Introduction: Just Another Day at the Office
Part I: The Problem
Chapter 1: Where is White-Collar Waste Hiding? In Plain Sight!
• What do a financial-services company and a tire manufacturer have in common?
• Why do 20 percent of earnings go missing—and unnoticed?
• Test your knowledge: three “spot the waste” stories.
• Introducing the concept of “virtuous waste.”
Chapter 2: Did You Notice That Your Most Valuable Assets Have Shifted?
• Buried in Babylon: the difference between tangible and intangible assets.
• Competencies: mundane work activities that are worth a fortune.
• Why your greatest assets remain unrecognized and underproductive.
• How unique is your business? Understanding the anti-standardization bias.
Chapter 3: How We Got Here: The Long Journey to Myopia
• Thirty thousand years of productivity improvements—in just five minutes.
• Should technology drive work activities—or the other way around?
• Why has knowledge work failed to improve when other work has wildly succeeded?
• The Industrial Revolution, “big rocks theory,” and the productivity paradox.
Part II: The Solution
Chapter 4: Finding--And Fixing--Your Business' Biggest Blind Spots
• Perceptive biases that trick your brain into giving you incorrect information.
• Logic biases, flawed rationalizations, and profit-robbing false trade-offs.
• The “principle of least effort”: not as simple as it sounds.
• Powering past your blind spots: techniques for “seeing the unseen.”
Chapter 5: Transforming Your Business into a Knowledge-Work Factory
• The immutable elements of industrial—and knowledge—work.
• Three perceptual errors that make the brain ignore these elements.
• The “better mousetrap dogma”: market-based suppression of business innovation.
• Touring the anthill of knowledge work operations.
Chapter 6: What's the Capacity of Your Knowledge-Work Factory?
• The rise and (mostly) fall of org charts: an unmatched masterpiece from 1855.
• How knowledge labor-cost data go missing—and where they’re hiding.
• Why knowledge workers believe they’re “exempt” from productivity management.
• Five lessons from a century of failed organizational theories.
Chapter 7: Recognizing the "Hidden Products" Your Knowledge Workforce Builds
• Taking inventory: the overlooked products your knowledge workers create every day.
• How “false complexity” erodes productivity—and impedes standardization.
• Lessons from the factory floor: adapting product-based management to knowledge work.
• A finance department case study: best intentions, worst outcomes.
Chapter 8: Building Your Very Own Knowledge Work Factory
• Beginning with basics: capacity and work products.
• The 1914 productivity death match: Frederick Taylor vs. Henry Ford.
• Separating the management of work from the performance of work.
• Reducing variance to boost productivity up to 30 percent—without technology.
Part III: The Turbocharge
Chapter 9: Optimizing Your Knowledge Work Assembly Lines
• “The five maybes”: a simple path to business-process improvement.
• How to outachieve the overachievers to reach better-than-best- practice performance.
• Why today’s knowledge work is tragically under-automated.
• Documenting and managing predictable patterns in business processes.
Chapter 10: Analyzing And Simplifying Knowledge Work Activities
• Overcoming the three challenges to activity-level knowledge work improvement.
• The “periodic table of knowledge work activities.”
• Which work activities are “unique”? Shattering a longstanding misperception.
• Tales of terror: real-world examples of hidden waste (with happy endings).
Chapter 11: Turbocharging Your Knowledge Work Factory
• Doubling and redoubling productivity, one wrench-turn at a time.
• A spreadsheet/robot smackdown.
• The Activity Cube: reconciling four “views” of operations.
• Vendor hype versus reality: how much can you actually automate?
Chapter 12: Managing Industrialization
• Counterintuitive strategy: how to win by playing “not to lose.”
• Crossing the void: three strategic milestones.
• Building your knowledge work factory: a two-phased approach.
• Demons of the deep: how to avoid common implementation traps.