The Public Sector R&D Enterprise: A New Approach to Portfolio Valuation

A New Approach to Portfolio Valuation

P. Linquiti

• Publisher: Palgrave Pivot
• Year: 2015
• ISBN:
  9781137542090
• Topic: Economics
• Subtopic: Public Finance
• Index: Economics

The Public Sector R&D Enterprise combines a primer on how government R&D programs actually work with a sophisticated methodology for prospectively putting a dollar figure on the value of R&D investments before they are made.

1

Research and Development: Opportunities and Challenges

Abstract: Chapter 1 describes the tension between the goals of policymakers who seek to make research and development (R&D) a cornerstone of national economic progress and the reality that R&D programs operate in a complex environment where program design and implementation is challenging and success is difficult to measure. The chapter also summarizes how the rest of the book offers insights and tools to improve the opportunities for success in government R&D programs.

Keywords: DOE energy efficiency programs; Government research and development; R&D management; R&D portfolio valuation; R&D risks

Linquiti, Peter D. The Public Sector R&D Enterprise: A New Approach to Portfolio Valuation. New York: Palgrave Macmillan, 2015. DOI: 10.1057/9781137542090.0005.

The global recession that began in 2008 had a profound effect on investments in research and development (R&D). The yearly growth rate in R&D spending by both the public and private sectors in developed countries fell to half of pre-recession levels (OECD, 2014a). Private R&D spending has since shown signs of recovery, but public spending has lagged behind. That notwithstanding, most governments around the world—not just OECD members—continue to affirm a goal of, at a minimum, maintaining R&D spending, or for most countries, of increasing R&D spending significantly (OECD, 2014b). China, for example, is on track to become the world’s largest R&D performer by 2020 if current trends persist (OECD, 2014a).

Such governments see R&D, and innovation policy more broadly, as a prerequisite for dealing with daunting societal challenges such as slow economic and employment growth, the healthcare needs of ageing residents, the transition to a low-carbon economy, and in some countries, rapid population growth. At the same time, R&D is also seen as a means of exploiting opportunities in fields like information and communication technology, biotechnology, nanotechnology, advanced manufacturing, “big data,” agriculture, and national defense. For these reasons, countries tend to view fostering R&D as an integral and vital component of public policy (Link & Vonortas, 2013).

The United States is no exception. In 2011, a total of about $429 billion was spent by the public and private sectors on R&D (National Science Foundation, 2014b) and President Obama has called for even more R&D spending (Executive Office of the President, February 2011). When it comes to government spending, the public sector R&D enterprise is a large one; the Federal government spends $130 billion per year on R&D.¹

Despite the size of this investment, however, the Science of Science Policy Task Group concluded that “the rationale for specific scientific investment decisions lacks a strong theoretical and empirical basis” (ITG, 2008, p. 1) and the White House has told agencies to “improve management of their R&D portfolios and better assess the impacts of their science, technology, and innovation investments” (Executive Office of the President, 2010, p. 2). Such concerns reflect a global trend of increasing demands from elected officials that public R&D administrators demonstrate the return on their investment of taxpayer funds (OECD, 2014b).

Responding to such demands, however, is often difficult because public sector R&D projects are not typically selected or managed with quantitative methods. Instead, qualitative review is the norm because policymakers often believe that available tools undervalue the benefits of R&D investments, especially those where potential payoffs may be far in the future (Vonortas & Desai, 2007). Several investigators have offered more robust quantitative techniques to supplement qualitative judgments during R&D portfolio formation, valuation, and management (Vonortas & Desai, 2007; Tassey, 2003; Casault, Groen, & Linton, 2013).

This book continues along the same lines. My goal here is to make a methodological contribution focused primarily on the process of forming and valuing portfolios of R&D projects.² In a study of 39 R&D initiatives, the National Research Council concluded that “how programs were organized and managed made a real difference to the benefits that were produced” (NRC, 2001, p. 6). My hope is that this exploration of the topic will, at a minimum, clarify our understanding of R&D programs, and at best, increase the likelihood of their success.

R&D programs exist in a complex environment, and successful programs must be thoughtfully designed and well executed. Before diving into the topic of portfolio valuation, therefore, I start in Chapter 2 with a broad overview of the public sector R&D enterprise, particularly as it operates in the United States. I assume the reader has had little exposure to these topics and have structured Chapter 2 as a primer-like review of the basic structure and operation of Federal R&D programs.

The discussion in Chapter 3 focuses on the process of deciding which R&D projects should be funded and how they can be combined into a coherent portfolio. I look at management practices typically used in the private sector, and then summarize similar efforts in government R&D programs. With this foundation in place, I turn to original research in Chapter 4 and present the methodology and results of an analysis of a portfolio of projects sponsored by the Department of Energy between 2002 and 2004.

As explained in Chapter 5, my analysis of these projects suggests that traditional methods of valuing R&D investments significantly understate their benefits. In addition, I demonstrate that the typical government practice of evaluating individual R&D projects in isolation, without regard to potential relationships among them, makes it almost impossible to characterize the risks being taken with taxpayers’ money. Finally, I conclude that proactive management of government-sponsored R&D, including interim performance reviews that can lead to project expansion, substantive redirection, or early termination, can improve outcomes as compared to a hands-off style of management.

Finally, while Chapter 4 demonstrates the feasibility of more rigorously quantifying the benefits of R&D projects, and the risks of the portfolios they comprise, I observe in Chapter 6 a few areas for improvement and briefly sketch methods for moving forward.

Notes

  1   This spending can be broken into categories. Basic research is the study of scientific phenomena without direct regard for the practical application of new knowledge that may be developed. Conversely, applied research attempts to generate new knowledge in order to meet a specific need. Development entails efforts to produce devices, systems, and methods to put new knowledge into practical use (AAAS, 2013).

  2   Some of the material in this book, especially in Chapter 3 and 4, draws directly from my dissertation (Linquiti, 2012b).

2

A Primer on the Public Sector R&D Enterprise

Abstract: The US government spends $30 billion per year on applied, nondefense R&D. Chapter 2 provides a holistic overview of how this R&D enterprise operates. Context is set with a review of the political, economic, and institutional forces that shape R&D programs. A logic model framework is used to describe the inputs, activities, outputs, outcomes, and impacts of public sector R&D. This expansive approach makes the subject more complex, but protects the reader from analytic myopia—a failure to recognize all of the drivers of success and failure. The primer aspires to provide readers who have a limited background in the field a readily accessible entry point to the world of government R&D programs.

Keywords: economics of R&D; government research and development; logic models; politics of R&D; R&D program evaluation; technology diffusion

Linquiti, Peter D. The Public Sector R&D Enterprise: A New Approach to Portfolio Valuation. New York: Palgrave Macmillan, 2015. DOI: 10.1057/9781137542090.0006.

This chapter describes a framework for thinking holistically about publicly supported R&D investments that are intended to stimulate the development and deployment of new technologies. My audience is students, public administrators, and others who seek a basic primer on the design, implementation, and evaluation of these types of public sector R&D programs. The focus here is on the United States and, in particular, on Federal (as opposed to state, regional, or local) programs.

Before beginning, I should point out that the framework does not address basic research or defense R&D. Analysis of basic research initiatives, intended to generate new knowledge without regard to potential commercial application, brings with it additional theoretical, practical, and policy considerations that go beyond those typically relevant to applied R&D. Rather than extend the proposed framework to address basic research, I instead focus more narrowly (and I hope more usefully) on applied R&D.

As for defense R&D, the presence of a single, large customer (e.g., a national defense ministry) means that the market dynamics for new defense technologies are very different than for nondefense technologies that compete in a market with multiple private buyers and sellers. Defense R&D also occurs in an environment marked by a much closer relationship between producer and customer than is the case in commercial markets where arms-length relationships are far more common. Finally, attaching a monetary value to the benefit of enhanced national security—presumably an outcome of successful defense R&D—would be a daunting analytic challenge.

Even after excluding basic research and defense R&D, considerable sums of money are still at stake. The Federal government spends about $30 billion on nondefense, applied R&D in fields such as health, energy, agriculture, transportation, and the environment (AAAS, 2013).

2.1Overview

The framework that I describe here aims to identify a comprehensive set of policy, political, technical, and market factors that may affect the success or failure of an R&D initiative. The framework is multidisciplinary, meaning that it includes economic considerations such as market failures and the macroeconomy, political considerations such as earmarks and lobbying, and institutional behavior such as interagency coordination and bureaucratic rules. Why take an expansive approach? Doing so makes the subject more complex, but a core tenant of the modern discipline of public policy analysis is that no single mode of inquiry offers a definitive vantage point from which to examine a public challenge; instead, complementary insights from multiple perspectives yield a more robust understanding (deLeon & Martell, 2008; Stone, 2012). What’s more, a narrow perspective, perhaps focused on only one element of the R&D enterprise, runs the risk of analytic myopia—a failure to recognize all the important factors that ultimately determine whether a new program succeeds or fails.

The framework is not an explanatory model per se; instead, it is conceptual, intended to offer administrators a way to locate their work in a broader context and identify key linkages among disparate factors. Not all of the factors identified in the framework will apply to all R&D initiatives. Rather, the framework can be used as a checklist to ensure that important factors are not overlooked during the design, implementation, and evaluation of public R&D programs. Of course, depending on the specific circumstances of a particular program, other factors may also be relevant.

The framework is structured as a logic model, so named because of the implicit chain of if-then statements embedded in it. Logic models are a common tool in the field of program evaluation and provide a systematic way of characterizing public (and nonprofit) initiatives (Newcomer, Hatry, & Wholey, 2010). Logic models draw causal linkages from the initial inputs for a program, through its operations, and on to its final impacts. Mediating factors that affect the operation of the causal relationships can also be depicted in a logic model. Because of its comprehensive nature, a logic model provides a useful way of describing public sector R&D initiatives. For an excellent summary of logic models applied to the R&D process, see Jordan (2013).

My proposed framework for analyzing public sector initiatives aimed at applied R&D is presented in Figure 2.1 The five core components of the model are arrayed from left to right, beginning with inputs used in the R&D program and ending with the ultimate impacts of the program on society writ large. The framework also identifies three sets of mediating factors which, though they exist outside the R&D program itself, may have a profound effect on it. Finally, the framework notes the potential for program evaluation, a process by which systematic efforts are made to understand the results of the program. The remainder of this chapter offers some observations on each of the five components of the logic model, as well as on the three sets of mediating factors and on the program evaluation process.

FIGURE 2.1 The public sector enterprise for applied research & development

Source: Adapted from Linquiti (2012b).

2.2Mediating factors: policy objectives

Before describing the core components of the typical publicly funded R&D initiative, it is helpful to review the reasons why policymakers might create such an enterprise in the first place. Rarely is a single rationale put forward; rather, mul...

Table of contents

• Cover
• Title
• 1  Research and Development: Opportunities and Challenges
• 2  A Primer on the Public Sector RD Enterprise
• 3  RD Portfolio Valuation and Formation
• 4  Public Sector RD Valuation: A Practical Example
• 5  Recommendations for Public Sector RD Managers
• 6  Next Steps in Valuing RD Portfolios: A Research Agenda
• References
• Index