Abstract and Keywords
This chapter introduces Frederick Winslow Taylor's system of scientific management, which was achieved through the application of knowledge to work. It shows that there has been an information technology (IT) revolution, despite the failure of Thomas Friedman, along with many others, to understand its full significance. The chapter discusses mechanical Taylorism, which states that the application of knowledge, not muscle power, is the source of productivity. It then moves on to consider digital Taylorism, where the knowledge of technicians, managers, and professionals is translated into working knowledge by codifying, capturing, and digitalizing their work. The chapter also looks at the industrialization of knowledge work and considers the future of knowledge work.
Industrial revolutions are revolutions in standardization.
Standardization in terms of IT has become huge…not only standards for a single customer but across countries…technology is the ultimate equalizer…it will drive globalization, drive change…I hope that people don’t get reduced to the state of drones…but I think increasingly employment will shrink.
—Chief Information Officer, Financial Services
THE OPPORTUNITY BARGAIN rests on an upbeat view of the future of work where a growing number of Americans will do clever and complex things to earn a living in the global economy. Much of the business literature has focused on how companies should develop their human capital to create innovative ideas, products, and services to take American companies forward. Peter Drucker, a highly respected management guru, argued that the source of productivity in a knowledge-driven economy was different from an earlier age of mass production. Then the revolution in productivity, which he credited to Fredrick Winslow Taylor’s system of scientific management, was achieved through the application of knowledge to work.2 It was the organization of factory production based on the moving assembly line (p.66) that created the mass production of autos, TVs, and washing machines and fueled the consumer boom of the 1950s and 1960s.
In today’s knowledge economy, Drucker believed that competitive advantage has come to depend on the productivity of knowledge—using existing knowledge to create new knowledge.3 The use of existing ideas to create new ideas also required a change in the role of management from responsibility “for the performance of people” to responsibility “for the application and performance of knowledge.”4 This is why knowledge management has become a key business issue. Thomas Friedman adds weight to the idea that America’s competitive advantage depends on creativity, innovation, and a highly skilled workforce, as the full force of the hi-tech revolution remains nascent. In The World Is Flat, he suggests that “the last twenty years were just about forging, sharpening, and distributing all the new tools with which to collaborate and connect. Now the real IT revolution is about to begin, as all the complementarities between these tools start to really work together to level the playing field.”5
This chapter will show that there has been an IT revolution, but Freidman along with many others have failed to understand its full significance, especially for college-educated workers. Corporate survival will depend on the creation of new markets through innovative products and services, but the global IT revolution has presented companies with new tools, of a digital rather than mechanical kind, to improve performance in much the same way that it was applied to mass production through the application of knowledge to work.6 Companies may continue to pay a premium for outstanding talent, however it is defined, but they are increasingly segmenting their knowledge workers in an attempt to know more for less. Although some are given permission to think, increasing efforts are being made to translate knowledge work into working knowledge where what is in the minds of employees is captured and codified in the form of digital software, including online manuals and computer programs that can be controlled by companies and used by other often less skilled workers.7
This follows a well-established trend where the gale of creative destruction is followed by the destruction of the creative. Today’s innovations are tomorrow’s routines, which is why Jay Tate’s observation that “industrial revolutions are revolutions in standardization” is a telling insight into the source of productivity. The productive potential of steam engine technology took 200 years to realize after Thomas Savery patented the first steam powered pump in 1698.8 It was the development of the factory system that brought together workers, supervisors, (p.67) machines, materials, and steam power into an integrated unit of production based on the introduction of standards of time, behavior, and techniques that led to rapid improvements in productivity.9 The same process of rationalization is now taking place in many of the industries currently associated with the knowledge economy, such as information technology, financial services, legal services, and pharmaceuticals. Although the rationalization of knowledge work may increase the productivity of knowledge, it will also have profound implications for the relationship between education, jobs, and rewards.
When considered in its historical context, this should come as no surprise. Productivity has not come from giving people permission to think but from imposing barriers to individual initiative and control through a detailed division of labor. Dating back to Adam Smith, there was a view that the prosperity of workers and nations depend on breaking down jobs into routine activities that did not call upon even a rudimentary intelligence. Although this was presented as a choice between prosperity or poverty for ordinary workers, it can also be viewed as a conflict between capital and labor because the issue of employee discretion and power is closely related to that of rewards—how the spoils of productive growth are to be distributed, especially among shareholders, executives, managers, and the rest of the workforce.
There is an assumption that the more companies depend on knowledge workers, the greater share of profits will go to these workers, ending the age-old struggle between the interests of capital and labor. This is not the first time this has been proclaimed, as we shall see in the following discussion of Taylorism. But the growth of knowledge work creates new tensions, if not outright conflict, between the many sides of industry because it has the potential to transform existing patterns of ownership and control. The key assets of knowledge-intensive companies shift from the ownership of physical assets such as land, factories, or machines, where property rights are clearly defined, to intangible knowledge-related assets, where property rights are less clear cut.10
In a system where the interests of shareholders are given priority over all other interested parties, including employees, questions of who controls, owns, and profits from knowledge work are paramount. While companies depend on driving up productivity, corporate executives eager to maximize their bonuses and shareholders eager to maximize their dividends are given priority over corporate profits. The role of management is to ensure a return on investments made by the owners of the company. This requires elaborate accounting systems and mechanisms (p.68) of control that safeguard property rights. It is these concerns that are shaping the direction of technological and organizational change.
If the profitability of companies depends on the productivity of knowledge, companies confront the problem of imposing their property rights over intangible assets and of how to manage what resides in their employees’ heads. This is a variation on the age-old issue of how to convert an individual’s capacity to think and act into added value for the company. For this reason, some management scholars, including Barbro Anell and Timothy Wilson, argue that the question of how to extract and distribute knowledge efficiently will not be answered by relying on the initiative and intellectual capital of knowledge workers, as it is difficult to control, standardize, or profit from ideas that remain in the heads of individual workers. “The solution resides in the ability of knowledge firms to extract and translate more or less tacit, personal knowledge into explicit, codified knowledge,” moving away from the individual nature of knowledge work.11 In short, if knowledge has become a key economic asset, the task of business is to capture and control as much of it as possible without undermining the organization’s capacity to innovate and compete in global markets. In celebrating the rise of the knowledge worker, its protagonists have neglected that “the loss of control over production violates the profit-making objectives of a firm.”12 To understand how companies are standardizing knowledge work into digital software, we need to begin with Taylor’s ideas on scientific management.
Fredrick Winslow Taylor thought he had found a solution to both raising productivity and the conflict between employers and employees over the distribution of profits. At the turn of the twentieth century, Taylor argued that American industry was inefficient because it failed to apply the principles of “scientific management” which could be used to ascertain the “one best way” of organizing production. He believed that the benefits of adopting a scientific approach to management were so large that both employers and employees would prosper, ending the squabble about who gets what, which Marx viewed as the Achilles heel of the capitalism system.
Taylor drew a distinction between scientific management and management by initiative and incentive. He believed the principles of scientific management “can be applied absolutely to all classes of work, (p.69) from the most elementary to the most intricate,” although most of his work focused on elementary tasks, such as shoveling pig iron or laying bricks.13 However, it was the application of knowledge rather than muscle power that Taylor recognized as the source of productivity.14
He argued that both sides of industry had to replace the old individual judgment or opinion with exact scientific investigation and knowledge.”15 Managers had to assume new burdens, duties, and responsibilities “never dreamt of in the past.”16 This involved the scientific study, analysis, and measurement of each job to raise production standards and to work in collaboration with workers for these standards to be achieved. In his book The Principles of Scientific Management published in 1911, Taylor outlined the major problem for what he called “ordinary management” (as opposed to scientific management) in the following way:
in the best of the ordinary types of management…foremen and superintendents know…that their own knowledge and personal skills falls far short of the combined knowledge and dexterity of all the workmen under them. The most experienced managers therefore frankly place before their workmen the problem of doing the work in the best and most economic way. They recognize the task before them as that of inducing each workman to use his best endeavors, his hardest work, all his traditional knowledge, his skill, his ingenuity, and his good will—in a word, his “initiative” so as to yield the largest possible return to his employer.17
For Taylor, trusting workers to do a decent job was no way to run a business. Social relationships needed to be replaced by a system that gave managers a monopoly of knowledge and expertise. This involved the separation of mind and body to achieve common standards. Herbert Stimpson, one of a growing number of efficiency engineers in 1911, was asked by a congressional committee investigating the dehumanizing consequences of Taylorism whether workers and machines could be classed in the same category for the purposes of industrial organization. Stimpson replied that he looked upon the worker “as a little portable power plant…a mighty delicate and complicated machine…The physical body of the man is constructed on the same mechanical principles as the machine is, except that it is very much higher developed.” He argued that it was possible to scientifically measure the limits of these human machines by employing “specialists” that became known as time and motion experts, as they calculated “what the human frame can stand.”18
(p.70) This mechanized, clockwork view of the worker not only required the separation of mind and body but also an unprecedented process of knowledge transfer. In the transfer of the knowledge, techniques, and know-how of workers, including those in craft trades to company bosses, “The managers assume…the burden of gathering together all of the traditional knowledge which in the past has been possessed by the workmen and then of classifying, tabulating, and reducing this knowledge to rules, laws, and formulae which are immensely helpful to the workmen in doing their daily work.”19
In reality, a lot of this traditional knowledge was not captured but ignored because Taylor’s ultimate goal was the introduction of a new system rather than the use of historical precedent as a starting point.20 In concentrating knowledge with managers, it not only transformed the way work was organized but also entailed a loss of power and autonomy from craft workers that was bitterly resisted. At Watertown, a U.S. government arsenal, striking workers had a rare and notable victory. It was judged that Taylor’s principles were an abuse of the welfare of workers, and the principles were banned on all government-funded work until 1949.
Yet it was the rise of mass assembly-line production associated with the name of Henry Ford that ensured Taylor his place in economic history. Ford drew on a range of innovations that were prevalent at the time, although he denied that scientific management had influenced the creation of the moving assembly line that employed mass ranks of low-skill workers responsible for carrying out the same monotonous tasks. Craft skills were broken down into their most rudimentary form, reduced to a series of simple repetitive operations of the order of punching a hole in metal plates thousands of times a day without moving from the machine. In the case of General Motors’ Vega, two young women jumped on and off the assembly line and slid grilles behind the headlights; this was one of the more active roles available.
The inspiration for Ford’s continuously moving line was watching butchers in Chicago use an overhead chain to move beef during the dressing process. Describing the principle of the continuously moving line in 1922, Ford wrote, “Every piece of work in the shop moves; it may move on hooks on overhead chains going to assembly in the exact order in which the parts are required; it may travel on a moving platform, or it may go by gravity, but the point is that there is no lifting or trucking of anything other than the materials…No workman has anything to do with moving or lifting anything.”21
The goal was to mechanize everything, including human beings. In his description of factory life, he talked of “men and machine united in (p.71) production” in a fashion similar to Herbert Stimpson but recognized a major difference between the two. While both men and machines need repairs and replacements, “machinery wears out and needs to be restored. Men grow uppish, lazy, or careless.”22 Despite such human glitches, the moving assembly line gave management a new weapon in the struggle to impose the techniques and disciplines of mass production on workers. The key challenge for management now became combining materials and humans to produce quality goods at the maximum speed possible.23
The pros and cons of scientific management and Fordist mass production have continued to generate heated debate. But in the present context, it’s worth noting Taylor believed that what was truly revolutionary about scientific management was not time and motion studies or even increasing productivity but what he called a “mental revolution.” This changed the way both workers and managers understood the division of the surplus resulting from their joint efforts: “under scientific management…both sides take their eyes off of the division of the surplus as the all-important matter, and together turn their attention towards increasing the size of the surplus until this surplus becomes so large that it is unnecessary to quarrel over how it shall be divided.”24
The introduction of the $5 day in Ford’s Highland plant in 1914 more than doubled the average wage for production workers, which led the Wall Street Journal to denounce it as “an economic crime.” It gave some credence to Taylor’s optimism, but this was short lived as other companies quickly improved on Ford’s production techniques. Ford was soon forced to compete on cost, which was achieved by increasing the speed of the production line. This led one of Taylor’s disciples to conclude that rather than maximizing harmony between man and machine, it was achieved at the cost of the “destruction of the workers.”25 J. K. Galbraith also concluded that in the mid-nineteen twenties, Ford’s River Rouge plant “was a machine-age nightmare.”26
By the 1980s, scientific management and the Fordist assembly line had been discredited. In a dynamic knowledge-intensive economy requiring customized products and services to meet the exacting demands of sophisticated consumers, new models of work organization were developing that required the workforce to act as more than expensive machines. The initiative, trust, and discretion that were anathema to Taylor’s view of organizational efficiency were now seen as a source of competitive advantage. Equally, the distinction between thinking and doing was now viewed as an impediment to innovation, (p.72) which depended on the creative insights of employees. Thirty years on, however, some of Taylor’s key ideas have been given a virtual new lease of life.
If the twentieth century brought what can be described as mechanical Taylorism characterized by the Fordist production line, where the knowledge of craft workers was captured by management, codified, and reengineered in the shape of the moving assembly line, the twenty-first century is the age of digital Taylorism. This involves translating the knowledge work of managers, professionals, and technicians into working knowledge by capturing, codifying, and digitalizing their work in software packages, templates, and prescripts that can be transferred and manipulated by others regardless of location. It is being applied to offices as well as factories and to services as well as manufacturing. Unlike mechanical Taylorism, which required the concentration of labor in factories, digital Taylorism enables work activities to be dispersed and recombined from anywhere around the world in less than the time it takes to read this sentence.27
Paul Romer uses a broad definition of software to include all the knowledge that has been codified and transmitted to others. He suggests that “it can be stored on paper, as images on film, or as a string of bits on a computer or laser disc.”28 But as long as companies were limited to knowledge capture in the form of physical manuals or mechanical devices, its application to the office and service industries was limited because senior managers lacked the digital equivalent of mechanical drills, jigs, or presses used in manufacturing. However, the impact of typewriters and calculating machines in the late nineteenth century office should not be underestimated. William Henry Leffingwell was an early advocate of applying scientific management to routine office functions. In Scientific Office Management (1917), he observed, “Many businessmen, after analyzing the remarkable results secured by applying Frederick W. Taylor’s system of scientific management in factories, have asked whether or not similar betterments could not be obtained in offices with the system. Their question can now be answered, for the main principles of the Taylor system have actually been adapted and applied to office work.”29
This conclusion was an exaggeration because today’s managers have the major advantage of the Internet, networked computers, and (p.73) workflow software. Although Leffingwell and others were inspired by mass-production techniques, it is, as Simon Head notes, “the modern-day re-engineer who has come much closer to reproducing in an office setting the rigor and disciplines of scientific management. The re-engineer owes this to information technology’s prodigious powers of measurement, monitoring, and control, unavailable not only to Leffingwell but to all office managers of the pre-digital age.”30
One of the difficulties identified by Leffingwell when applying Taylor’s ideas to the office was that service industries often required greater flexibility because it was difficult to judge the requirements of customers or to standardize the way they ordered goods or services. Requests were usually received by letter in different formats that lacked the standardization of online applications or order forms. Leffingwell attempted to solve this problem of diversity by applying what he called the “exception principle.” This was the process of weeding out difficult cases and channeling them to experts for handling, thus reducing the need for extensive training to only a handful of employees.31
The exception principle has now been digitalized. Indeed, it represents the organizing principle of today’s call or contact centers, where customers are digitally routed to different teams depending on the nature of the inquiry, reducing the need for job training beyond the requirements of a specific customer inquiry, such as purchasing vacation insurance. We have become so used to online applications and digital payment software that we barely notice how they require us to complete forms in ways that reduce the need for any human interaction, let alone human initiative. When we call our bank or after-sales providers on toll free 800 numbers, we are invariably asked to “select from the following options,” repeated several times to narrow our range of possible questions, and only after failing to identify the exact inquiry are you connected to an exceptional employee.
In investment banking, the exception principle was applied to selling over-the-counter (OTC) derivatives. To reduce its operational costs, a major American bank offshored as much as possible to India. It examined the various features of the selling process and decided to offshore initial telephone or Internet contact with customers “while the more experienced resources based in London processed exceptions.” Using this model, the bank was able to “minimize their investment in knowledge transfer and training of the India-based staff while reaping as much as 40 percent savings in operating costs.”32
Customer contact centers are the office equivalent of the Fordist production line. There is an extensive use of scripts which instruct (p.74) employees about what to say, often with online instructions on what to do depending on a customer’s answer to each prescribed question. Those employed as cold-callers have the unenviable task of trying to sell us everything from kitchens, mobile phones, financial advice, and charitable causes. They also have their pace of work determined by an autodialer that selects and dials numbers giving managers complete control over the pace of work. Some autodialers do not have a pause button, making it difficult to take a break, even to visit the restroom.33
Television monitors also adorn the walls of contact centers that give supervisors minute-by-minute information about the number of calls answered or in a queue waiting to be answered. The performance of individual operators is monitored on displays with smiley faces for those meeting appropriate performance targets and sad faces for those who are not. Although the level of surveillance and the nature of the work vary considerably within contact centers, new information technologies give employers the tools to micromanage through the use of software programs that monitor e-mails and telephone conversations. There are also electronic manuals that prescribe various aspects of the job that are easy to update to meet changing business circumstances.
We were told how executives in an automotive company had introduced digital monitoring software that gave them real-time information about the productivity levels being achieved by any of their factories around the world from a laptop. Over a slice of toast and mug of coffee, the company’s CEO would breakfast watching these performance figures before making a few calls to plants where production targets were not being met. Digital Taylorism has given companies a powerful tool for employee surveillance and remote control to compare the performance of plants, offices, suppliers, managers, and workers located anywhere in the world. Its application has become more widespread with consequences for employees in a wide range of industries and occupations.
The Industrialization of Knowledge Work
Leading consultancy companies are playing an important role in applying digital Taylorism to a range of service industries, including retail, health, and finance, that typically focus on business processes, including receiving orders, marketing services, selling products, delivering (p.75) services, distributing products, invoicing for services, and accounting for payments. Digital Taylorism enables innovation to be translated into routines that might require some degree of education but not the kind of creativity and independence of judgment often associated with the knowledge economy. To reduce costs and increase control, companies are eager to capture the idiosyncratic knowledge of workers so that it can be codified and routinized, thereby making it generally available to the company rather than being the property of an individual worker.
There are many ways digital Taylorism can be applied; for example, a leading company producing and selling software handling credit card transactions and credit rating expanded very rapidly over the last decade, both within Britain and overseas, mainly through acquisitions. In an interview with the CEO in 2006, we were told that the company’s major problem was how to encourage staff—mostly college graduates—to be innovative. The CEO thought this was essential for the continued success of the business as they developed products for new markets and customers. Today, the problem has changed dramatically. The company has achieved an annual growth rate of 25 percent and opened offices across the developed and developing world, including China, India, and Bulgaria. There has been a change in CEO, and the major issue is no longer defined as innovation but of how to align business process and roll out software products to a global market. The creative work in producing new platforms, programs, and templates has been separated from what they call routine analytics. Permission to think is restricted to a relatively small group of knowledge workers currently still in Britain, and the more routine work (that is, customizing products to different markets and customers), also referred to as the grunt work, is offshored to their offices in Bulgaria and India, where college graduates can be hired at a third of the cost.
A business relations manager for wealthy clients at a bank that was brought to its knees due to disastrous speculation told us how his discretion over the amount of money he could lend to a customer had declined well before the financial crash. The bank previously respected his expertise and judgment in making decisions, but loans where increasingly authorized by a credit controller. This credit controller is a software package that automatically assesses a loan application according to specified criteria. Only in appealing against the controller’s judgment does the manager have a role, but even in these cases, he was often overruled. From a position of authority and respect, he described himself as a salesperson armed with a series of (p.76) software manuals instructing him how to sell particular kinds of products, which now meant that “a junior with a ready smile could now do my job.”
If we think of the way this manager’s job has been reclassified, then digital Taylorism has become central. Its effect is intended to increase the decision-making power of those at the top of the organization, reduce inconsistency in performance, and reduce costs. As we were told by another leading main-street banker, “We have to drive the business on a mass scale; we cannot have…files being checked on an individual basis. It’s a mass game…we have to run that kind of a model.” As a result, “analytical power is something which employees are losing out on because previously they used to analyze a lot on their own. Today it is format driven.”
The separation of conception from execution (thinking from doing) that is a trademark of scientific management represents more than another attempt to shift the priority from human creativity to behavioral control by prescribing conduct through technological means. It reveals why the modular corporation is a revolution at work. Companies are not only reexamining where to think but are also using new technologies to redefine the nature of work itself.
The Modular Corporation
Accenture Consulting uses the term industrialization to highlight the way functions within service industries can be broken down into their component parts. It is almost exactly the same way that Adam Smith described the division of labor in the manufacture of pins in the eighteenth century. But today, components can be “recombined in a tailored, automated fashion—to non-manufacturing settings.”34 Hewlett-Packard’s motif is “invent,” yet it has put standardization at the center of building a modular organization. It wants to reduce complexity across its global operations to reduce the cost—both in time and money—of implementing change.
Here standardization is no longer embraced to create bureaucratic routines but to increase flexibility by combining and recombining reusable components. When companies are attempting to globally integrate their operations, they need to develop common standards across the organization. A building-block, or Lego, approach using platform architectures and reusable IT components is now seen as a more efficient way of making organizations more adaptable to change, which can be applied to systems, processes, and (p.77) people. As Hewlett-Packard’s Nora Denzel suggests, “Jobs, business processes and technology are beginning to be standardized, virtualized and integrated into an IT ’supply chain’ that delivers services on demand—where, when and precisely how much the customer requires.”35 The idea is to break everything down into its most basic components, including work roles. These components can then be translated into reusable software so that they can be reconfigured in response to changing customer requirements, strategic initiatives, or competitive pressures.
In response to global competition, IBM decided to reengineer its global operations to raise productivity and lower costs with 250,000 employees in 80 delivery centers around the world. It adopted the joint strategy of automating areas of repetitive work and “turning repeatable processes into software” that could be used with different clients.36 Along with many other companies, it attempted to manufacture or industrialize services so that assignments could be carried out using the same software applications in Vietnam and Venezuela in much the same way that identical autos or iPods can be built to the same standard anywhere in the world. As Mike Daniels, head of global technology services at IBM suggests, the real advantage “comes out of doing the work in a codified way.” This required asking the key question of how you do the work using base-level components that do not rely on the tacit knowledge of employees that may lead them to undertake the same assignments in different ways. To help IBM achieve this, it has over 500 efficiency experts “to scrutinize its operations and apply disciplines from ‘lean’ manufacturing.”
Likewise, Suresh Gupta from Capco Consulting foresees the arrival of the “financial services factory” because as soon as banks or insurance companies begin to break tasks into a series of procedures or components that can be digitalized, it gives companies more sourcing options such as offshoring. If these trends continue, “tomorrow’s banks would look and behave no differently to a factory.”37
This is part of a new vocabulary of digital Taylorism that includes components, modules, and competencies. The way these are combined to create a new model of the modular corporation was revealed to us in an interview with the female head of global human resources for a major bank with operations in 85 countries. Until 2000, the bank adopted a country-based approach with little attempt to integrate its operations globally. It then set up a completely separate business to manage its high-volume, low-value transactions using operations in (p.78) China, India, Malaysia, and the Philippines. She commented, “So what we were doing is arbitraging the wage costs,” but this initial approach to offshoring based on “lift and shift” did not go according to plan. “We had errors, we had customer dissatisfaction, all sorts of bad stuff.”
She recalled that it took time to realize it is not easy to shift a process that has been done in the same place and in the same way for a long time. When people are asked to document what they have been doing for many years, there are inevitably going to be blind spots because they know it so well. As a result, “The semidocumented process gets shunted off while the process itself is dependent on long-term memory that is suddenly gone, so it really doesn’t work.”
Thus, the bank recognized the need to simplify and standardize as much of the company’s operations as possible before deciding what could be offshored. “So we go through that thinking process first, which means mapping these processes, changing these processes.” She also thought that this new detailing of the corporate division of labor was in its infancy “because you need the simplicity that comes with standardization to succeed in today’s world.”
The componentization of functions, alongside the modularization of jobs, reveals the growing importance attached to behavioral competencies. Reminiscent of Taylor’s mental revolution, she argued that demand for a competence-based approach was coming from employees as well as the company. Speaking before the financial crash, she believed that the biggest change during her 20 years with the company is that employees today want choice—“what they do, when they do it, where they do it.” But as she explained in this part of our discussion, which is worth repeating in full:
If you are really going to allow people to work compressed hours, work from home, then work needs to be unitized and standardized; otherwise, it can’t be. And as we keep pace with careers, we want to change; we don’t want to stay in the same job for more than 2 years max. They want to move around, have different experiences, grow their skills base so they’re more marketable. So if you’re moving people regularly, they have to be easily able to move into another role. If it’s going to take 6 months to bring them up to speed, then the business is going to suffer. So you need to be able to step into a new role and function. And our approach to that is to deeply understand the profile that you need for the role—the person profile, not the skills profile. What does this person need to have in their profile? If we look at our branch network and the individuals working at the front line with our customers, what (p.79) do we need there? We need high-end empathy; we need people who can actually step into the customers’ shoes and understand what that feels like. We need people who enjoy solving problems…so now when we recruit, we look for that high-end empathy and look for that desire to solve problems, that desire to complete things in our profiles…we can’t teach people to be more flexible, to be more empathetic…but we can teach them the basics of banking. We’ve got core products, core processes; we can teach that quite easily. So we are recruiting against more of the behavioral stuff and teaching the skills stuff, the hard knowledge that you need for the role.
Whatever the merits of her argument about the future of portfolio careers, it is diametrically opposed to how pundits of the knowledge economy have portrayed the future of work, within loosely defined occupational roles and high levels of employee discretion. In the modular corporation, there is a different kind of flexibility that requires clearly defined roles that are simplified and codified to enable plug-and-play even for highly qualified employees. This is what is at the heart of digital Taylorism—the digital documentation of business process and job descriptions, linked to electronic databases of individual competence profiles, based on human capital metrics.
Human capital metrics involve the numerical measurement of individual performance through software programs that are used to assess individual, team, or organizational performance. Writing for CFO Magazine, Craig Schneider observed how chief financial offices were behind attempts to measure the value added of the workforce because established HR measures, such as head count, turnover, or the cost of compensation and benefits, “no longer cut it in this new world of accountability. They don’t go far enough to create shareholder value and align people decisions with corporate objectives.”38
The implications for employees were highlighted in our discussions with a senior manager working for an international bank in India. The bank had developed “staff league tables” to measure both hard performance, such as meeting sales targets, how many times they had visited customers, and so on, and soft performance, such as relationship management or customer satisfaction. The creation of these league tables gave senior managers control over what is to count as performance. There is also nowhere for employees to hide because anyone within the organization across the country is able to compare the performance of individuals, teams, and branches. As we were told, “If a particular person in the banking hall needs to know where he or she stands in the (p.80) country in her particular function, she can just go and open the league tables, and she will get to see where her position is.”
We were assured this did not mean that people where constantly being judged: “I am underperforming or you are overperforming because they may all be performing to a high level.” The reality is that employees are constantly under pressure to raise their performance, as companies use software tools such as the customer relations management modules used by this company to codify performance alongside a worker’s job description.
The Future of Knowledge Work
Economic history shows that the power to both innovate and standardize has increased over time. It also shows, at least in America and Britain, a proclivity toward managerial control over employee discretion. But it is important not to emphasize control for its own sake as in Harry Braverman’s classic study of Taylorism because it should be seen as the latest attempt to boost productivity and corporate profits.39 The economic landscape is also strewn with historical examples of how highly skilled workers have found that their skills are not as unique as they assumed or have been rendered redundant by technological innovation. Today, the extent to which companies can capture the knowledge of those trained to think for a living is difficult to judge, although there is little doubt that this has become a corporate “holy grail.”
The prospect of work organization being restructured by digital Taylorism was recognized by Harold Wilensky nearly half a century ago. He envisaged a time when the distinction between conception and execution would move farther up the occupational hierarchy as new technologies offered senior managers and executives great control of their white-collar as well as blue-collar workforce.
He predicted that all but a cadre of top managers would lose most of the discretion they had previously enjoyed, as new technologies permitted “the top to control the middle, as scientific management in the past allowed supervisors to control the workers.” Innovation and planning would be centralized with top executives, surrounded by programmers, efficiency experts, and other staff experts, more sharply separated from everybody else. As Wilensky predicted, “the line between those who decide, ‘What is to be done and how’ and those who do it—that dividing line would move up. The men who once applied Taylor to the proletariat would themselves be Taylorized.”40
(p.81) The distinction between thinking and doing in a period of mechanical Taylorism also helped shape class relations between blue-collar and white-collar workers. Digital Taylorism is not only deskilling many white-collar workers, but it also incites a power struggle within the middle classes, as corporate reengineering reduces the autonomy and discretion of some but not all managers and professionals. It encourages the segmentation of talent in ways that reserve permission to think to a small proportion of elite employees responsible for driving the business forward, functioning cheek by jowl with equally well-qualified workers in more Taylorized jobs.
Many knowledge workers may disappear off the talent radar screen. This process is at an early stage in many organizations, as we’ve already indicated, but we can distinguish three types of knowledge worker: developers, demonstrators, and drones. Developers include the high potentials and top performers discussed in the next chapter. They represent no more than 10–15 percent of an organization’s workforce given “permission to think” and include senior researchers, managers, and professionals. Demonstrators are assigned to implement or execute existing knowledge, procedures, or management techniques, often through the aid of software. Much of the knowledge used by consultants, managers, teachers, nurses, technicians, and so forth is standardized or prepackaged. Indeed, although demonstrator roles may include well-qualified people, much of the focus is on effective communication with colleagues and customers. Drones are involved in monotonous work, and they are not expected to engage their brains. Many call center or data entry jobs are classic examples, where virtually everything that one utters to customers is prescripted in software packages. Many of these jobs are also highly mobile as they can be standardized and digitalized. They are increasingly filled by well-qualified workers either attracted by relatively high salaries in emerging economies or those in developed economies who are overqualified but struggling to find a job that matches their training or expectations.
If the translation of knowledge work into working knowledge is once again the price the workforce has to pay to increase productivity, the context today is very different from that of the early days of scientific management. Peter Drucker argued that it was the application of knowledge to work which “created developed economies by setting off the productivity explosion of the last hundred years.”41 What Drucker ignored was Adam Smith’s insight into the human cost of such working practices. Today, the question is how (p.82) will a much better educated workforce respond to work that does not fulfill their expectations, given that there is little prospect of rising incomes to compensate for the new realities of work. There is little incentive for companies to raise wages to compensate for a loss of intrinsic satisfaction in the context of a high-skill, low-wage workforce, as we will go on to show, but first we need to consider the global war for talent.
(1.) Jay Tate, “National Varieties of Standardization,” in Peter A. Hall and David Soskice (eds.), Varieties of Capitalism: The Institutional Foundations of Comparative Advantage (New York: Oxford University Press, 2001), 442.
(2.) See Peter F. Drucker, Post-Capitalist Society (New York: HarperCollins, 1993). Taylor’s ideas will be discussed later in the chapter.
(3.) As Peter F. Drucker observed, “the only thing that increasingly will matter in national as well as in international economics is management’s performance in making knowledge productive.” Post-Capitalist Society, 176.
(5.) Thomas Friedman, The World Is Flat (New York: Penguin, 2005), 200.
(6.) It is not innovation or standardization but innovation as standardization.
(7.) We credit the idea of “permission to think” to Ian Jones, who was a doctoral student of Phillip Brown.
(8.) David Landes, The Wealth and Poverty of Nations (London: Abacus, 1998), 187.
(9.) Ibid., chapter 13. It is this rationalization of economic activity that has been an enduring issue within the social sciences. Max Weber observed what he called the “routinization of charisma” and the prospects of an “iron cage” of bureaucracy, and Steven Brint has argued that the rhetoric of the knowledge economy is ahistorical: “Many years in the future, we shall see the same standardization in the computer software industry that a previous generation witnessed in the insurance and automobile industries.” Steven Brint, “Professionals and the ‘Knowledge Economy’: Rethinking the Theory of Post Industrial Society,” Current Sociology, 49, no. 4 (2001): 116.
(10.) See Werner Holzl and Andreas Reinstaller, The Babbage Principle after Evolutionary Economics, MERIT-Infonomics Research Memorandum Series, Maastricht, the Netherlands. http://edocs.ub.unimaas.nl/loader/file.asp?id=812
(11.) Barbro I. Anell and Timothy L. Wilson, “Prescripts: Creating Competitive Advantage in the Knowledge Economy,” Competitiveness Review, 12, no. 1: 26–37.
(12.) Holzl and Reinstaller, The Babbage Principle, 14.
(13.) Frederick W. Taylor, Principles of Scientific Management (New York: Harper and Brothers, 1911), chap. 2, p. 6. http://www.archive.org/details/principlesofscie00taylrich. Peter Drucker argues, “Few figures in intellectual history have had greater impact than Taylor. And few have been so willfully misunderstood and so assiduously misquoted.” Drucker, Post-Capitalist Society, 31.
(14.) See Robert Kanigel, The One Best Way: Frederick Winslow Taylor and the Enigma of Efficiency (London: Abacus 1997), 9.
(15.) Frederick W. Taylor quoted in Robert Kanigel, The One Best Way, 473.
(18.) See Kanigel, The One Best Way, 460.
(20.) Kanigel, The One Best Way, 282.
(21.) Henry Ford, My Life and Work (New York: Garden City Publishing, 1922), 85.
(22.) See Emma Rothschild, Paradise Lost: The Decline of the Auto-Industrial Age (New York: Random House, 1973), 34.
(23.) See Phillip Brown and Hugh Lauder, Capitalism and Social Progress: The Future of Society in a Global Economy (Basingstoke: Palgrave Press, 2001).
(24.) Quoted in Kanigel, The One Best Way, 472–473.
(25.) See Judith Merkle, Management and Ideology: The Legacy of the International Scientific Management Movement (Berkeley: University of California Press, 1980).
(26.) John K. Galbraith, The Liberal Hour (New York: Penguin, 1960), 140–141.
(27.) In mechanical Taylorism, the application of knowledge to work focuses on the development of hardware, such as machines, production lines, and factory buildings; in digital Taylorism, the application of knowledge to work focuses on the development of software. Although mechanical Taylorism relates closely to manufacturing and its digital variety to service sector occupations, it should be noted that the mechanical and digital are being applied to both factories and offices. Mechatronics, for example, is indispensable to the production of automobiles, which combines mechanics, electronics, and computing not only in the use of industrial robots but also reflects the increasing importance to the value of an automobile.
(28.) Paul Romer, “Beyond the Knowledge Worker,” Worldlink (January/February 1995), 56–60.
(29.) Simon Head, The New Ruthless Economy: Work and Power in the Digital Age (New York: Oxford University Press, 2003), 61.
(32.) Suresh Gupta, “Financial Services Factory,” Journal of Financial Transformation, (The Capco Institute, 2006): 46.
(33.) Jon Ronson, “Cold Sweat,” The Guardian Weekend, January 28, 2006. See also Adria Scharf, “‘From ‘Welcome to McDonalds’ to ‘Paper or Plastic?’ Employers Control of Speech of Service Workers,’ Dollars and Sense, The Magazine of Economic Justice (September/October 2003). www.dollarsandsense.org/archives/2003/0903scharf.html. After developing the distinction between mechanical and digital Taylorism, we came across this article by Parenti Christian that used the term digital Taylorism. The focus is mainly on technologies of surveillance, and although this is important, we want to emphasize that control is not being imposed for its own sake but to drive profits by lifting productivity and reducing costs. We have also sought to understand digital Taylorism within its wider context of the modular corporation. Parenti Christian, “Big Brother’s Corporate Cousin,” Nation, 273, no. 5.
(34.) Accenture, The Point: Automation for the People (2007), 1. https://www.accenturehighperformingbusiness.com/Global/Services/By_Industry/Financial_Services/The-Point/Archive/fsi_thepoint47.htm. This article suggests, “When manufacturing companies seek greater economies of scale across product lines while retaining each product’s distinctive brand traits and characteristics, they ‘industrialize’ their operations: deconstructing the product and the manufacturing processes into smaller, more discrete components that can be efficiently combined in various combinations depending on what is being built. The automotive industry is a perfect example. With their ‘platform’ approach to building cars, companies such as Volkswagen and Toyota can combine different parts in different ways to spread engineering and production costs across a greater number of vehicles while ensuring that, for example, a Volkswagen Passat remains different from an Audi A4—even though they share many components and are built on the same assembly line.”
(35.) Nora Denzel, Standardization: Reduce Cost, Simply Change, HP Feature Story, (February 2004). http://h41131.www4.hp.com/hk/en/stories/standardization-reduce-cost-simplify-change.html; see also Suzanne Berger, How We Compete (New York: Currency Doubleday, 2005); Raghu Garud, Arun Kumaraswamy, and Richard N. Langlois (eds.), Managing in the Modular Age (Malden, Mass.: Blackwell, 2003); Andrew Holmes, Commodification and the Strategic Response (Aldershot: Gower, 2008).
(36.) See Richard Waters, “Big Blueprint for IBM Services,” Financial Times, March 2, 2009.
(37.) Gupta, “Financial Services Factory,” p. 43.
(38.) Craig Schneider, “The New Human-Capital Metrics,” CFO Magazine (February 15, 2006), 1. www.cfo.com/printable/article.cfm/5491043. This is likely to change in the future as a survey by the Conference Board of Canada found that 84 percent of HR executives in the 104 medium to large organizations surveyed where planning to use human capital metrics. Ibid. See also The Strategic Value of People: Human Resource Trends and Metrics (Ottawa: The Conference Board of Canada: 2006). http://www.conferenceboard.ca/documents.asp?rnext=1707
(39.) During the 1950s and 1960s, the extent to which Taylor’s approach was adopted varied considerably both within and across industrial sectors and countries. But it’s well worth reading Harry Braverman, Labor and Monopoly Capital: The Degradation of Work in the Twentieth Century (New York: Monthly Review Press, 1974).
(40.) Harold Wilensky, “Work, Careers, and Social Integration,” International Social Science Journal, 12 (1960): 557.
(41.) Drucker, Post-Capitalist Society, 35.