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A Decision-Making Framework for Project Portfolio Planning at Intel Corporation

Siddhartha Sampath

Decision Engineering Group, Intel Corporation, Chandler, Arizona 85226, siddhartha.sampath@intel.com

Esma S. Gel

School of Computing, Informatics, and Decision Systems Engineering, Ira A. Fulton Schools of Engineering, Arizona State University, Tempe, Arizona 85281, esma.gel@asu.edu

John W. Fowler

Supply Chain Management Department, W. P. Carey School of Business, Arizona State University, Tempe, Arizona 85287, john.fowler@asu.edu

Karl G. Kempf

Decision Engineering Group, Intel Corporation, Chandler, Arizona 85226, karl.g.kempf@intel.com

The work we describe addresses the problem of deciding between project-funding opportunities under budget and headcount constraints. Although the projects lead to products that yield revenue in the market, complex interactions between the projects and products make the selection of a portfolio difficult. Furthermore, the senior managers in the company have a wealth of business intuition that can inform the required decisions. We combine modeling, simulation, and optimization techniques to provide a set of the best portfolios possible from the proposed projects and resulting products. We also provide a rich set of analysis and visualization tools for the decision makers to use in exploring the suggested portfolios and applying their intuition to make the final selection. The resulting interplay between analytics and intuition produces better business solutions through a more focused and effective debate in a shorter time than previously achieved.

Keywords: analytics; binary integer linear program; decision support; elimination by aspects; intuition; portfolio management; practice of OR; simulation.

History: This paper was refereed.

Funding reviews occur regularly in companies offering a variety of products in a number of markets. At any point in time, many product- development projects are in various stages of execu- tion, ranging from those in their initial ramp-up stages to those nearing new-product launch; all re- quire continued funding. Other projects are new and seeking startup funding. In innovative companies, the number of requests usually exceeds the budget avail- able to fund these requests. Management has to peri- odically make decisions on the effective allocation of limited budgets to achieve corporate goals, including profit maximization.

Making these decisions is inherently difficult be- cause of the combinatorial complexity resulting from the number of projects, products, and markets in- volved and their extensive interrelationships. For

example, one project may support many products. Other projects may depend on each other for inter- mediate deliverables. One product may be released into multiple markets, and one market may receive many different products. Product offerings can affect each other synergistically or cannibalistically in the marketplace. These interactions result in a single project or product having different costs and (or) benefits depe