Why Knowledge Workers Must Embrace Standard Work

By Irwin Hirsh, Q-Specialists AB

Knowledge workers often resist following standard work, arguing that it stifles productivity and hampers the creative process integral to their roles. However, standard work can significantly enhance productivity and creativity by reducing cognitive load and automating routine tasks. This article discusses the benefits of standard work for knowledge workers, drawing from personal experience and supported by scientific literature.

Herein, "standard work" is the explicit knowledge and information created to support the performance of a part or parts of a process (checklists, instructions, process maps, etc.). The standard work is created and routinely improved via Demming PDCA (plan-do-check-act) methodologies, wherein the process experts, those who regularly perform the process, strive to reduce waste in the process and increase customer value.

In a series of articles published earlier this year, I introduced a knowledge management framework.^1,2,3,4 This framework is based on process understanding from process mapping and is maintained through digitization and governance. While the framework can support knowledge management for any business, the context for the series was manufacturing process development in biotechnology. Development scientists, who typically have advanced degrees and are highly sought after for their education and experience, fall under the category of knowledge workers.

This is part one of a series designed to show how to manage the flow of knowledge from knowledge workers into the business. It provides knowledge workers with the context to communicate more clearly and effectively within the business. For managers, the goal is to improve or create a system that helps knowledge workers be more productive in ways that directly benefit the business and drive growth and innovation. The word “system” can mean different things. For the sake of this article, we will assume that it means a collection of processes that work together to achieve a common goal.

Benefits Of Standard Work For Knowledge Workers

The primary benefits of adopting standard work, which I will discuss in more detail here, include:

1. Reduced cognitive load
2. Enhanced creativity and focus
3. Accelerated time to competency
4. Consistency and quality control
5. Reduced task switching

Reduced Cognitive Load

From personal experience, implementing standard work reduces cognitive load by eliminating the need to constantly decide how to handle routine tasks. This allows for greater focus on more complex and creative aspects of the job. A 2006 study by Kirschner, Sweller, and Clark supports this, highlighting that reducing extraneous cognitive load can free up mental resources for higher-order thinking and problem-solving.⁵

In their book, “Team Topologies,” Skelton and Pais argue that there are three types of cognitive load experienced by software developers.⁶

• Intrinsic load: The inherent difficulty of the tasks the team needs to perform.
• Extraneous load: The way information or tasks are presented to the team, which can either help or hinder their understanding and efficiency.
• Germane load: The mental effort required to create new knowledge and skills or to solve problems effectively.

The authors propose that by organizing teams into specific topologies to manage cognitive load across the teams, that is, divide up the type of “standard” work to which each team is held accountable, will deliver improved efficiency, innovation, and overall performance.

Enhanced Creativity And Focus

With routine tasks standardized or automated, knowledge workers can dedicate more time and more of their cognitive capacity to creative processes and strategic decision-making. This aligns with the findings of a study by Levitin,⁷ which demonstrates that minimizing routine decision-making can enhance creativity by preserving cognitive resources for more demanding tasks.

Working Within A Platform

Standard work in development and operations platforms brings consistency, reduces errors, enhances scalability, and supports productivity by providing a structured approach to managing known unit operations and equipment. This structured approach reduces variability, provides a clear rationale for design choices and trade-offs and allows workers to concentrate on optimizing and innovating processes, driving overall organizational efficiency and effectiveness. Additionally, standard work enhances scalability within these platforms. When new equipment is introduced or when scaling up operations, having a set of established procedures allows for smoother transitions and faster integration of new elements into the existing workflow.

This facilitates continuous improvement and innovation, as team members can build upon a solid foundation of standardized practices. Research in operations management has shown that standardized processes lead to more predictable outcomes and can significantly improve operational efficiency.⁸

In the case of operations, for example, in an IT operations platform, standardized procedures for handling server configurations, software deployments, and incident management ensure that all team members are aligned in their approach, reducing the likelihood of misconfigurations or overlooked steps that could lead to system failures. This level of standardization supports productivity by allowing team members to focus on more complex, value-added tasks rather than repeatedly addressing preventable issues.

Consistency And Quality Control

Standard work ensures that tasks are performed consistently, reducing variability and enhancing quality control. This is particularly crucial in environments where precision and accuracy are essential. The standardization of processes in industries like healthcare and manufacturing has led to significant improvements in quality and safety.⁹

Accelerated Time To Competency

Standard work provides a clear, explicit guide for new and less experienced workers, reducing the time required to achieve competency. This not only accelerates their learning curve but also minimizes disruptions for more experienced workers, who would otherwise spend significant time training newcomers. The concept of "scaffolding" in educational psychology supports this approach, where providing structured support accelerates skill acquisition¹⁰ and better retention of information and skills.¹¹

Reduced Task Switching

Task switching, often mistaken for multitasking, is a significant productivity killer. Task switching refers to the process of shifting attention between different tasks, which incurs a cognitive cost each time the switch occurs. Studies show that task switching can reduce productivity by up to 40% and increase errors.¹² This contrasts with multitasking, where multiple tasks are managed concurrently but not necessarily completed simultaneously.

Task Switching Vs. Multitasking

Task switching: When individuals shift their focus from one task to another, it results in a cognitive switch, which is mentally taxing and time-consuming. This phenomenon is well-documented in psychological research. For instance, a study by Rubinstein, Meyer, and Evans found that task switching can significantly increase the time needed to complete tasks and lead to more errors.¹³

Multitasking: Involves handling multiple tasks at the same time but not necessarily switching focus continuously. For example, listening to music while working on a report may not significantly affect productivity if the music is not distracting. However, true multitasking is rare and often less effective than focusing on one task at a time.

Scientific Evidence On Task Switching

The impact of task switching on productivity is extensively researched. For example, a study by Monsell demonstrated that even brief mental blocks created by shifting between tasks can significantly decrease productivity.¹⁴ These findings are supported by the American Psychological Association, which notes that task switching can reduce productivity by up to 40% and lead to an increase in errors.

Conclusion

Adopting standard work practices offers numerous benefits for knowledge workers, including reduced cognitive load, enhanced creativity and focus, accelerated time to competency, consistency, quality control, and efficient training processes. Additionally, by minimizing the need for task switching, standard work can further enhance productivity and reduce errors.

Overcoming initial resistance to standardization of the processes of the knowledge worker is in and of itself different than standardization of operations. Operations desire routine with low variation, while knowledge workers embrace variation if only to find root cause and eliminate it.

It is the role of the manager to support the knowledge worker to increase productivity and engagement in work, and standard work initiatives run the risk of creating the opposite effect. So, from a human change management perspective the knowledge workers’ management must first understand the challenges of the knowledge worker (a regular “go and see” (Gemba-type) approach would be useful). Then participation in the creation of standard work that eliminates these challenges would be ideal.

The balancing (and focus) of the cognitive load is the critical aspect I have experienced as a knowledge worker. The challenge from this perspective is that management must start by identifying if it is their own mixed messages and shifting priorities that stifle cognitive resources. If not, is it the way the team is structured (see the team topology discussion above)? Once these two failures of management are addressed, then it is appropriate to do a deep dive into the processes of the knowledge worker. See my earlier work on knowledge management to get started.

References:

1. Hirsh, I. (2024). How To Speed Up Time To Market With CMC Knowledge Management (bioprocessonline.com).
2. Hirsh, I. (2024). Process Mapping For More Effective Knowledge Management (bioprocessonline.com)
3. Hirsh, I. (2024). Digitizing CMC Knowledge Management (bioprocessonline.com)
4. Hirsh, I. (2024). Improving Governance And Compliance With Knowledge Management (bioprocessonline.com)
5. Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching. Educational Psychologist, 41(2), 75-86. https://doi.org/10.1207/s15326985ep4102_1
6. Skelton and Pais (2019). Team Topologies, Organizing businesses and technology teams for fast flow. IT Revolution Press, Portland, OR, USA. ISBN13: 978-1914278829
7. Levitin, D. J. (2014). The organized mind: Thinking straight in the age of information overload. Dutton Penguin, NY, NY. ISBN-13: 978-0525954187
8. Liker, J. K. (2004). The Toyota way: 14 management principles from the world's greatest manufacturer. McGraw-Hill, NY, NY.  ISBN-13: 978-0071392310
9. Gawande, A. (2011). The checklist manifesto: How to get things right. Metropolitan Books, NY, NY. ISBN-13: ‎ 978-0312430009
10. Wood, D., Bruner, J. S., & Ross, G. (1976). The role of tutoring in problem solving. Journal of Child Psychology and Psychiatry, 17(2), 89-100. https://doi.org/10.1111/j.1469-7610.1976.tb00381.x
11. Salas, E., Tannenbaum, S. I., Kraiger, K., & Smith-Jentsch, K. A. (2012). The science of training and development in organizations: What matters in practice. Psychological Science in the Public Interest, 13(2), 74-101. https://doi.org/10.1177/1529100612436661
12. American Psychological Association. (2006). Multitasking: Switching costs. American Psychological Association. From https://www.apa.org/research/action/multitask and they are referencing the work of Monsell below.
13. Rubinstein, J. S., Meyer, D. E., & Evans, J. E. (2001). Executive control of cognitive processes in task switching. Journal of Experimental Psychology: Human Perception and Performance, 27(4), 763-797. https://doi.org/10.1037/0096-1523.27.4.763
14. Monsell, S. (2003). Task switching. Trends in Cognitive Sciences, 7(3), 134-140. https://doi.org/10.1016/S1364-6613(03)00028-7

About The Author:

Irwin Hirsh has nearly 30 years of pharma experience with a background in CMC encompassing discovery, development, manufacturing, quality systems, QRM, and process validation. In 2008, Irwin joined Novo Nordisk, focusing on quality roles and spearheading initiatives related to QRM and life cycle approaches to validation. Subsequently, he transitioned to the Merck (DE) Healthcare division, where he held director roles within the biosimilars and biopharma business units. In 2018, he became a consultant concentrating on enhancing business efficiency and effectiveness. His primary focus involves building process-oriented systems within CMC and quality departments along with implementing digital tools for knowledge management and sharing.