Organizations have long struggled to reduce the uncertainties of new product development. Numerous knowledge sources have validated management's heightened attention to the truly debilitating costs of product slippages, launch failures and reduced market penetration. For example, a study by PRTM Inc. found that 70 percent of companies it surveyed were dissatisfied with their results in managing new product development (1).
Countless papers have been written on improving project execution, but relatively few provide guidance to executives trying to manage resource conflicts arising in multi-project environments. Enterprise resource planning (ERP) software and development chain management (DCM) tools are expensive, address broader business issues and do not provide much insight into this particular problem. Project management software (e.g., MS-Project) provides some capacity management tools, but is clumsy to use and not helpful in communicating results to operations management. In short, there are few tools or metrics associated with project portfolio management or development department utilization that are useful for real-time decision support.
Eliyahu Goldratt is generally credited with the mathematics and concepts behind the Theory of Constraints (2). His work describes how to optimize the performance of complex systems through management of critical constraints. This paper applies his techniques to a portfolio of engineering projects. It suggests metrics of development capacity and a capacity-modeling procedure that identifies both constraints and under-utilized assets. It discusses an interactive tool that evaluates different portfolio scenarios. Use of similar tools has reduced chronic planning miscalculations and improved the performance and predictability of engineering teams.
A development organization decomposes into collections of assets with differentiated skills and capabilities. (In this context, assets can be people or capital equipment). Some assets are dedicated to a single project while others are shared among multiple projects. But even people dedicated to a single project can have legacy responsibilities that can interrupt their focus and progress. Constraints are not static. Assets constrained during one time period may be different from assets constrained in another.
At the concept level, the Theory of Constraints describes a dynamic shown in Figure 1. For a multi-project development organization, increasing project load forms the X-axis and increasing results forms the Y-axis. At modest loads, the organization is under-utilized and the delivered results can linearly track increases in load. This relationship continues until the first constraint is reached. At this point the organization's ability to deliver results in additional projects begins to flatten. Somewhere near this point, the total delivered result peaks (arrow). If projects continue to be added, inefficiencies due to multitasking and inter-project interference occurs. More assets become saturated. Soon, delivered results decline. The Theory of Constraints demonstrates that the decline begins well before the 100 percent load point (represented by the dotted line).
[FIGURE 1 OMITTED]
A good analogy is a superhighway. The theoretical maximum traffic load on a multilane superhighway is greater than the actual sustainable traffic load. As traffic flow approaches the theoretical maximum, any driver touching his brakes, or slowing down, will result in the cars around him doing the same. This collective behavior creates traffic oscillations, i.e., variations in flow familiar to anyone who has driven in heavy traffic. The net sustainable volume flow stabilizes at a point well below the theoretical limit. If additional drivers attempt to enter the highway, the volume flow is further reduced.
The Theory of Constraints describes how to best attack a multiplicity of constraints. …