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Scientific Management – Taylorism

Updated August 24, 2022 by Carl Lindberg

As a CEO interested in leadership, I had to dig deeper into Scientific Management, or Taylorism. Scientific Management has significantly impacted management research and has profoundly influenced many other frameworks. This article explains the background, characteristics, and a few examples of Scientific Management. Let us start with a few overall answers to provide a setting for your continued reading.

What is Scientific Management?

Scientific Management is a scientific approach to mapping and optimizing an organization. Scientific Management aims to improve labor processes to maximize company profit by scientifically measuring steps, tasks, and processes.

Scientific Management, also known as Taylorism, is the basis for the 20th-century command and control management system. In the early 1900s, loads of people related to business or production adopted Taylorism as management’s main form. At a time when factories and production centers grew at high rates of speed, operations started to become more and more difficult to overview and execute effectively. Scientific Management helped bridge this lack of control by reducing operations and production into data points. Alfred P Sloan, General Motors CEO, could make the company he was leading the world’s largest corporation, many thanks to Scientific Management.

Scientific Management is no longer a desired form of management since it puts too much focus on production rather than on people. Companies that use Taylorism as the primary management approach want to get the maximum possible output from their employees. However, there are some modified variants of this approach still used today.

The newer, modified, and modernized versions of Scientific Management help organizations reach new heights thanks to digitalization. It has even spawned a new name, or at least a version of the old name of Taylorism, and is called Neo-Taylorism.

What is Scientific Management?

Most modern-day leaders are acquainted with Scientific Management already, to some degree. It has become well-known since it was such an early and impactful approach to management. Everything started in 1911 when Frederick Taylor published The Principles of Scientific Management, which became an instant classic in the Organizational Leadership segment. Scientific Management requires systematic measurements of every aspect of operations, ranging from minute tasks to overall production lead times. Once these detailed measurements have been obtained, involved managers will have a clear picture of limitations and requirements within production.

This high resolution of information obtained by the Scientific Management approach to measurement provides managers a better picture of where any bottlenecks or time losses lie so that those activities can be further streamlined and improved, with better productivity in the end. This can be achieved by breaking down all tasks into small sub-tasks or sub-activities so that employees can handle them faster, better, and more efficiently. At the same time, waste can be reduced, bringing further efficiency.

According to Scientific Management, everything is based on precise data. Only by having numbers can managers evaluate the job done. Generally talking, this theory has four underpinning principles, namely: to find the one’ best way’ to perform each task, to carefully match each worker to each task, to supervise workers closely, and use reward and punishment as motivators, and finally to manage, plan and control [2]. There is a striking similarity with Bureaucratic Leadership.

What are the four principles of Scientific Management?

Scientific Management has four fundamental principles:

  • Clear division of tasks, jobs, and responsibilities
  • Using scientific methods to find and standardize the most optimum way to perform a task
  • Strict monitoring and control of the workforce through the organizational hierarchy
  • Rewards and punishments to motivate strong output

These principles are deeply rooted in our world today. They can hamper our creativity in looking elsewhere for efficiency improvement, such as in more people-oriented focus areas, including vision, purpose, participation, etc. (Suggested reading: Visionary leadership, democratic leadership.)

Scientific Management theory was widely accepted early on in the United States, and some critics state that this approach limits the growth of the U.S. economy. In 1986, Konosuke Matsushita, the founder of Panasonic, even went as far as to say: “We will win, and you will lose. You cannot do anything about it because your failure is an internal disease. Your companies are based on Taylor’s principles. Worse, your heads are Taylorized, too.”

Scientific Management helps to set the expectations of every sub-task and to find the proper output to expect from each worker performing their tasks, opening up to incentives and punishment depending on the output compared to the expectation. This incredibly detailed view on output and maximizing the amount each employee should produce eventually made Scientific Management seem exploitative and less human. The Scientific Management approach also achieves maximum job fragmentation, minimizes skill requirements, separates execution from planning, and provides precise measurement capabilities, which in the end, can enable a payment-by-result method [1].

Taylor said that”… in the past, man has been first, in the future the System will be first.” With this, he wanted to say that once optimized, the system would have better information and judgment than humans when identifying the optimum operating methods. Given this, the main task of any leader is not to make employees work effectively on an individual basis but to optimize the system, which consists of a network of people performing different activities, all driving toward the final production output.

Neo-Taylorism and Digital Taylorism

It seems Scientific Management as a management ideology is outdated. Still, with globalization and the new requirements set in front of managers and leaders, it has come back in a new form. Now, the new possibilities of media technologies have a larger impact on working processes [4]. Moreover, market requirements refer to quality, flexibility, time reduction, and satisfaction with an increasing diversity of clients and tastes. So the companies must rely on the so-called “knowledge work” that characterizes the information or third industrial revolution. This opens up a Tayloristic approach to modern processes, not limited to assembly and more physical tasks, but in the form of Neo-Taylorism, also called Digital Taylorism.

Digitalization of the working process is realized in the following way. Tasks are subject to the same mapping and measurement process as in Scientific Management. Until recently, many tasks have been considered non-machinable, but more and more of them are codified and digitalized. In practice, this means that tasks performed by humans before can now be performed with automated processes and software. This development is even further propelled by the emergence of Artificial Intelligence or A.I.

One of the best examples showcasing the advantages of Neo-Taylorism is single-queuing systems. With the goal to increase value in customer service, the new systems reduce waiting time, leading to higher efficiency for each customer service operator.

Another example is the extension of “effective” working time beyond the “formal” working hours. This is especially true for I.T. companies, where we can’t find strict control over employees. Instead, the management is more focused on the value they create and how effective the team members work. However, the best example and its use in practice come from Google. As you know, it offers tons of benefits to its employees. At first sight, you might think it’s just motivation [5]. But in fact, due to such an approach, Google gets maximum from each employee as they work all the time.

However, this Neo-Tayloristic model is gradually yielding its position to alternative concepts, such as Lean and DevOps. These approaches value knowledge workers and desire participation in problem-solving such as democratic leadership and use less of a command and control management approach than commanding leadership [3].

Advantages of Scientific Management

These are the advantages of Scientific Management:

  • It provides procedures and systems to increase an organization’s effectiveness
  • It provides detailed and robust control over processes and employees
  • It enables cost reductions and efficiency improvements in production
  • It allows the optimum use of resources and development.    

Disadvantages of Scientific Management

These are the disadvantages of Scientific Management:

  • Employees accomplish their tasks without any knowledge of the final product, leaving limited space for purpose and creativity
  • The oversimplification and chase for productivity may have inhuman, demoralizing effects.
  • It makes limited use of the talent, intelligence, and craftsmanship of each worker

Conclusions on Scientific Management

Scientific Management, also known as Taylorism, was a new approach to management that provided opportunities to reach further efficiency and productivity, mainly in production environments. Scientific Management completely dominated the management field for half a century and still has a firm grip on modern management perspectives. However, since our economies rely increasingly on knowledge workers, Scientific Management, which needs repetitive tasks that can be broken down, analyzed, and improved, is becoming gradually less relevant.


[1] Ndaguba, E.A, Nzewi, O.I., Ijeoma, E.C., Sambumbu, M. & Sibanda, M.M., 2018, ‘Using Taylorism to make work easier: A work procedure perspective’, South African Journal of Economic and Management Sciences 21(1), a2120. https://doi.org/10.4102/sajems.v21i1.2120

[2] Walonick, D.S., 1993, Organizational theory and behavior, viewed 09 July 2015,


[3] https://itrevolution.com/neo-taylorism-or-devops-anti-patterns/

[4] Eva-Maria Nyckel, “Digital Taylorism”? Data Practices and Governance in the Enterprise Software Salesforce, 2020, pp. 7 https://www.ssoar.info/ssoar/bitstream/handle/document/68536/ssoar-2020-Nyckel-Digital_Taylorism_Data_Practices.pdf

[5] José Luis Vázquez, García María Purificación, From taylorism to neo-taylorism: a 100 year journey in human resource management, Vilmányi Márton – Kazár Klára (szerk.) 2017: Menedzsment innovációk az üzleti és a nonbusiness szférákban. SZTE Gazdaságtudományi Kar, Szeged, 496–513. https://www.scrummaster.dk/lib/AgileLeanLibrary/Topics/_NeoTaylorism/FromTaylorismToNeo-taylorism.pdf

[6] Rogers, H. (1987), Theory of Recursive Functions and Effective Computability, Cambridge, MA: The MIT Press.

[7] https://www.marshall.usc.edu/sites/default/files/padler/intellcont/TismToTeams-1.pdf


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