978-1259539060 Chapter 7 Lecture Notes

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Instructor’s Manual

Chapter 7

SYNOPSIS OF CHAPTER

This chapter overviews the most commonly used qualitative, quantitative, and combination

methods used to evaluate new product development projects. The chapter emphasizes that each

method has its strengths and weaknesses, and that most firms will (or should) use a combination

of methods in order to triangulate their information about a project’s prospects.

The chapter begins by discussing the role of the development budget, including capital rationing,

and differences in R&D spending across industries and across firms within industries. The

chapter then reviews popular quantitative methods (e.g., NPV, IRR, Real Options methods) for

project valuation, then turns to qualitative methods (e.g., screening questions, Qsort, balancing

the company’s R&D portfolio), and methods that are both quantitative and qualitative (e.g.,

conjoint analysis, data envelopment analysis).

TEACHING OBJECTIVES

1. Familiarize students with the wide variety of methods available (both quantitative and

qualitative) to evaluate innovation projects.

2. Highlight the important role played by managerial assumptions in the accuracy and utility

of any measure used.

3. Emphasize the importance of a balanced R&D project portfolio (i.e. advanced R&D,

breakthrough, platform, and derivative).

LECTURE OUTLINE

I. Overview

a. New product development is inherently risky and expensive, putting pressure on managers to

make careful choices among projects.

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b. Firms use a mix of formal, informal, quantitative and qualitative methods when selecting

and managing innovation projects and each of these methods has its own strengths and

weaknesses. Often the choices are driven by strategic implications rather than strictly

financial analysis (this is a good point to have students discuss some of the strategic

implications considered in Bug Labs’ decision about which modules to develop).

II. The Development Budget

a. Many firms use capital rationing (a fixed R&D budget and project rankings) to choose

between valuable projects. Firms might establish this budget based on industry benchmarks,

historical performance benchmarks and/or on a desired level of R&D intensity.

b. Expenditures on R&D vary widely between industries and between firms in the same

industry.

Show Figure 7.1

i. For example, as shown in Figure 7.X Intel’s R&D intensity is significantly higher

than the industry average (20 percent versus 11 percent for semiconductors and

electronic components), and Pfizer’s R&D intensity is significantly less than the

industry average (13 percent versus 16 percent for drugs). The table in Figure 7.2

highlights the impact of firm size on R&D budgets.

Show Figure 7.2

b. New ventures often have to rely on external financing, family, friends, and/or personal debt

because technology start-ups often have an unproven technology, an unproven business

concept and/or an unproven management team. Three additional sources of financing are:

i. Government grants and loans from agencies such as the Small Business

Administration in the U.S. or the Enterprise fund in the UK.

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ii. Angel investors are similar to venture capitalists but without the limited

partnership structure. Angel investors usually fund projects under $1 million.

iii. Independent or corporate venture capitalists invest on average $10.5 million

in each project and usually specialize in one or a few industries in which they can

leverage their expertise. Financing is usually accomplished through a complex

debt-equity hybrid contract. Corporate venture capitalists are organized in one of

two ways, via an internal venturing group or as a dedicated external fund. The

pros and cons of each structure are summarized below:

1. Internal venturing groups are in a better position to use the firm’s

expertise and resources to help a new venture succeed. Entrepreneurs may

be concerned about the larger firm expropriating the entrepreneur’s

proprietary technology under this structure.

2. Entrepreneurs are more likely to trust a dedicated external fund because

it is less likely that these funds will have the expertise or desire to steal their

ideas. On the downside, the ability of the entrepreneur to leverage any of the

larger firm’s non-financial resources is more limited.

III. Quantitative Methods for Choosing Projects

Discounted cash flow and real option analyses differ in that the real options approach facilitates

the consideration of a project’s strategic importance. Both of these approaches allow rigorous

mathematical and statistical comparisons of projects. The accuracy of these methods is,

however, questionable because the value of a new technology is difficult to know in advance

and because these methods favor short-term low risk investments. For example, Intel’s

investment in DRAM technology enabled Intel to develop microprocessors, which turned out to

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be a very profitable business. From a NPV perspective this project is likely to have been

considered a total loss.

i. Discounted Cash Flow Methods (NPV & IRR) rest on estimates of future returns,

payback period, risk, and the time value of money. The NPV asks what the project

is worth today and the IRR asks what rate of return does this project yield.

1. Net Present Value (NPV) compares the present value of cash inflows to the

present value of cash outflows. In Figure 7.3, the present value of the future

cash flows (given a discount rate of 6%) is $3,465.11. So, if the initial cost

of the project were less than $3,465.11, the net present value of the project is

positive.

Show Figure 7.3

If cash inflows are expected to be roughly equal from year to year for a very

long period of time, the value of them can be calculated as an annuity. The

present value of C dollars per period, for t periods, with discount rate r is

given by the following formula:

Annuity present value = C X 1-{1/(1+ r )

}

Perpetuity present value = C X 1/r

Managers also consider the discounted payback period. In the above

example, if the initial investment was $2,000 it would be paid back between

the end of year two ($1,833.40) and the second month of year three

($166.60).

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Year Cash Flow

1 $ 934.40

2 $1,833.40

3 $2,673.02

4 $3,465.11

2. Internal Rate of Return (IRR) identifies the discount rate that makes the

net present value of the investment zero and is difficult to calculate when

cash flows arrive in varying amounts per period because there can be

multiple rates of return.

ii. Real Options thinking is most useful when there is uncertainty (and there

usually is high uncertainty when technology trajectories are considered) and when a

firm’s investment in its own learning, development of new capabilities and the

creation of opportunities are important factors in the decision making process.

There is some empirical evidence that a real option approach results in better

investment decisions.

1. Real options are analogous to call options on a stock. A call option gives

the investor the right to buy the stock at a specified price (i.e. exercise price)

in the future. Examples of this type of investment decision are shown in

Figure 7.4.

R&D costs = Call option price

Costs to capitalize on R&D = Exercise price

Returns to R&D investment = Value of the stock purchased with the call

option

Show Figure 7.4

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The value of a call option rises with the value of the stock, dollar for dollar

(45° angle) once the option is “in the money” and is zero otherwise.

Show Figure 7.5

2. The analogy can be stretched too far, however. Technology investments

often do not conform to the same capital market assumptions upon which

the approach is based. For example,

a. Call options are relatively inexpensive but real options can be very

expensive because firms may have to make large investments in a

technology before they can learn whether or not the real option is

valuable.

b. Call option value is independent of the call holder’s behavior but real

option value is highly dependent on the resources (e.g. dollars,

capabilities, complementary assets, strategies) a firm invests in

developing a technology.

IV. Qualitative Methods for Choosing Projects

a. Most firms will use both quantitative and qualitative evaluation approaches (ranging from

informal discussions to highly structured decision processes) because many of the factors

important to the decision are extremely difficult to quantify and attempts to quantify these

factors can lead to misleading results.

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b. Boeing’s development of the Sonic Cruiser is an example of a development project that may

not be profitable but may at the same time be necessary when the importance of firm

capabilities is considered.

c. Screening Questions are organized into categories (see below) and are used by managers to

structure technology project investment discussions. If managers want to formalize the

process they can utilize a scoring mechanism (i.e. scaled responses to each question like

“Project fits closely with existing competencies” to “Project fits poorly with existing

competencies”) that can then be weighted according to importance. Sample screening

questions follow (a more extensive list can be found in the text):

1. Role of Customer―How big is the market of likely customers and

what types of marketing will reach them best? How will the customer

value the product relative to substitutes? How will the customer

perceive the ease-of-use of the product (e.g. complements, training,

etc.)? How will the product be distributed?

2. Role of Capabilities―What affect will the new project have on current

core competencies (e.g. leverage, obsolete). Will the firm be able to

handle the possible cash flow implications? What new competencies

will the firm have to develop and will these new competencies help the

firm achieve its strategic intent?

3. Project Timing and Cost―Does the firm have a choice with regard to

entry timing (i.e. does the firm have the capabilities to be a first

mover)? How variable are the projected costs and learning curve

effects?

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d. The Aggregate Project Planning Framework focuses a firm’s attention on the

mix of development projects (advanced R&D, breakthrough, platform, and derivative) in its

R&D portfolio in order to determine whether the projects are consistent with the company’s

resources and strategic intent. The framework also enables firms to determine whether its

portfolio is balanced between projects with short and long–term payoff horizons. It is

important to emphasize this balance to students: too much focus on short term projects can be

profitable in the immediate term but leave the company with no long-term prospects, and too

much focus on the long-term can leave the firm strapped for cash in the short run. To create

the map managers categorize their existing projects according to the resources required and

the parts of the company’s product line they support.

i. Advanced R&D projects are necessary to the development of cutting

edge strategic technologies (e.g. Honda’s work on hydrogen fuel cells). If firm’s

portfolio consists entirely of advanced R&D projects the firm may not be able to

sustain itself in the short term (i.e. no short term cash flows). There may be no

obvious immediate commercial application.

ii. Breakthrough projects incorporate revolutionary new product and

process design technologies into a new product — that is they are oriented around

a specific commercial application (e.g. Honda’s development of Insight).

iii. Platform projects generate fundamental improvements in the cost,

quality, and performance of a technology versus prior generations and are designed

to serve a core group of customers (e.g. Hunter’s “Care Free humidifier and

Toyota’s Camry).

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iv. Derivative projects involve incremental changes in products and/or

processes (e.g. Camry LE, Camry SE, etc. are based on the Camry platform but

target different customer segments). If a firm’s portfolio includes only derivative

projects then it may have good short-term returns but also may not be able to

compete when the market moves to a new technology.

Show Figure 7.6

1. For example, pharmaceutical firms can suddenly find a devastating gap in

its project portfolio because they have become increasingly reliant on a new

blockbuster drugs and because projects typically have high failure rates,

long development cycles, and rely on patent protection that will expire.

e. Q-Sort is used to rank projects on a variety of dimensions. Individuals are given a stack of

cards (on each card is a development project) they put in order according to their assessment

of how well each project performs on the criteria presented (e.g. technical feasibility, market

impact, fit with strategic intent). These rankings are then used to structure a debate about the

projects.

V. Combining Quantitative and Qualitative Information

a. Conjoint and data envelopment analyses combine quantitative and qualitative

project assessments by translating qualitative assessments into quantitative measures so

that projects evaluated in different ways can be fairly compared.

i. Conjoint Analysis is a family of techniques (e.g. Discrete Choice, Modeling,

Hierarchical Choice, Tradeoff Matrices, Pairwise Comparisons) enabling the

relative importance of product attributes to be derived statistically. The text uses the

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selection of camera attributes as an example of how multiple regression can be

used to identify the weights implicitly assigned by customers to individual criteria.

In the theory in action section Marriott’s experience in developing the Courtyard

concept is investigated.

1. Marriott used conjoint analysis to determine which features customers

would want most in a moderately priced hotel (the segment of the industry

with continued high growth). Marriott first ran focus groups to identify

customer segments and the hotel attributes they valued. Then in an exercise

similar to a Q sort hotel customers were given a fictional $35 with which to

build their own hotel and a set of cards representing the major hotel

attributes. The tradeoffs customers made in the process of building their

hotel enabled managers to develop “hotel profiles” that participants were

then asked to rate. The managers could then use regression to assess how

different levels of service within a specific attribute influenced customer

ratings of the hotel overall.

Show Figure 7.7

ii. Data Envelopment Analysis (DEA) facilitates the comparison of projects using

multiple criteria and different kinds of measurement units (e.g. dollars, rankings,

Likert measures from a survey). DEA uses linear programming to create a

hypothetical “efficiency frontier” that represents the best performance on each

measure. Each project is then assigned an efficiency value based on the projects

distance from the efficiency frontier.

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1. For example, the Advanced Technologies Group of Bell Laboratories chose

to evaluate projects in terms of three measures: discounted cash flows, the

investment required, and desirability from the perspective of intellectual

property and product market benefits. For the latter two measures, projects

were given a score of 1, 1.5, or 2.25 based on the group’s model for

intellectual property and product market benefits.

Show Figure 7.8

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