The purpose of Part I was to define projects, project management, and the Process Groups. The five Process Groups and nine Knowledge Areas are the building blocks of every project management life cycle (PMLC). Chapters 4 through 8 presented the robust use of these building blocks. That completes the foundation for our further exploration of PMLC models.
Part II identifies five different PMLCs and discusses their characteristics, strategies for using them, when to use them, and how to adapt the tools, templates, and processes to each life cycle model.
Part II consists of four chapters.
The project management landscape is defined based on two characteristics: goal and solution. They are either clearly defined or not clearly defined. That generates a two-by-two matrix into which all projects fit. In Chapter 2 these four categories were illustrated in Figure 2-1. These four categories are the landscape over which the five PMLC models that were defined in Chapter 2 are distributed. In Part II we will examine each of these five PMLC models and discuss their use in managing the complexity and uncertainty that is characteristic of the projects that populate the four-quadrant project landscape.
The simplest part of the landscape arises in cases where both the goal and the solution are clearly defined. These are what I call Linear and Incremental life cycles. Data gathered from more than 10,000 project managers around the world suggests that approximately 20 percent of all projects fall in this part of the landscape.
Next in complexity are projects for which the goal is clearly defined but the solution is not. These are what I call Iterative and Adaptive life cycles. The testimonial data that I have collected from across the globe suggests that approximately 70 percent of all projects fall in this part of the landscape.
The most complex projects are those for which neither the goal nor the solution are clearly documented. These are what I call Extreme projects. Their complexity comes from the fact that through iteration it is hoped that the goal and the solution will converge to something that has business value. Pure research and development (R&D) projects would be of that type. The same testimonial data referred to above suggests that approximately 10 percent of all projects fall in this part of the landscape.
There is a fourth group of projects in the landscape. Those are the projects for which a solution is clear but the goal is not. Although at first this may seem like a nonsense category, it really isn't. Again pure R&D projects are often of this type. Consider the case where a new technology has been introduced and the question becomes, “Is there any practical use for this technology in our business?” Wal-Mart's investigation of Radio Frequency Identification (RFID) technology is one such example. For the purposes of this book, I am calling these projects extreme in reverse, or “Emertxe” projects.
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