Managing trade-offs between conflicting goals through a portfolio visualization process

摘要

Portfolio optimization processes help managers understand the costs of achieving performance goals and the trade-offs in the performance of one business measure versus other business performance measures.A good portfolio optimization process makes it possible to negotiate goals and constraints on important key performance measures interactively and collaboratively,at the same time being fully aware of the price being paid to achieve one goal at the expense other goals.This article advocates a gradient search process,instead of a traditional linear programming or mixed integer linear programming methods to build thousands of optimum portfolios from an inventory of investment opportunities.The performance levels of those portfolios are then analyzed interactively with a visualization tool to negotiate collaboratively the trade-offs between goals and resource levels for the corporation or business unit.The portfolio visualization process described in this article begins by asking asset managers to define different operational strategies and acceptable performance exchange rates for various key performance measures.Combinations of operational strategies and performance exchange rate strategies each create a portfolio strategy and a gradient in a multidimensional resource space.For each portfolio strategy,the gradient search (or greedy algorithm) creates dozens of optimum portfolios,each at different resource levels and with different results in key performance measures.Thousands of optimal candidate portfolios are created and stored,and the coupled visualization tool enables them to be interactively and collaboratively filtered.This powerful combination of technologies allows asset managers to explore the effects of resource constraints and performance goals at specified levels of confidence on dozens