Raul O. Chao

A Theoretical Framework for Managing the New Product Development Portfolio: When and How to Use Strategic Buckets

Developing the “right” new products is critical to firm success and is often cited as a key competitive dimension. This paper explores new product development (NPD) portfolio strategy and the balance between incremental and radical innovation. We characterize innovative effort through a normative theoretical framework that addresses a popular practice in NPD portfolio management: the use of strategic buckets. Strategic buckets encourage the division of the overall NPD resource budget into smaller, more focused budgets that are defined by the type of innovative effort (incremental or radical). We show that time commitment determines the balance between incremental and radical innovation. When managers execute this balance, they are often confounded by (i) environmental complexity, defined as the number of unknown interdependencies among technology and market parameters that determine product performance; and (ii) environmental instability, the probability of changes to the underlying performance functions. Although both of these factors confound managers, we find that they have completely opposite effects on the NPD portfolio balance. Environmental complexity shifts the balance toward radical innovation. Conversely, environmental instability shifts the balance toward incremental innovation. Risk considerations and implications for theory and practice are also discussed.

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

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 organizations 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 managers 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.

Incentives in a Stage-Gate Process

Many large organizations use a stage-gate process to manage new product development projects. In a typical stage-gate process project managers learn about potential ideas from research and exert effort in development while senior executives make intervening go/no-go decisions. This decentralized decision making results in an agency problem because the idea quality in early stages is unknown to the executive and the project manager must exert unobservable development effort in later stages. In light of these challenges, how should the firm structure incentives to ensure that project managers reveal relevant information and invest the appropriate effort to create value? In this paper, we develop a model of adverse selection in research and moral hazard in development with an explicit go/no-go decision at the intervening gate. Our results show that the principals uncertainty regarding early-stage idea quality --- a term we refer to as idea risk --- alters the effect of late-stage development risk. The presence of idea risk can lead the firm to reject projects that otherwise seem favorable in terms of positive net present value. A simulation of early-stage ideas, found through search on a complex landscape, shows that the firm can mitigate the negative effects of idea risk by encouraging breadth of search and high tolerance for failure.

Tolerance for Failure and Incentives for Collaborative Innovation

Most organizations employ collaborative teams to manage innovation projects. Although the use of collaborative innovation teams is a good starting point, an organizations ability to innovate can be enhanced by managing risk-taking behavior through monetary incentive schemes and through an organizational culture that tolerates failure. This article reports the results of two controlled experiments aimed at understanding how tolerance for failure and incentives impact the decisions of individuals engaged in a collaborative innovation initiative. A key element of our experiments is the notion of endogenous project risk, which we define as the explicit link between resources allocated to a project and the likelihood of project success. We observe that when penalties are low, the amount of risk an individual assumes is fairly insensitive to the rewards that are offered. In an analogous result, when individuals make decisions alone (rather than collaboratively), higher tolerance for failure does little to increase the amount of risk an individual is willing to take. Taken together, these results highlight the importance of implicit incentives that are created as a result of project and organizational characteristics.

R&D Intensity and the New Product Development Portfolio

A key metric for assessing innovative activity at the firm level is R&D intensity. R&D intensity is the ratio of a firms R&D investment to its revenue (the percentage of revenue that is reinvested in R&D). Empirical and anecdotal evidence suggests that R&D intensity within an industry tends to be remarkably consistent. Despite this consistency in R&D spending, however, firms differ with respect to their new product development (NPD) portfolio strategy and overall performance. This paper seeks to explain how R&D intensity can be so consistent at the aggregate level, while NPD portfolio strategies and firm performance are so varied at the firm level. We develop a model that considers firm level factors, such as the NPD portfolio composition and risk levels, as well as industry level factors, such as competition intensity and environmental stability. We show how a simple evolutionary process links aggregate R&D intensity and firm level portfolio choices. Our results highlight that R&D intensity alone does not explain firm performance. Rather, it is the proper alignment between R&D intensity (how much the firm invests) and an NPD portfolio strategy (how the firm invests the money) that drives profitability.

R&D Intensity and the NPD Portfolio

A key metric for the assessment of innovative activity at the firm level is R&D intensity. R&D intensity is the ratio of a firms R&D investment to its revenue (the percentage of revenue that is reinvested in R&D). Empirical and anecdotal evidence suggests that R&D intensity within an industry is remarkably consistent. Despite this consistency in R&D spending, firms tend to be differentiated with respect to their NPD portfolio strategy and overall performance. This study aims to explain the observed consistency in R&D intensity for firms within an industry, despite the varying choices in terms of how much the firm invests in R&D and how resources are allocated among projects in a portfolio. We consider the implications of firm level factors, such as NPD portfolio composition, as well as industry level factors, such as competition intensity and environmental stability. We find that R&D intensity alone does not explain firm performance. Rather, it is the proper alignment between R&D intensity (how much the firm invests) and NPD portfolio strategy (how the firm invests the money) that drives profitability. More importantly, the proper alignment critically depends on two industry factors - competition intensity and environmental stability.

Habit Formation from Correlation Aversion

Making plans about how much to consume and how much to invest in risky assets over an uncertain lifetime is a fundamental economic challenge. The leading models of this planning problem use either additive or habit-forming preferences. For the most part, these models assume an individual is either correlation neutral or correlation seeking in consumption, respectively. In this paper, we introduce two habit-forming, correlation-averse preference models. With these preferences, we find closed-form solutions to the classic consumption and portfolio planning problem. Our solutions recommend that a correlation-averse decision maker follow a habit in their consumption plans. While such habits traditionally have been associated with correlation-seeking preferences, our model leads to consumption habits from correlation-averse preferences.

Motivating Participation and Effort in Innovation Contests

The rise of open innovation and crowdsourcing has allowed rms to involve large communities of external users in their innovation process. Unfortunately, user (solver) participation in such innovation contests is not guaranteed. Solvers, who have di erent skill or ability levels, may nd the cost to participate prohibitive. If and when they decide to participate in a contest, the solvers must be induced to exert e ort that delivers the output needed by the rm (seeker). To alleviate possible con icts of interest that may arise when incentivizing both participation and e ort (as opposed to just e ort), the seeker o ers the solvers an incentive plan de ned by a number of awards to induce the solvers to act in the seekers best interest. Most papers in the existing literature focus on incentives for e ort alone and they largely nd that a winner-takes-all award scheme is optimal. In contrast, we establish that multiple awards are needed to balance the trade-o between participation and e ort in settings where solver participation is voluntary.Many firms use external contests to obtain solutions to their innovation challenges. A central managerial concern for these contests is how to screen the population for only the most capable people when the capability of the population is not known. If the manager sets the bar too high, then the contest could fail to receive submissions and the innovation could be delayed or even fail leaving the firm to suffer the consequences. Alternatively, if the bar is set too low, then too many people enter, which leads to increased competition, a lack of effort, and diminished performance, again leaving the firm to suffer the consequences. We study a situation in which the size of a heterogeneous population of solvers is known but the fraction of this population that actually submits a solution to the contest is unknown. We derive the optimal contest design to maximize the performance of the best submission while accounting for the possibility that the contest fails and the associated consequences of such a failure. Our results provide an alternative rationale for why many contests offer multiple awards: firms want to avoid the negative consequences associated with a contest that fails to yield a solution. We also consider alternative levers available to the firm when facing uncertain participation. These include the establishment of performance thresholds and the decision to expand the potential solver population.

Towards a unified model of innovation and technological change

ABSTRACT Innovation and technological change have been at the center of our society for most of the past 50 years. During that time, academics have tried with varying success to study the processes that drive growth in innovation and technology. This paper provides a historical perspective on the trajectory of research on innovation and technological change. Based on our review, we offer three positions that run counter to the status-quo. First, that a model of innovation should explain the dynamics of market competition rather than to simply define the source of economic rents. Second, that the manner in which we should study innovation and technological change is much more behavioral in nature. Third, we need to unpack the organization to make progress in understanding innovation. With this in mind, we develop a taxonomy of the relevant literature in strategy, economics, product development, and technology management. We then propose some principles for modeling innovation and technological change in a manner that brings together these fields of study.

Husk Power Systems: Scaling Up a Start-Up

Husk Power Systems (HPS) provides technologies that generate and distribute electrical power to rural villages in India. Since 2007, HPS has installed 60 mini power plants that power 25,000 households in more than 250 villages, impacting the lives of approximately 150,000 people in rural India. This case details the operational and strategic challenges associated with scaling up HPS, and provides details related to technology development, suppliers, operational capabilities, costs, and market adoption.