Portfolio Management in New Drug Development - Innovation and Marketing in the Pharmaceutical Industry - page 112

value measures should be highly correlated, it is still open as to the extent to which
both measures are related to ex-post value. In other words, which measures have
greater predictive power? Does the firm or the market do a better job of valuing a
new drug? Do firms know better because they have internal know-how that gives
them better insights over the prospects of various projects in their portfolio? Or is it
possible that the market mechanism can efficiently price the value of various proj-
ects due to the “aggregate wisdom” of investors?
In addition, accounting for synergies between projects and pipelines in a portfolio
is still an open challenge. Research such as Girotra et al. ( 2007 ) and Blau et al. ( 2004 )
attempts to model the interaction effect of multiple projects. Yet, a systematic study
of how organizational capabilities, know-how, and market needs come together can
enhance the understanding of valuing portfolios. Modeling external shocks that can
affect multiple projects in a portfolio alongside internal interdependencies will
enhance understanding of prioritizing projects in a portfolio. Using Grewal et al.
( 2008 )'s descriptors, does the diversity from higher portfolio breadth truly counteract
the positive synergy from a lower portfolio breadth with greater resources allocated
to fewer areas? Are firms diversifying portfolios as a result of competitive pressures
akin to a “Prisoner's Dilemma” or because this is the most value-adding strategy?
We can further our understanding of portfolio diversity by considering all sources
of diversity, not just in terms of therapeutic areas. For instance, partner diversity
(work with few or many other firms in collaborative efforts) and product-market
diversity (potential presence in multiple geographic and product segments) can also
be further investigated to determine whether portfolio risk and value are optimally
traded off with such choices.
Drawing upon Grewal et al. ( 2008 ), further investigations on the key descriptors
of a portfolio and the key metrics that firms should use to measure portfolios' worth
needs to be undertaken.
Further implications of data visualization and presentation also need to be
explored. Measurement of a portfolio's state can involve hundreds of metrics rang-
ing from extremely granular measures at the project-level to projections in multiple
dimensions at the aggregate level. The literature on managerial biases suggests that
the problem of managerial decision making based on such complex data is tied to
how data is presented and interpreted. Do scoring models and bubble charts, so
often favored by managers, enable optimal portfolio decision making? Empirical
research can investigate the biases that impact portfolio management decisions as
managerial judgment continues to be a key ingredient alongside analytical
methods.
For portfolio optimization, a rich literature has contrasted the merits of incre-
mental versus radical innovations. However, the choice for firms is usually not
“either-or” but how much of each type to include in the portfolio. Hence, research
on optimal mixtures of incremental and radical innovations would push the frontier
closer to the actual decision problem for pharmaceutical firms. While tools and
frameworks exist for managing portfolio risk and return (Day 2007 ), an assessment
of how these frameworks translate into innovation outcomes would enhance under-
standing of what works and what does not.