Revenue Driven Resource Allocation: Funding Authority, Incentives, and New Product Development Portfolio Management

Abstract

The first step in transforming strategy from a hopeful statement about the future into an operational reality is to allocate resources to innovation and new product development (NPD) programs in a portfolio. Resource allocation and NPD portfolio decisions often span multiple levels of the organization's hierarchy, leading to questions about how much authority to bestow on managers and how to structure incentives for NPD. In this study, we explore how funding authority and incentives affect a manager's allocation of resources between existing product improvement (relatively incremental projects) and new product development (more radical projects). Funding may be either fixed or variable depending on the extent to which the manager has the authority to use revenue derived from existing product sales to fund NPD efforts. We find that the use of variable funding drives higher effort toward improving existing products and developing new products. However, variable funding has a subtle side effect: it induces the manager to focus on existing product improvement to a greater degree than new product development, and the relative balance in the NPD portfolio shifts toward incremental innovation. In addition, we highlight a substitution effect between explicit incentives (compensation parameters) and implicit incentives (career concerns). Explicit incentives are reduced as career concerns become more salient.innovation, new product development, authority, incentives, resource allocation, portfolio

Blinded by Experience: Prior Experience, Negative News and Belief Updating

“…In this study, we use a paradigm of deciding where to allocate funding within a business. This is a common operational decision that can be found not only in the research and development context (Chao et al 2009), but also other settings such as capacity allocation (Campbell and Frei 2011) or supplier selection (Van Mieghem 1999). An additional benefit of this paradigm is that it draws on prior research (Staw 1976) and extends it through the manipulation of experience.…”

“…As such, decision makers observe the consequences of a particular action and then must use this information to determine their next action. Illustrative examples can be seen in a wide variety of contexts, including labor scheduling (Kesavan, Staats and Gilland 2014;Tan and Netessine 2014), production tool choice (Upton 1997;Ramdas et al 2010), job shop scheduling (Fryer 1975), local capacity decisions (Campbell and Frei 2011), inventory ordering (van Donselaar et al 2010), pricing (Phillips, Şimşek and Ryzin 2015), research and development investment (Chao, Kavadias and Gaimon 2009), and Bayesian models (Brown, Lu and Wolfson 1964) more generally. In these and other models, individuals are assumed to use Bayesian updating to generate their beliefs, which ultimately determine their next action.…”

Portfolio Management in New Drug Development

“…Thus, firms need to ensure that those responsible for strategic choices and executing on them are rewarded appropriately for their decision making, especially in the high risk world of new drug portfolios. Chao et al (2009) examine the incentive problem for managers allocating resources between incremental and radical innovation projects, as a function of funding authority. When funding is variable (i.e., manager can use revenue from existing product sales to fund NPD efforts), the manager is induced to focus on incremental rather than radical innovation.…”

A methodology for assessing the effect of portfolio management on NPD performance based on Bayesian network scenarios

“…Project termination quality may positively affect the success of portfolios and prevent portfolios from deviating investments into non-strategic projects (Chao, Kavadias, & Gaimon, 2009). Consequently, new product success rate would be improved (Martinsuo & Lehtonen, 2007).…”