Preparing a Negotiated R&D Portfolio with a Prediction Market


Cédric Gaspoz, Yves Pigneur
Faculty of Business and Economics (HEC), University of Lausanne, Switzerland
{cedric.gaspoz, yves.pigneur}@unil.ch



Abstract

The main objective of this research is to use
prediction markets as negotiation agents, for
supporting R&D portfolio management. To support
this research, we iteratively designed, developed,
operated and evaluated several prototypes. We start by
presenting the weaknesses of the current techniques for
managing R&D portfolio. Then, we intend to
demonstrate that prediction markets correct these
weaknesses in R&D portfolio management.
Furthermore, following a design science paradigm, we
illustrate the design of our artifacts using build-and-
evaluate loops supported with a field study, which
consisted in operating the prediction markets in
different settings.

1. Introduction
R&D portfolio management is a critical task for the
majority of the large companies. Several studies
evaluated the practices in “Fortune 500” companies,
finding that there is neither a single method nor a
solution applicable to all companies [8, 20]. The most
recent investigations [7, 9] showed that to be effective,
portfolio management must apply a mix of various
qualitative and quantitative methods. The use of
quantitative methods presents weaknesses, mainly for
(1) selecting the right criteria, (2) collecting the data,
(3) and negotiating the portfolio between the different
stakeholders.
Whereas many stakeholders, such as the different
business units, are involved in the portfolio decision
process, a “negotiation support systems” could be the
appropriate solution to speed up the process. However,
it will not significantly reduce the communication
effort. We suggest a paradigm shift with a new tool to
address the portfolio selection.
The research assumption is that a prediction market
could improve R&D portfolio management. Prediction
markets are future markets evaluating the projects
potential of a portfolio. Prediction markets collect
information from different actors, who trade on the
market, and aggregate this information in an
automatically negotiated equilibrium price,
corresponding to the valuation of the project. Such
market mechanism addresses the three weaknesses
mentioned above: (1) no more criteria to be explicitly
selected, (2) less data to be collected, and (3) fewer
issues to be explicitly negotiated between actors. These
three activities are replaced by the buy and sell trading
of claims concerning portfolio contents.
For this research, we adopted a design science
method, with its build-and-evaluate loop. We designed
and implemented different versions of prediction
markets, which we operated and evaluated on small
and large-scale experiments.
The next section presents the R&D portfolio
management and its weaknesses. Section 3 gives the
prediction market foundations, its automatic
negotiation kernel, and the advantages in a R&D
context. Section 4 defines the artifact we designed and
describes the main design issues. Section 5 presents the
evaluation phase; we suggest 5 lessons based on the
experiments we managed for operating and validating
prediction markets.
2. R&D Portfolio Management
R&D project portfolio selection is a periodic
activity, which aims at optimizing the research effort of
the company. It enables the company to select a
portfolio which corresponds to its strategic objectives,
without exceeding the resources available. The
selection of a powerful project portfolio is a delicate
exercise. On one hand, it requires wide competencies
of strategic management and the associated tools
regarding the objective criteria. On the other hand, it
necessitates very good competencies in negotiation
regarding the subjective criteria as well as the final
choice of the portfolio composition.
"The portfolio decision process is characterized by
uncertain and changing information, dynamic
Proceedings of the 41st Hawaii International Conference on System Sciences - 2008
1530-1605/08 $25.00 © 2008 IEEE 1