Utilization of Simulation Modeling to Optimize the Project Portfolio Management Process

This paper presents a new approach for the project management practice of selecting projects that maximize value for a given company; and incorporates numerical analysis and simulation to optimize the project selection process to maximize lifecycle profits. Project portfolio management is the continuous process of selecting and managing the optimal set of projects that deliver the maximum value to the business. It is a dynamic decision-making process, enabling management to optimize its finite set of resources to focus on projects that maximize profits, do not constrain the company’s financial and resource capacity, and are strategically aligned with their business goals.

The process a company undergoes when selecting its portfolio of projects is largely, to date, not standardized. Some companies concentrate on projects that revolve around their core competencies, while others attempt to expand their product offerings by taking on projects that satisfy new and untapped market segments. When researching why companies select the products they do, the resulting data shows no conclusive trends. According to Donald Reinertsen, many companies prefer to use intuition rather than quantitative analysis when making these decisions. Our approach will allow companies to use data-driven modeling to optimize their portfolio of products, rather than simply relying on human intuition.

Our model is based on three data sets: a set of resources in the company, a set of product development projects that the company is currently working on, and a new development project to consider. The resource data set consists of a pool of employees, differentiated by discipline, pay rate, efficiency, availability, and project allocation. The second data set is the set of product development projects that the company is currently working on, differentiated by type, schedule, sale price per unit, demand, unit manufacturing cost, development expense, historical resource requirements, and current resource allocation. The new development project the company is considering adding is characterized by the same attributes.

The model answers the questions in the following decision tree. (1) Do we add a new development project? (2) If yes, do we drop or delay an existing project(s)? (3) If yes, which existing project(s) do we drop or delay? The structuring of the model is as follows: the company inputs the required resource and project data, and the model calculates the optimal method of integrating a new project into the current portfolio structure, as well as the corresponding effects this integration has on the project schedules and the company’s cash flow. Our work introduces a new approach to estimate the historical development capacity for each project type. We also develop an approach to use this historical data to more realistically estimate project delays as the decision to drop or delay projects is considered.

The integration of a new project into the company’s portfolio of projects is based on the simulation analysis of development capacity, lifecycle profits, and cost of delay. A new project is added to the portfolio if there is enough development capacity, meaning the company has the required number of resources and available cash flow to finance the project. If the company needs the new project to start immediately, the current project with the lowest lifecycle profits is dropped and the new project is added. Lifecycle profit equals lifecycle revenue minus lifecycle cost, where the lifecycle cost is the sum of the development expense and manufacturing cost. These metrics are affected by supply, demand, utilization, and efficiency. If the company’s timeline is flexible, the projects with the lowest cost of delay are delayed and resources are reallocated. Cost of delay is calculated as the additional cost (in reduced lifecycle profits) of delaying a project by a certain amount of time. Thus, lifecycle profits and cost of delay are interrelated. The simulation model runs through multiple iterations and scenarios based on the input given by the company to optimize the schedule and resource utilization of projects in its portfolio.