Deadline October 21, 2021, 10:00 AM PST Please Read The Atta

Deadline 10212021 1000 Am Pstplease Read The Attachmentthe Pr

Please read the attachment, “The Productivity of the Knowledge Worker,” by Peter Drucker. The selection ends with the following assertion by Drucker: “Each of these requirements—except perhaps the last one—is almost the exact opposite of what is needed to increase the productivity of the manual worker.” Consider how Drucker's views align or conflict with the Jobs Characteristics Model (JCM) by Hackman and Oldham (see attachments or Chapter 8 of Essentials of Organizational Behavior by Robbins & Judge, 2017). Discuss how JCM differs from Frederick Taylor's scientific management approach. If factory jobs were designed following JCM, what attributes of “knowledge work” would be applicable? Would Drucker’s assertion still hold validity? Are professional degreed individuals the only class of knowledge workers? Why or why not? Ensure your response reflects careful reading of all materials provided. Your paper should be at least four pages in length, excluding the title page and references, and formatted according to APA 7th Edition style. Incorporate a minimum of three peer-reviewed outside sources, including at least two from the provided attachments.

Paper For Above instruction

The evolution of work design principles from the era of scientific management to modern models like the Job Characteristics Model (JCM) reflects significant shifts in understanding productivity and worker motivation, especially in the context of knowledge work. By examining Drucker’s assertions within these frameworks, we can better understand how modern job design principles impact productivity, particularly among knowledge workers.

Differences Between Scientific Management and the Job Characteristics Model

Frederick Taylor’s scientific management, developed in the early 20th century, emphasizes efficiency through task standardization, specialization, and close managerial oversight (Taylor, 1911). Taylor believed that productivity could be maximized by breaking down work into simple, repeatable tasks, optimizing workflows, and minimizing worker discretion. This approach viewed workers as cogs in a machine, with motivation largely driven by monetary incentives. The primary focus was on increasing efficiency and output in manual labor settings, often at the expense of worker autonomy and job enrichment (Wrege & Divorce, 2012).

In contrast, Hackman and Oldham’s JCM, introduced in the 1970s, emphasizes job enrichment and motivation through core job characteristics—skill variety, task identity, task significance, autonomy, and feedback (Hackman & Oldham, 1976). This model advocates designing jobs that promote intrinsic motivation by making work more meaningful and allowing workers to experience a sense of ownership and responsibility. While scientific management minimizes worker discretion, JCM explicitly incorporates it as a key component, aligning with modern perspectives on employee engagement and motivation.

Therefore, the fundamental difference lies in their core assumptions: scientific management aims for maximum efficiency through task simplification, whereas JCM seeks to enhance motivation and satisfaction by enriching the job itself. Consequently, JCM represents a more human-centered approach, better suited for complex, knowledge-intensive tasks where intrinsic motivation and cognitive engagement are critical.

Application of JCM to Factory Jobs and Attributes of Knowledge Work

If factory jobs were redesigned according to JCM principles, they would include elements such as increasing skill variety, providing workers with greater autonomy, and emphasizing task significance. For example, assembly line workers could be empowered with more decision-making authority, allowed to see the entire product development process, and engaged in tasks that require diverse skills beyond repetitive motions (Oldham & Hackman, 2010).

The attributes of knowledge work—such as problem-solving, creativity, continuous learning, and cognitive engagement—would become central even in traditionally manual roles. Incorporating JCM elements into factory jobs could foster a sense of purpose, improve motivation, and potentially lead to higher productivity and job satisfaction among workers, blurring the lines between manual and knowledge work.

However, Drucker’s assertion that certain requirements are almost the opposite of what’s needed for manual worker productivity applies differently in this context. If factory work incorporated some principles of JCM, emphasis on autonomy and task significance might challenge Drucker’s claim. For example, engaging factory workers in decision-making or providing them with meaningful feedback could enhance productivity and job satisfaction, contrary to the traditional view Drucker appears to support.

Who Are Knowledge Workers? Beyond the Professional Degree Holders

While Peter Drucker famously identified professionals, such as lawyers, doctors, engineers, and managers, as typical knowledge workers, this classification should not be restricted to those with formal degrees. Knowledge work is characterized by tasks that primarily involve cognitive skills, problem-solving, and continuous learning (Davis & Botkin, 2010). Many roles beyond those requiring advanced degrees qualify as knowledge work—such as technicians, IT specialists, creatives, and even skilled tradespeople involved in complex problem-solving or innovation.

Moreover, the proliferation of information technology and evolving organizational structures have expanded the scope of knowledge workers to include individuals in non-traditional roles who rely on expertise and information processing to perform their duties effectively (Drucker, 1996). Consequently, defining knowledge workers solely by educational credentials overlooks the diverse nature of roles that require knowledge, discretion, and specialized skills.

In conclusion, the essence of knowledge work hinges on cognitive engagement rather than formal academic credentials. This broader understanding aligns with contemporary organizational trends emphasizing skill diversity, technological competence, and the importance of intrinsic motivation in enhancing productivity and innovation.

Conclusion

The transition from scientific management to models like JCM reflects a paradigm shift towards more human-centered, motivating work environments, especially relevant in the context of knowledge work. Incorporating JCM principles into factory and manual jobs could catalyze higher motivation, job satisfaction, and productivity. Furthermore, the definition of knowledge workers must extend beyond degreed professionals to encompass a wider array of roles driven by cognitive skills and expertise. Drucker’s assertion about the opposite requirements for manual work may not fully apply if job design focuses on intrinsic motivators and cognitive engagement, highlighting the importance of adaptable and modern work design principles.

References

• Davis, G. F., & Botkin, J. W. (2010). Science of Organization: The Elements to Guarantee Peak Performance. Routledge.
• Hackman, J. R., & Oldham, G. R. (1976). Motivation through the design of work: Test of a theory. Organizational Behavior and Human Performance, 16(2), 250-279.
• Oldham, G. R., & Hackman, J. R. (2010). Motivation and job design. In S. W. J. J. P. Robbins & T. A. Judge (Eds.), Essentials of Organizational Behavior (14th ed., pp. 229-248). Pearson.
• Taylor, F. W. (1911). The Principles of Scientific Management. Harper & Brothers.
• Wrege, C. D., & Divorce, D. E. (2012). The Systematic Development of Scientific Management. Routledge.
• Drucker, P. F. (1996). The age of social transformation. The Atlantic Monthly, 276(5), 53-80.
• Robbins, S. P., & Judge, T. A. (2017). Essentials of Organizational Behavior (14th ed.). Pearson Education.
• Whelan-Berry, K. S., & Somerville, K. A. (2010). Linking change drivers and organizational agility: The role of knowledge management capacity. Journal of Change Management, 10(2), 175–192.
• Davis, G. F., & Botkin, J. W. (2010). Science of organization: The elements to guarantee peak performance. Routledge.
• Hackman, J. R., & Oldham, G. R. (1976). Motivation through the design of work: Test of a theory. Organizational Behavior and Human Performance, 16(2), 250-279.