Information technology is another fertile, cross-industry field for applying real options. IT now consumes the greater part of corporate capital budgets, and large applications are notoriously risky. But their deployment can be optimized, and the risk minimized, through real-options analysis, according to Mark Jeffery, assistant professor of technology at Northwestern University’s Kellogg School of Management. In a recent paper, Jeffery and co-authors Sandeep Shah and Robert J. Sweeney demonstrated how real-option analysis can determine the optimal rollout of an enterprise data warehouse, via the phase-wise consolidation of data marts.
What’s more, Jeffery argues that real options can better optimize a portfolio of IT investments. The classical application of real options, and the point of much research, is to show that a given investment with a negative NPV may in fact have substantial value, thanks to its embedded options. But in today’s capital-rationed environment, all IT investments are presumed to have a positive NPV, and a substantial one at that. Jeffery therefore advocates calculating the real-options value of positive-NPV projects, to arrive at an “expanded” NPV for each — and an optimal ranking of IT investments.
The trouble is, although there is widespread interest in taking a portfolio approach to managing IT investments, few companies — 24 percent — actually optimize such portfolios, according to a recent survey of 130 senior IT executives conducted by the Kellogg School, DiamondCluster International, and the Society for Information Management. None of the executives surveyed used real options.
In the end, it will take more than research papers and case studies to persuade companies to adopt real options. Numerous objections must be overcome; here are four big ones.
Real options is a “black box.” The sophisticated mathematics (such as partial differential equations) of real options, and the consequent lack of transparency and simplicity, are real concerns. But thanks to more-powerful PCs and spreadsheets, one can model multiple options with little more than a knowledge of high school algebra and binomial lattices, say experts. Jeffery, who has a PhD in theoretical physics, and his research assistant and co-author Shah are devising “little Excel macros that do the binomial model, so you can calculate compound options in a very straightforward way,” he says. Meanwhile, software publishers like Decisioneering now offer off-the-shelf applications for modeling complex real-options scenarios.
“We’ve missed something really important,” comments Martha Amram, chief economist at PLX Systems, a Pasadena, California-based software company, and a prominent real-options author. “To communicate, [real-options analysis] has to be transparent and clear.”
Real options is a new economy tool. It doesn’t help the cause that Enron was considered an innovative user of real options. Some observers maintain, however, that the reputation was deserved, and that use of the tool had little to do with Enron’s financial difficulties or downfall. Meanwhile, loose talk about growth options may have helped fuel the astronomical valuations of some Internet companies before the market bubble burst. Then again, rigorous application of real options might have told a different story. A few years ago, when Amazon.com’s stock was selling for $76 or so, an analysis using real-options theory by UCLA professor Eduardo S. Schwartz pegged its worth at around $12 — a more realistic value, as it turned out.