, relevant improvements. As shown in Fig. 6.14, over years waste will reduce so that more value will flow to customers. Consider a flooded field where water pools behind a series of bottlenecks. Water flow slows to a drip. As those bottlenecks are opened, the water flows faster and faster. Opening the bottlenecks didn’t create water; it merely allowed the water that was there to flow faster. Similarly, reducing waste doesn’t create capability in knowledge staff; it just frees the capability that was always there.

Chapter 7: Reduce Waste #1—Discord



Chapter 8: Reduce Waste #2—Information Friction



Chapter 9: Reduce Waste #3—More-Is-Better Thinking



Chapter 10: Reduce Waste #4—Inertia To Change



Chapter 11: Reduce Waste #5—No-Win Contests



Chapter 12: Reduce Waste #6—Inferior Problem Solving



Chapter 13: Reduce Waste #7—Solution Blindness



Chapter 14: Reduce Waste #8—Hidden Errors



Chapter 15: Standardize workflow

Standard workflow creates a single-best way to do the tedious parts of knowledge work, for example, the structure around solving problems or the details around approvals. It can seem dull, and certainly standardizing has its dull moments, but not nearly as many dull moments as work without standards: renegotiating tedious steps again and again followed by the useless innovation to reinvent something tedious; and then, recovering from the inevitable mistakes of the reinvention. What makes standardizing inviting is how we can do something tedious in a tenth of the time it used to take and so use the saved time on something that fascinates us: innovation, mastering a craft, nurturing a budding leader, or delighting a customer.
Before a knowledge organization can start its first cycle of improvement, there must be a foundation from which it can take that first step: the ability to execute repeated tasks in the same way. That begins with the simple step of identifying the best way we know today and using that best way each time we do a task. This is standard work.


  • Creates clarity that allows the people doing the work to improve the process. When the organization is diligent in documenting the standard way to do something and that standard way doesn’t work, it’s quickly seen that that standard is the problem. When that way is not defined, it’s easier to blame the person doing the work, or the management, or bad luck. In this way, standard work, whether on the factory floor or in knowledge work, allows people doing the work to see gaps, make changes, and observe improvement. Standard work is just the guidelines created and maintained by the people doing work for the people doing the work.
  • Addresses the least creative parts of our jobs, making them easier, and that allows more time for those parts of the job that require creativity.”
  • It becomes a force multiplier for managers. If you are a manager, consider how much time you must invest in “normal” work. Do you have to call a lab three times to expedite results? Do you have to write emails to get approval for something common? Do you frequently have to ask people on your team what they are working on or how long it will be before they are done? These are all examples of things that could be managed better through standard work. These activities waste your time and create tension: you might be annoyed that you have to ask for something people should know to do, and the recipient of that type of attention may be annoyed with what appears to be make-work or micromanagement. As the team moves to the model of Fig. 15.2, the efficiency of all involved goes up. This now frees the manager’s time and energy to those things managers should be focused on, for example, resourcing decisions, dealing with exceptions through a review process, and, of course, finding the next area to improve.


It steals creativity, turning people into automatons, mindlessly doing work they used to enjoy. In fact, standard work addresses the least creative parts of our jobs, making them easier, and that allows more time for those parts of the job that require creativity.
In traditional “top-down” thinking, process may have been pushed down from the management and then used to blame people when things didn’t go well. In lean thinking, standards make requirements clearer and provide more opportunity for driving change. In traditional thinking, process creates paperwork—useless instructions and make-work reports. In lean thinking, standard work is a lightweight mechanism to build a foundation that empowers everyone to improve upon it. Standard work also flattens the organization: “No one is above the standards we created!” When done well, standardizing builds relationships among the team because all pull together, all doing things the same way so that over time they can (1) find what works and do more of it and (2) find what doesn’t and get rid of it.

How To

Collaboratively figure out what works:

  • Begin with what people actually do, not what they should do.
  • Define the standard
  • Identify problems with the standard
  • Improve the standard
  • Keep the standard updated
  • Observe improvement

How Not To

  • Forced
  • Standards don’t work

Application Nuances

Start with what people actually do, not what they should do

Even when there is a documented workflow, organizations usually discover that what people actually do differs from what is written down. This is a common vestige of traditional management: a supervisor or designated expert may have documented a process that he or she felt the team should execute. That documented process may have poorly represented what the team did at the time or it may have been initially accurate, but was not updated as the process changed.

Resolving multiple ways doing the same thing

Some organizations will, unintentionally, do the same things in different ways. This can happen when teams are merged together through acquisitions, or when multiple teams started with a common process and then drifted apart over time. Normally, the long-term goal is common process across the organization. However, if the current state has multiple processes, there are potential negative effects of quickly forcing all teams together. If a manager dictates all teams will use the process used by one of the teams, it’s just another form of forcing solutions down from the top, something we avoid in lean thinking. If the management directs the teams to “settle it themselves,” demanding they come to consensus on which process to move forward with, it may create unhealthy competition as teams battle, each promoting their own methods. Often the best alternative is to drive change methodically: narrow the scope to select the most urgent need around one of the process variants. In the initial improvement cycle, focus on one team, but include a few people from other teams. Over time, future improvement activities can expand and gradually create a common process across the organization. This can increase harmony among the teams, but has the disadvantage of taking longer to complete.

It’s not enough to simply document the system, you also have to create an application system

Another analogy is a complex process familiar to almost every adult: managing traffic speed. In this analogy, the “organization” is the state Department of Motor Vehicles (DMV) plus all the drivers in the state. Driver workflow (roughly, the “recipe”) is mostly to stay within posted speed limits. Of course, simply posting speed limits is inadequate to manage vehicle speeds. Consider the other things the state does to ensure drivers remain within the speed limit: • Requiring driver’s school and licensing. This is the training and certification to qualify a person to execute the workflow. • Requiring a speedometer in vehicles. The speedometer is the scorecard used by the driver to help determine if he or she is within the speed limit. • Equipping law enforcement with radar speed detectors. This forms a reporting system used to gather information on a vehicle’s speed. • Issuing and enforcing speeding citations. Speeding tickets are the countermeasures most often used to bring the process back to within specifications. Other countermeasures include increasing insurance rates for those caught speeding and statewide point systems where too many violations over a period of time result in license suspension and other penalties.

A more general picture of organizational process for the ground view can be seen in Fig. 15.2.


Chapter 16: Workflow Improvement Cycle



Chapter 17: Workflow—Checklists And Expert Rule Sets



Chapter 18: Workflow—Problem Solve-Select



Chapter 19: Workflow—Visual management for initiatives and projects

Initiatives in knowledge work regularly encounter unexpected events. Accommodating those changes in a 4- or 8-page Action Plan is exceedingly difficult because of task interdependences. The result is that long Action Plans fall quickly out of date; if that happens, the results are almost always disappointing.

Visual Action Plan

Our solution here is the Visual Action Plan, a visualization that displays the same task parameters as a traditional Action Plan but much more efficiently. The visualization allows you to represent perhaps 5 the complexity for the same effort and in the same amount of space.
The Visual Action Plan is based on the swim lane diagram, which is commonly used in manufacturing. The primary difference for project planning is placing calendar time on the horizontal axis [10, 11]: the left and right sides of the task represent its start and end date (respectively), so that the width of a task represents its duration. Dependencies can optionally be shown with leader lines, something that is particularly helpful for the most important connections. Trying to show leader lines for every connection can create a spider’s web that adds little to understanding because of the many, ambiguous dependencies common in knowledge work. Notice that Fig. 19.5 has no leader lines, which is an alternative I have also seen work: the dependencies are simple enough that the team can keep track of them from memory.

Chapter 20: Workflow—Visual Management With Buffer



Chapter 21: Workflow—Kanban And Kamishibai: Just-In-Time Rationalization



Chapter 22: Workflow—Putting Out “Fires”



Chapter 23: Workflow—Visualizing revenue gaps



Chapter 24: Workflow—Leadership review of knowledge work


In this chapter, we will discuss a few techniques that can improve leadership review of knowledge work. This review is typically carried out by a team of leaders who together bring a great deal of experience and acumen, though they normally have less domain expertise than the people carrying out the work they are reviewing. For example, a product development team might have their work occasionally reviewed by a management team composed of functional leaders from Operations, Finance, Customer Service, Applications Engineering, Sales, and General Management. Those people cannot normally direct the expert in their area of expertise, but they can test the critical thinking by comparing work to their experiences: has the customer been involved enough? Is the value of the work clear? Are we doing enough to ensure compliance with regulatory bodies? So, the review is a partnership between knowledge staff, who bring expertise and transparency, and the leaders, who collectively bring decades of experience to the table.


This chapter has presented severaltechniquesto servethose providing leadership review of knowledge work. Leadership teams bring experience and acumen, and though they may have less domain expertise than knowledge staff, they can nevertheless bring substantial increased likelihood of success by identifying Hidden Errors. Doing these reviews well not only can improve the performance of the organization by stripping out expensive errors and omissions, but also can increase engagement with knowledge workers by teaming up with them to improve their work. As knowledge staff engage in the process, transparency and diligence will increase, improving the effectiveness of the review over time. Part of the benefits of good leadership review is to simplify preparation with clear requirements and standard format (see Fig. 24.9). The Engagement Wheel for leadership review shows that strong leadership review inspires a team who knows their work will be honed by senior people finding errors before those errors escape. They can feel connected to leaders who spend their time and energy to improve the work of their organization. Tough reviews will create a meaningful challenge—for example, to pass the first time—so long as reviews are fair. They will protect the organization by preventing errors from escaping that could damage profitability, quality, and customer relationships. Experimentation with leadership review can be done by measuring the value of projects approved, for example, quantified by estimated future revenue of the work.


Knowledge work



what customers are willing to pay for goods or services.



Value creation is often divided into two facets:

  • Direct: what the customer is willing to purchase
  • Support: what work must be provided to make that purchase possible.

At the auto repair shop, customers are willing to pay for a brake pad being replaced; most are unwilling to pay a separate line item for booking an appointment. But people are willing to pay for appointments in the form of overheads, which is one reason why customers willingly pay more for the repair than the sum of the parts and the mechanic’s wage—so they will pay for appointments and heating and annual taxes, just not as separate line items. This distinction between direct and support is important in much of lean manufacturing, but it’s less important in knowledge work. While a slice of knowledge work is for direct value creation—for example, physicians caring for patients and attorneys representing clients—most of it is indirect.

Facets Of Value

  • Fit for purpose: Work that’s done well enough to meet the need.
    • Example measures: # returns, # complaints, % win ratio, defective parts-per-million (ppm)
  • Profitable: Financial reward for the organization resulting from work product.
    • Example measures: high revenue and lower costs
    • Example measures: currency, % margin, % growth, ROI
  • On-schedule: Providing a product or service when the customer needs it.
    • Example measures: days late, % tasks finished on time
  • Innovative: Products and services that meet real customer needs in creative and differentiated ways.
    • Example measures: newer products/services taking share or commanding higher-than-average price, industry innovation awards, customer surveys
  • Protected and compliant: Meeting requirements of regulatory agencies and standards that customers value; protecting intellectual property (so the competitors have more to comply with!).
    • Example measures: # compliance issues, compliance cost, # patents

End Customer


Since value is based on the perception of the customer, we must know who the customer is. On the factory floor, the customer is usually defined as the end customer: the person or organization that purchases products.

Internal customer


The primary customer for knowledge work is probably the person who determines when the work product has met the need.



An organization is a group of people aligned to accomplish a defined set of purposes.


  • The Ford Motor Company is an organization. So is the 15-person sales team at a Ford dealership in Saginaw. So is the state government of Michigan.

Knowledge Organization




Opaque Workflow


Workflows where the creation of value is unclear, where everyone doing the work has a different understanding and those outside the team may not have the first idea what happens.

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