Author

Ideas To Double Click On

The 1900s Productivity Paradox

The Digital Age has failed to produce meaningful, measurable productivity gains in knowledge work despite the adoption of office technology—from the 1960s on. The causes of this phenomenon have defied detection since at least the 1980s. In recent decades it has been known as the “productivity paradox.” However, the same paradox is documented in the early 1900s, when offices adopted precomputer technology.

The Three Pillars Of Industrialization

These principles are ubiquitous, underutilized, and timelessly valuable:

Standardization. This exists at multiple levels. There’s the interchangeability aspect we’ve mentioned with the Bureau of Standards and all those nuts and bolts. But there are also reference standards (think of BluRay, Bluetooth, etc.). There are interoperability standards, such as communications for emergency workers and air traffic control. At a large insurer, by contrast, call center workers used no standards for recording the reasons for inbound calls. Of course, this caused chaos. But this chaos went unnoticed because that’s just business as usual in the world of knowledge work.

Specialization. Specialization applies equally to machines and workers—and that includes all workers, especially knowledge workers and their intangible tasks. The easiest way to think about it is to imagine the number and diversity of tasks performed by a worker or a machine. For handmade shoes, for example, a single cobbler might perform all or most of the tasks. As shoemaking is specialized, different machines might perform a single task, alongside workers doing the same. The fewer tasks performed by a single worker, the more productivity rises. And interestingly, the largest gains are often the first. When assembly lines were first introduced in manufacturing, it was not unusual to see a 50 percent increase in productivity on the very first day!28 Most people are surprised to learn that knowledge work, and mathematics in particular, was one of the first areas to adopt Smith’s doctrine and benefit from specialization. Around 15 years after publication of The Wealth of Nations, Gaspard de Prony was busy with a team of mathematicians developing a set of logarithmic tables for publication by the French government. Anxious to finish quickly and economically, he hired a wide range of mathematicians of varying skills and wage rates. He assigned the most skilled to oversee entire calculations while more economical, lower-skilled workers toiled with simpler, underlying math work. Four decades later, Charles Babbage cited this work specialization by Prony as helping to inspire his vision for the first mechanical computers, which he designed in the 1830s.29 And yet today, almost two centuries later, knowledge workers confidently continue to insist that their simplest tasks cannot be standardized and similarly specialized. And their management executives defer to this misperception.

Division of labor. Smith talked about the people drawing out wire to make pins. But the division of labor can be further subdivided: There’s . . . 1. Division of work. Think of the ancient Egyptians dividing work on the pyramids among skilled craftsmen, artisans, stonecutters, and porters. That’s the same way today’s general contractors and subcontractors divide work. Next there’s . . . 2. Division of job positions. Think of a factory where the work is divided by job—like a machine shop. Each machinist performs groups of activities and is responsible for the quality of the output. Even the cavemen’s flint-tool lines are examples; it’s really a workroom with craft or artisanal workers who design their own “bundles” of activities and methods (like knowledge workers today). And then there’s . . . 3. Division of work management. This is what can be called the “specialization of specialization.” It occurs when the design of production is removed from the workers and transferred to a “specializer.” In factories, the task of specializing labor became industrial engineering (i.e., a specialty). But knowledge workers, like the cavemen toolmakers above, generally retain the “decision rights” to design their own production methods. That’s because of . . . 4. Division of perception. This has not been widely adopted within businesses. The perception of what work can be feasibly standardized is still as uncontrolled and autonomous as a century ago, when the U.S. market was crowded with a million ax models. The same is true today: no one is taking inventory of countless one-off perceptions in the business. But just like Herbert Hoover, executives could mandate that the perception of knowledge work activities be standardized and documented. And then industrial engineers could go to work industrializing the million unnecessarily different ways that knowledge workers perform tasks as simple as chopping wood: reconciliation, reporting, reviewing, and more.

Contents

Part 1: The Problem

Chapter 1: Where Is White-Collar Waste Hiding? In Plain Sight!

The numbers are shocking. Today’s knowledge workers waste a third of their day, every day, on activities that could be reduced, consolidated, or eliminated altogether... This is “virtuous waste,” a catchall phrase for the types of well-intentioned error correction, review, rework, overservice, and needless variance that permeate virtually every aspect of knowledge work operations today.

Source: This figure, based on The Lab’s experience, analysis, and benchmarks, excludes service workers (e.g., food, retail, transportation, hospitality).

Chapter 1 Takeaways

1. White-collar, office, or knowledge work is vaguely defined as nonroutine problem solving that requires creative thinking. Wasted effort in knowledge work receives scant attention.
2. Knowledge workers waste a third of their day, every day, on activities that could be streamlined, consolidated, or avoided altogether. For the Fortune 500 in 2017, the overlooked costs are stunning: • 20 percent of earnings • $3 trillion in shareholder value • Almost equal to the combined value of Facebook, Apple, Amazon, Netflix, and Google, or FAANG
3. Knowledge work waste has characteristics that help it pass virtually unnoticed:
1. The root causes are misperceived as “unavoidable.”
2. Remediation is rationalized as valuable, even heroic: “virtuous waste.”
3. Work activities are misperceived as unique, thwarting investment in standardization.
4. Knowledge work is ripe for application of the time-tested principles of industrialization:
1. Standardization
2. Specialization
3. Division of labor

Chapter 2: Did You Notice That Your Most Valuable Assets Have Shifted?

• The 40-year period from 1975 to 2015 saw the vast majority (70 percent) of business value migrate rapidly:
• From tangible assets, mostly property, plant, and equipment
• To intangible assets, mostly “economic competencies,” or knowledge work methods
• Newly emergent intangible assets are neither well defined nor widely understood:
• Definitions are negative, describing “what they are not.”
• Accounting rules require most intangible assets to be classified as “expenses,” i.e., costs.
• Most assume intangible assets are limited to patents, trademarks, etc.
• The largest category (>70 percent) of intangible assets, “economic competencies,” is made up of loosely standardized knowledge work operations and methods:
• Databases and information
• Knowledge and know-how
• Practices of managers and workers
• The “anti-standardization bias” obscures perception of valuable opportunities to “industrialize” knowledge work competencies: two-thirds of knowledge work activities are similar and repetitive, ideally suited for standardization, specialization, and division of labor.

Chapter 3: How We Got Here - The Long Journey To Myopia

It argues that since time immemorial, there has only been one improvement in business, and that improvement is industrialization: standardization, specialization, and division of labor.

Chapter 3 Takeaways

• Breakthrough productivity gains are conventionally perceived as the adoption of breakthrough technologies—the multiple, big-rock theory of improvement.
• The Steam Age
• The Electric Age
• The Digital Age
• The Digital Age has failed to produce meaningful, measurable productivity gains in knowledge work despite the adoption of office technology—from the 1960s on.
• The causes of this phenomenon have defied detection since at least the 1980s.
• In recent decades it has been known as the “productivity paradox.”
• However, the same paradox is documented in the early 1900s, when offices adopted precomputer technology.
• An alternative, one-rock theory argues that industrialization is the single, timeless method for improvement—only the enabling technologies change. Implications:
• The productivity paradox is lastly a technology problem.
• Secondarily, it is a management problem.
• First and foremost, it is a perception problem.

Part 2: The Solution

Chapter 4: Finding—and Fixing—Your Business’ Biggest Blindspots

Chapter 4 Takeaways

• Layers of cognitive biases and misperceptions are hardwired into the human brain, posing two types of costly problems for business:
• They upend simple, painfully obvious notions, such as the principle of least effort.
• They persist because humans are biased to believe they are less biased than others.
• Within knowledge work, cognitive bias offers valuable, predictable improvement opportunity in three categories:
• Fundamental perception and observation, e.g., of operations, markets
• Logic and reasoning, e.g., avoiding false trade-offs
• Methodologies and tools, e.g., documentation errors, tribal knowledge
• Manufacturers have overcome these biases by industrializing their production and distribution operations. However, all “unindustrialized” knowledge work operations represent a major competitive vulnerability—for manufacturers as well as service providers.

Chapter 5: Transforming Your Business Into A Knowledge Work Factory

Chapter 5 Takeaways

• Four essential elements of industrial work provide the building blocks for the foundation of the knowledge work factory:
• Capacity
• Processes
• Work activities
• Products
• All four elements are currently in place within knowledge work operations and, at large scale, viewed from a distance, represent “a spectacle to behold.” But close scrutiny reveals vast inefficiencies and improvement opportunities. Analogies include:
• The American System of Manufacturing, late nineteenth century
• The anthill analogy
• Three interconnected perceptual errors related to the overconfidence bias obscure visibility of the four elements and the knowledge work industrialization opportunity:
• Oversight
• Denial
• Rationalization
• The widely held belief that the competitive marketplace unfailingly adopts valuable innovations (“better-mousetrap dogma”)

Chapter 6: What’s The Capacity Of Your Knowledge Work Factory

• The first organization chart, developed for a railroad in 1855, far surpasses most modern charts and even functions as an early knowledge work factory by:
• Visualizing the entire business (largest in the United States at the time)
• Defining management roles, decisions, and asset responsibilities
• Quantifying organizational capacity clearly and unmistakably
• Defining data flows for performance reporting and “product” definition
• More than a century of subsequent organization chart innovation attempts have failed to meet or exceed the functionality of this original chart. These efforts offer lessons that point out costly flaws in organization design to be avoided.
• Improvements in today’s typical organization charts provide two near-term advantages for knowledge work improvement:
• Deliver the first of four essential elements needed for “industrialization”—capacity.
• Produce meaningful operational improvement benefits that begin within 30 days.

Chapter 7: Recognizing The Hidden Products Your Knowledge Workforce Builds

• Although knowledge workers deliver numerous “work products,” they prefer to perceive that they deliver “services,” shunning simple, proven, product-based management methods used by manufacturers.
• Decentralized, informal knowledge work management methods create staggering levels of costly, ever-increasing—and avoidable—operational complexity:
• Work product proliferation
• Business process mutation
• Fragmented accountability
• Stranded expertise
• Overwork: “working below one’s pay grade”
• The avoidable “false complexity” of knowledge work impedes the success of industrialization efforts (e.g., shared service centers, outsourcing, centralization) that depend on standardization, specialization, and division of labor. 4. Knowledge work organizations can adopt bills of materials to gain product-based management capabilities that avoid the “false complexity” eroding effectiveness: • Formal product definitions and inventories
• Instructions for production
• Capacity estimates for planning • Data for costs and productivity

Chapter 8: Building Your Own Knowledge Work Factory

• Create a basic knowledge work factory by simply dividing work products into the relevant organizational capacity—but dive down to individual-employee productivity levels, similar to a conventional factory.
• When individual knowledge worker performance is measured and analyzed, several unexpected and unconventional insights typically emerge:
• Wider variance—Compared with summary-level performance figures, i.e., organization-wide, individual performance varies significantly for identical work. Top-quartile workers’ performance can often average 2x to 7x that of bottom-quartile workers.
• Lower efficiency—This wide variance often consumes 15 to 25 percent of organizational capacity, delivering an unexpectedly costly operational efficiency penalty.
• Surprising effectiveness—High productivity in knowledge work operations often delivers higher effectiveness, as well as higher efficiency. Conventional perception often frames these objectives as mutually exclusive, i.e., a false trade-off.
• The best way to close the individual variance gap is to begin by adopting Frederick Taylor’s methods for recording and transferring best practices from high performers to low performers. But don’t stop there—see #4, below, for the next step.
• Achieving “better-than-best-practice” performance requires adopting Ford’s methods of work-activity-level improvement:
• Redesign,
• Elimination
• Standardization
• Automation (addressed in more detail in subsequent chapters).

Chapter 9: Optimizing Your Knowledge Work Assembly Lines

• Absent breakthrough technology, the limits of knowledge work improvement are conventionally—and falsely—perceived to be current “best practices.”
• Manufacturers routinely shatter this barrier to achieve “better-than-best practice” without breakthrough technology:
• They consistently challenge conventional perceptions with direct observations by diverse executives and managers, e.g., Gemba walks.
• They define—and redefine—business processes more broadly to encompass more end-to-end, cause-and-effect improvement opportunities.
• They formally document business processes and the relationships between them to create comprehensive taxonomies or hierarchies.
• They focus on improving activities through standardization, specialization, and division of labor—industrialization.
• All these methods can be adopted by knowledge work organizations, once the numerous definitional “disconnects” are reconciled—particularly between IT and business operations.

Chapter 10: Analyzing And Simplifying Knowledge Work Activities

• Three potent organizational challenges impede the efforts of knowledge work organizations to identify, analyze, and manage their operational work activities:
• y xLack of data—few characteristics, such as definitions, volumes, and locations, are routinely recorded.
• Decentralized decision rights—individual employees can design their own work activities.
• Cost-accounting failures—prior activity-based costing efforts can undermine new efforts to manage activities.
• Contrary to widely held misperceptions, knowledge work activities are not unmanageably unique. Similar to manufacturing, these tasks and related improvements can be concisely defined with:
• Roughly 18 to 34 unique activities
• Approximately 25 root causes of improvement
• No more than 500 total operational improvements
• Best practices from manufacturing can be easily adapted for knowledge work activity management:
• Standardized hierarchies for universal descriptions
• Normalization protocols for verb-noun descriptions
• Reconciliation of activity-time intervals with relevant organizational capacity

Chapter 11: Turbocharging Your Knowledge Work Factory

• The management capabilities delivered by the knowledge work factory (Chapter 8) can be enhanced—turbocharged—by using the work activities from the business process maps.
• The Activity Cube provides a simple way to inventory, reconcile, measure—and automate—the four basic operational elements of the turbocharged knowledge work factory:
• Organizational capacity
• Work products
• Business processes
• Work activities
• Knowledge work operations can achieve similar breakthrough gains in productivity as manufacturers, by using similar industrialization methods—but without similar capital investment.
• The Productivity Quad is a simple matrix for categorizing work activities for two fundamentally different improvement strategies:
• Eliminate. Virtuous waste activities
• Automate. Value-added activities (semiautomated, manual)

Chapter 12: Managing Industrialization

• Implementing a KWF requires changing the organization’s conventional, intuitively biased perception. Plan a strategy well suited for initial dismissal and persistent skepticism of the notion.
• A successful implementation management strategy can use counter-intuitive methods to most effectively achieve three major milestones:
• Avoid dismissals—Playing “not to lose” is the best way to navigate around the inherent dismissal bias typical of most organizations and achieve success incrementally.
• Reconcile perceptions—Diverse, passionately held perceptions of existing operations can be reconciled promptly and efficiently with a simultaneous group review of highly detailed current-state maps, i.e., the Process Map Fair.
• Preempt objections—Almost all organizational objections are highly predictable and can be preemptively minimized with simple tools and techniques.
• The most costly management mistake is agreeing to a “false ceiling” of benefits targets. Instead, agree to a “minimum floor” for benefits and leave the upside potential unconstrained.

Models

Mini Mental Model Encyclopedia

Activity Cube

Activity Cube

Other Summaries

Presentations

Author Interviews

Contents

Highlights

Kindle Popular

Goodreads Popular