In the book “Reinventing Project Management –The Diamond Approach to Successful Growth and Innovation,” (1) the authors, Shenhar and Dvir, present a model for understanding risk and uncertainty in projects based on a decade or more of research.
For the purposes of this discussion, I will treat risk and uncertainty as the same thing and leave the definitional nit-picking for another time.
What I like about his approach, the Diamond Model, is the relative simplicity of the basic structure and the very helpful practical examples and guidelines provided to make it easy to use in practice.
The authors present a lot of information about how the learning points of the model relate to the main knowledge areas of PMBOK. This is useful because the PMBOK framework is familiar to a lot of people in the world of project management.
The Diamond Model integrates a lot of very solid research from a number of fields into one coherent approach to uncertainty.
This is useful because it takes us beyond the more limited risk view found in run-of-the-mill risk management models.
The model provides a robust framework for thinking about the expected risks and benefits if a project as well as a set of rules and recommended actions for each project type.
Project type is a function of the scores on the respective dimensions, and it is precisely the recommendations about how to manage the various project types that makes the book so valuable.
In essence, the book gives us a model that let’s us identify the key elements of the project approach and the project charter itself. Said another way, we receive powerful assistance to identify the most useful management style for the type of project we have to deliver.
The four dimensions of project uncertainty
Shenhar and Dvir’s project uncertainty model has four dimensions where the bases are labeled:
This base represents the uncertainty of the projects goal, the uncertainly in the market or both. It measures how new the project’s product is to customers, users or to the market in general and thus how clear and well defined the initial product requirements are.
There are three types of novelty:
Understanding novelty helps us make decisions about:
- The time required to freeze product requirements
- How much (or little) we trust the accuracy and reliability of marketing data
This base represents the project’s level of technological uncertainty. It is determined by how much new technology is required.
There are four types of technology:
Understanding technology helps us decide:
- The time required to freeze design
- The intensity of the technical activities
- The technical skills required by the project manager and team
This base measures the complexity of the product, the task and the project organization.
There are three types of complexity:
- Array (or system of systems)
Understanding complexity helps us decide:
- The structure of the project organization
- How best to manage it (i.e., finding the right level of bureaucracy and formality)s
This base represents the urgency of the project-namely, how much time there is to complete the job.
There are four types of pace:
Understanding Pace helps us decide:
- How to do the planning
- How and when to do reviews
- The most useful degree of autonomy for the project team
- The most useful level of involvement of top management (i.e., particularly the most urgent projects)
How to use this model
The authors’ research showed that in failed projects, there were often a mismatch between the risk profile of a project and the management style adopted to run it.
By understanding the specific risks and uncertainties relevant for a particular project, we can break out the critical components and build in the most appropriate activities to increase our chance of success.
It should also be evident that the model expands considerably in the isolated idea of ‘complexity’ and creates a much more versatile and practical analytical instrument for us.
I’ve written earlier about complexity and shared a view of this that classifies complexity into three main categories: simple, complicated and complex.
We can see this structure mirrored in Shenhar and Dvir’s four dimensions which in two cases expand this to four, primarily by sub-dividing the ‘complicated’ category.
In any case, I like the model because I see how it lines up with and builds on a lot of other research that has come out since. This demonstrates to me the robustness of it and that it is worthwhile the investment in time and effort to understand it to the point where we can safely apply it to our projects.
Shenhar, Aaron, Dov Dvir (2005). Reinventing Project Management –The Diamond Approach to Successful Growth and Innovation, Harvard Business School Press, Boston, MA.
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Filed under: Complexity Risk Uncertainty
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