The Stacey model is a framework developed by Ralph Stacey that categorizes complex problems into four domains: simple, complicated, complex, and chaotic. The model considers the degree of certainty of the problem and the level of agreement on what needs to be done.
Simple: These are problems that are well-defined, with clear goals, and solutions that have been tried and tested before. There is a high level of certainty, and everyone agrees on what needs to be done. In this domain, traditional project management approaches work best.
Complicated: These are problems that require expertise, analysis, and multiple steps to solve. There is some level of uncertainty, but experts can agree on the approach. In this domain, traditional project management approaches can work, but some Agile principles such as iterative development and frequent feedback can also be useful.
Complex: These are problems that are unpredictable and have many interdependent factors. There is a high level of uncertainty, and no one knows the best solution. In this domain, Agile approaches such as Scrum and Kanban work best because they allow for experimentation and adaptation as the project progresses.
Chaotic: These are problems that are urgent, unpredictable, and require immediate action. There is no agreement on what needs to be done, and there is a high level of uncertainty. In this domain, Agile approaches that emphasize rapid experimentation and quick decision-making, such as Lean Startup, can be useful.
The Stacey model recognizes that not all problems can be solved with the same approach. Each problem has unique characteristics and requires a different level of complexity and uncertainty to be addressed. In project management, it's important to understand the nature of the problem you are trying to solve to determine which approach will be the most effective.
The simple and complicated domains are more straightforward and can be solved with traditional project management approaches that rely on proven methods and techniques. These domains require a clear understanding of the problem, the goals, and the steps required to achieve those goals. In these cases, a project manager can rely on techniques such as Waterfall or Six Sigma to plan, execute, and deliver the project.
On the other hand, the complex and chaotic domains require a different approach. These domains are characterized by uncertainty, unpredictability, and a lack of clear agreement on the best course of action. In such cases, it's important to use Agile approaches that emphasize flexibility, experimentation, and adaptability. Agile methodologies such as Scrum, Kanban, and Lean Startup are designed to address complex and unpredictable problems by allowing teams to iterate, experiment, and learn as they progress.
By using the Stacey model to categorize projects, organizations can select the most appropriate approach for each project. This can help teams achieve better outcomes by matching the approach to the problem at hand. Using the Stacey model can also help teams avoid using an overly rigid or inflexible approach to a problem that requires more experimentation and adaptability.
In summary, the Stacey model provides a useful framework to categorize problems based on their level of complexity and uncertainty. By doing so, organizations can choose the most appropriate approach for each project, whether that be a traditional project management approach or an Agile approach.
Stacey, R. D. (1993). Strategic management and organizational dynamics: The challenge of complexity. Pearson Education.
Larman, C., & Vodde, B. (2010). Scaling lean & agile development: thinking and organizational tools for large-scale Scrum. Pearson Education.
Schwaber, K. (2004). Agile project management with Scrum. Microsoft Press.
Sutherland, J., & Schwaber, K. (2011). The Scrum guide. Scrum.org.
Highsmith, J. (2009). Agile project management: creating innovative products. Addison-Wesley Professional.