Limiting Effects of Tariffs Through Scientific Management
The Trump administration’s commitment to tariffs and the ongoing uncertainty over precisely which countries, products and services will face these new, steep import taxes are creating headwinds for the global economy and making it difficult for companies to plan. But firms concerned about the impact on their supply chains can still reduce costs, improve quality and increase the production of goods and services, by adopting elements of what is known as “scientific management” and updating them for the new millennium.
Developed by Frederick Winslow Taylor around the turn of the 20th century, scientific management (see also “Taylorism”) was a precursor of Business Process Engineering (BPE) that sought to apply scientific principles to the organization of work. Taylor, a mechanical engineer who wanted to improve industrial efficiency, was a pioneer in management consulting, influencing firms like the Singer Manufacturing Company (now the Singer Corporation; maker of sewing machines) and the car magnate Henry Ford. Dubbed “the world’s first efficiency expert”, Taylor laid the framework for management theory in “The Principles of Scientific Management” (1911), a thin volume named one of the most influential management books of the 20th century. Scientific management focused on boosting firms’ economic efficiency by systematically analyzing and optimizing work processes and labor performance and by standardizing best practices.
Scientific management aimed to avoid “waste” of any kind, Taylor’s principles were widely adopted by firms in many product and service industries.
Many elements of Taylorism still inform present day management strategies.
Like the Total Cost Management (TCM) approach to work process improvement and management, though more narrowly focused, Taylorism prizes efficiency and worker training and selection. The approach involves breaking tasks down into their smallest components and identifying the “one best way” to perform a task by measuring the time taken for each movement. Well-trained workers and performance standards, along with these standardized procedures, increased productivity.
Six Sigma, introduced by Bill Smith at Motorola in 1986, is a modern process improvement methodology focused on defect reduction and scientifically studying and optimizing work. It traces some of its core principles back to scientific management, as seen in its emphasis on standardization and best practices, while building on them through enhanced methods like statistical analysis. Taylorism, Six Sigma and Lean Management all share a common goal of increasing efficiency, and lean principles can be part of a comprehensive TCM strategy, but while Taylorism has been criticized for dehumanizing workers, viewing them merely as tools for production, approaches like Six Sigma, TCM and business process reengineering (BPR) draw from Taylorism, while placing more emphasis on employee autonomy and collaboration in problem solving.
Taylor’s principles could prove particularly useful in jobs organized around measurable tasks, like manufacturing, engineering or software development. Less so in the knowledge and creative fields.
Artificial intelligence can help firms use the best elements of scientific management to increase productivity. AI can provide predictive analytics to help with resource allocation and planning, create virtual models using real-time data to test hypotheses, help firms provide personalized employee performance feedback and may also be able to help with the sort of time and motion studies Taylor made famous, by automating and analyzing different process variations to identify the most effective approach.
The takeaway: Though the concept of scientific management dates back more than a century, it remains relevant and necessary today and companies can begin implementing elements of this decades old approach, with significant results, right away. Doing so will improve efficiency, offset higher costs and protect firms’ bottom lines even in this age of uncertainty.
