Many misunderstand Agile as a mere process idea, rather than recognize it as a comprehensive way of working. However, it is important to understand that Agile is not merely someone’s idea. It is grounded in solid scientific foundations. In this article, we will provide a snapshot of some of the key theories that underpin Agile principles, shedding light on their scientific basis. It is important to note that this article offers a glimpse into these theories rather than providing a comprehensive overview. (This article requires prior knowledge to Agile; here is an introduction to Organizational Agile).
Complex Adaptive Systems Theory
Organizations in the 21st century function as complex adaptive systems, where various entities, such as teams and individuals, interact and self-organize to navigate the dynamic environment. This theory recognizes the emergence of complex behaviors and emphasizes the significance of adaptability, transparency, and collaboration.
Within the extensive body of work on Complex Adaptive Theory (including contributions by Follet, Lewin, McGregor, Buckley, Senge, Stacey, Uhl-Bien, Wheatley, and others), we would like to highlight Ashby’s Law of Requisite Variety. This law underscores the crucial role of self-organization in managing complex systems. It states that to effectively handle complexity, an organization must possess a range of responses equal to the complexity it encounters. To illustrate, in a team of three members, there would be a variety of three possible interactions among all team members. According to Ashby’s Law, the system needs to have at least three responses to stabilize it. Please bear in mind, that for this document, we oversimplify the variety within the system. Tools (or absence of), external events, Systemic Policies, Team hierarchy, and others, will affect the variety within the system.
Dealing with a team of three is relatively straightforward, and one node of control can manage this. However, when managing an organization of 200 people, the number of potential interactions amounts to 19,800 (as calculated by ChatGPT). Controlling such complexity becomes impractical. Therefore, we need an alternative approach.
Drawing from science, we can draw various response models to effectively manage this complexity. While Game Theory, Chaos Theory, and Motivational Theory offer further insights, this article focuses on three specific ways of responding:
Empirical Process Control
Scientists often employ empirical process control in their scientific experiments. Empirical process control involves a systematic approach of observing, measuring, and analyzing data to gain insights and make informed decisions based on evidence. It is a fundamental aspect of the scientific method, which emphasizes the importance of experimentation and observation to develop and validate hypotheses.
In scientific experiments, researchers typically design controlled studies where variables are manipulated, and their effects are observed and measured. By collecting empirical data through experiments, scientists can analyze the results, draw conclusions, and make adjustments to refine their hypotheses or experimental methods.
Agile frameworks, such as Scrum, rely on empirical process control. Similar to Scientists, teams in Scrum emphasize learning through observation, experimentation, and adaptation. Recognizing the inherent unpredictability of complex environments, Agile teams embrace an iterative and incremental approach to deliver value. By continuously inspecting and adapting their processes based on real-time feedback, organizations can respond to changing circumstances and improve outcomes.
While Lean Thinking incorporates principles that have been refined and tested through practical application, it does not have a singular scientific foundation or theory. Instead, it draws upon a combination of concepts and practices, such as waste reduction, value stream mapping, continuous improvement, and just-in-time production, among others.
That being said, Lean Thinking is informed by various disciplines, including operations management, systems thinking, and quality management. It aligns with scientific principles and theories related to process optimization, elimination of waste, and continuous improvement.
Agile methodologies draw inspiration from lean principles, which originated in the manufacturing industry, notably in Toyota’s production system. By minimizing non-value-added activities, organizations can streamline their workflows and enhance overall efficiency.
Motivational theory focuses on understanding the factors that drive and influence human motivation. It explores why individuals initiate, sustain, and direct their behavior towards certain goals or outcomes. Motivational theories, such as Maslow’s Hierarchy of Needs, Expectancy Theory, or Self-Determination Theory, offer frameworks to understand the various psychological, social, and cognitive factors that shape motivation.
When considering the Theory of Complex Adaptive Systems, motivation plays a vital role in influencing the behavior of individuals within these systems. Complex Adaptive Systems recognize that individuals within the system interact, self-organize, and adapt based on local rules and their individual motivations. Motivation can impact how individuals respond to dynamic changes and make decisions within the system.
Motivational theory can inform our understanding of how individuals’ goals, needs, and intrinsic or extrinsic motivators shape their behavior within a complex system. It helps explain why individuals may choose certain actions or exhibit specific patterns of behavior within the larger system.
Agile Organization address that through the principle understanding that we not need to motivate teams and individuals. They are already per default. This is the foundation to creating trustful environments and increasing team performance. “Build projects around motivated individuals. Give them the environment and support they need, and trust them to get the job done.” (Agile principle #5)
Agile, as a comprehensive way of working, is grounded in solid scientific foundations. The Theory of Complex Adaptive Systems recognizes organizations as complex entities where adaptability, transparency, and collaboration are crucial. Ashby’s Law of Requisite Variety highlights the significance of self-organization to manage complexity effectively.
Agile organizations leverage these scientific foundations to empower motivated individuals, foster a trustful environment, and enhance team performance. By embracing complexity, employing empirical process control, adopting lean principles, and understanding motivation, organizations can navigate the challenges of the modern business landscape and thrive in an ever-changing world.
But please bear in mind, that this is only a snapshot of scientific concepts. There are many more scientific principles out there, which inform us on the necessity of agile ways of working in your organization. Contact us, if you are keen to learn more, start up or look for improvements in your agility.