STRATEGIC MARKETING PLANFOR

SYCON DESIGN, INC.

Prepared by The Other Team:Eric KwanMarco LoEdmond NgNalin Vanasin

EESOR 483Stanford University, CaliforniaJune 6, 1997

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TABLE OF CONTENTS

EXECUTIVE SUMMARY ...........................................................................................................................2

INTRODUCTION .........................................................................................................................................3

COMPANY BACKGROUND.............................................................................................................................3THE MARKET ...............................................................................................................................................3PRODUCT DESCRIPTION................................................................................................................................4PROBLEM STATEMENT .................................................................................................................................5

PROBLEM FORMULATION .....................................................................................................................6

GENERAL APPROACH...................................................................................................................................6DECISION ANALYSIS FRAMEWORK...............................................................................................................6

Decision Hierarchy..................................................................................................................................6SYCON’s Decisions .................................................................................................................................7Uncertainties .........................................................................................................................................10Value Model...........................................................................................................................................12

CONJOINT ANALYSIS..................................................................................................................................14Goals of Conjoint Analysis ....................................................................................................................14Process of Conjoint Analysis .................................................................................................................15Design and Implementation of Conjoint Analysis..................................................................................15Results of Conjoint Analysis ..................................................................................................................17Simulation Using Conjoint Results ........................................................................................................18

DECISION MODEL.......................................................................................................................................19Assessment of Uncertainties ..................................................................................................................19Probabilistic Model of SYCON’s Decision............................................................................................19Evaluation..............................................................................................................................................20

APPRAISAL ................................................................................................................................................21

SENSITIVITY ANALYSIS ..............................................................................................................................21OTHER INSIGHTS........................................................................................................................................23FUTURE DIRECTIONS..................................................................................................................................23

CONCLUSION ............................................................................................................................................25

RECOMMENDATION....................................................................................................................................25LESSONS LEARNED.....................................................................................................................................25

APPENDICES…………………………………………………………………………………………….. 27

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Executive Summary

SYCON Design Inc. is preparing to launch its Electronic Design Automation (EDA)

product in the semiconductor industry. SYCON apparently has a technologically

superior product. Its employees all have strong technological background; however, they

do not have any experience in marketing. The project team applies various analytical

techniques to study the different aspects of the EDA industry and SYCON’s position in

it. The project team recommends SYCON to take on an aggressive strategy which

consists of:

• competing directly with the major EDA suppliers

• include floorplanning, placement, and routing in the product

• setting the price around $350,000

• promoting aggressively, using personal selling, direct marketing, and

advertising

• distributing via both internal direct sales force and outside distributors.

Our present analysis indicates that this product launch strategy will generate the highest

value for SYCON (expected NPV is $56.7 million). For further analysis, we would

suggest SYCON to generate new alternatives such as selling the company before it goes

public.

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Introduction

Company Background

SYCON Design Inc. is a start-up company in the physical design segment of the

Electronic Design Automation (EDA) industry, which generally encompasses software

tools that aid the design of custom (microprocessor) and ASIC chips. Founded in 1996,

SYCON has specialized in servicing the full-custom physical IC design market.

Currently, few chip designers believe that it is possible for automatic tools to achieve the

same or better chip densities than can be achieved manually. SYCON believes that their

break-through products will enable customers to improve the performance and maximize

the density of a chip, given any set of design rules or process technology, and to deliver

these results weeks or months ahead of how long it would currently take using any other

existing IC layout system , manual or automatic. With prototypes in hand, the company

has been able to get the first round of funding worth $3 million, but given their limited

human resources, SYCON is only currently involved in “beta-sites” activities with Intel

and AMD.

The Market

The Electronic Design Automation industry can be decomposed into the “front end” and

the “back end” market. The “front end” market consists of products that focus on the

primary concept, creation, and verification of a circuit function and performance. The

“back end” or physical design market consists of EDA solutions for translating the circuit

concepts into a physical implementation and verifying the results. As mentioned above,

SYCON’s product serves the “back end” market.

There are two levels of physical design of integrated circuits. One is the transistor level,

and the other is the circuit/block level. Each of these levels consists of three major

activities: floorplanning, placement, and routing of circuits. As mentioned above, the

most complicated parts of these activities are currently done manually, but there exist

companies that offer software that aid these activities. The major companies include

Cadence, Avanti , and SVR, who dominate (80%) of the market that is worth

4

approximately $100 million. Appendix A contains a matrix representing the current

physical design segment of the EDA industry. As one can see, the software currently

offered by the big-six EDA suppliers only perform basic design functions for the block

level. As for the transistor level, the market (henceforth the niche market) is more

compact and occupied by small, specialized companies.

We utilize the Porter’s Five Forces framework in order to gain an initial understanding of

the physical design segment of the EDA industry. Appendix B contains the diagram and

explanation of the Porter model. As mentioned earlier, this particular segment of the

EDA industry already has a lot of companies. Established players, such as Cadence and

Avanti, concentrate on producing the higher profit margin productthe datapath design

software. There are a few small players spending much of their effort in the niche

market. As one can see from the Porter diagram, a company cannot expect to make much

if they enter this market with a product similar to existing software in the market. There

is a high buyer concentration in this industry. However, because of the high value added

provided by these tools, buyers are usually willing to pay a high price for them.

In the SYCON vs. Competition Matrix (Appendix A), one can see that the existing

datapath design software does not contain many features that chip designers would like

them to have. If SYCON can make all the features in its software to work, it could

conceivably take a large portion of this market.

Product Description

SYCON currently has two prototypes:

1. Tempest-DP: a datapath(circuit)-oriented placement and routing product. Some of

the features include:

• Datapath analysis

• Standard Cell Placement

• Optimized Datapath placement

• Manual Floorplanning

• Automatic Floorplanning

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• Final Routing

2. Tempest-Lib: an individual-cell or library-element generating tool. Some of the

features include

• Transistor Level Placement and Routing

• Cell Level Process Migration

• Standard Cell Layout Synthesis

The specific features of each of the above prototypes are listed in the SYCON vs.

Competition Matrix in Appendix A.

Problem Statement

The goal of this study is to develop a strategic marketing plan necessary for the company

to break the strong hold of the market by the big three EDA suppliers mentioned above as

well as maximize its profitability. Specifically, the marketing plan will encompass an

optimal scheme for the 4 P’s namely product pricing, product attributes, distribution

methods and advertising and promotion that would maximize SYCON’s profitability.

This marketing plan must align with SYCON’s corporate mission, which is to retain

ownership until they go public. We worked closely with SYCON to ensure that our

analysis and approach addressed the needs of SYCON and reflect their judgment on key

issues to the fullest extent possible.

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Problem Formulation

General Approach

The approach we employ to formulate SYCON’s strategic problem is based on a decision

analysis framework. Specifically, we bound the scope of SYCON’s decision problem by

formulating a decision hierarchy. Then we establish the decision basis by identifying the

relevant decisions and major uncertainties that SYCON faces, and devising a value model

which enables us to quantify and measure the different levels of desirability of the

possible prospects. Using this decision basis, we build a probabilistic decision model

(i.e., a decision tree) to evaluate SYCON’s problem in order to identify the best course of

action.

It should be mentioned that we used conjoint analysis and ACA simulation extensively to

complement the decision analysis framework. The role of conjoint analysis is to gain

quantitative insights on customers’ preferences. The results are utilized in two ways.

First, it aids SYCON in formulating an appropriate product and pricing strategy for the

Aggressive strategy. (See discussion of strategy themes below.) Second, it allows us to

perform simulation to determine the impact on SYCON’s market share under various

competitive market scenarios. The market share is incorporated into the value model to

determine the NPV of the associated outcomes.

Decision Analysis Framework

Decision HierarchyBefore we can establish the aforementioned decision basis, we first define the scope of

our analysis. Due to the large number of issues that SYCON needs to consider, we have

to limit our scope so as to make meaningful analysis feasible. A decision hierarchy, as

depicted in Figure 1, is a suitable tool for this purpose. In the policy region occupies a

decision that we take as a given, which is the company’s goal to maintain its ownership

until it goes public. Therefore, selling the company to a bigger player in the industry is

out of the question. In order to identify strategic decisions, we use the 4-P marketing

framework, which identify the major marketing issues to be Product, Price, Promotion,

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and Place (distribution). In other words, the strategic decisions that we need to analyze

are the features to include in the product; pricing schemes; distribution of the products;

and promotion techniques. Finally, decisions in the tactics region, which concern human

resource and financing schemes, are operations level decisions that we will not analyze in

this project.

•Retain Ownership Until IPO

Policy

Strategies

Tactics

•Determine the Best Marketing Mix (4 P’s)

•Design the Organizational Structure•Devise the Financing Scheme

Given our defined scope, we can now establish the decision basis, each of which is

discussed below.

SYCON’s Decisions

From the decision hierarchy, we have identified the 4 P’s as our strategic decisions.

Table 1 summarizes the alternatives within each of these four areas.

Product Price Place Promotion

Floorplanning $150,000 Direct Sales AdvertisingPlacement $200,000 Distributor Personal Selling

Library $300,000 Public RelationsRouting $350,000 Direct Marketing

Table 1. SYCON’s Marketing Mix

• Product

Figure 1. Decision Hierarchy

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Due to the high degree of market segmentation even within the physical design portion of

the EDA industry, SYCON has many alternatives regarding its product. The company

can market just the library, floorplanning, placement, or routing, or any combination of

these.

• Price

The price that SYCON can charge actually depends on the type of product it launches.

Furthermore, it is important to realize that since SYCON’s are industry (as opposed to

consumer) products, the actual price will be negotiable with each customer. In planning a

pricing strategy, therefore, we only need to come up with a benchmark from which the

negotiation will start. And this benchmark is determined, to a large extent, by the product

and the market segment SYCON decides to target.

• Place

Due to the specialized nature of the industry, the channels of distribution available for

SYCON only include direct sales and distributor. Currently, both channels are common

in the industry. Direct sales may be slightly more effective because the company can

better explain its products to potential customers, but this channel requires a large selling

team and thus higher costs. Distributor, on the other hand, may take longer to sell but

this method saves the product owner significant costs, while at the same time covering a

large geographical customer base.

• Promotion

Above we have described the promotion types in terms of concepts rather than specific

media. Advertising, such as on-line advertising, is an impersonal promotion scheme that

has the advantage of being pervasive at a moderate cost. Public relations, such as trade

shows and news stories, is directed at a smaller group of customers and has the advantage

of seeming more credible than normal advertising. Finally, personal selling and direct

sales are aggressive strategies that are more personal and customized, obligating the

potential customer to pay attention.

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Strategy Themes

Due to the prohibitively large number of combinations of the above decision alternatives,

we will only consider a small subset of these combinations. In forming this subset, we

choose three distinct ‘themes’, each of which is defined by an alternative for each of the

four P’s. The goal is to simplify the problem so that it will be feasible to analyze, while

at the same time considering as exhaustively as possible all of the major distinct

strategies. The three marketing strategies are listed in table 2.

MarketingStrategy

Product Price Distribution Promotion

Aggressive Floorplanning,Placement and

Routing

$350,000 Direct andDistributor

Everything

Niche Player Library $150,000 Direct Sales Direct Marketingand Personal Selling

Low-end Floorplanning $150,000 Distributor AdvertisingTable 2. Strategy Table.

• Aggressive

This strategy is suitably named because it aims at capturing almost the entire range of

market segments. Since the product for this strategy covers all of the major activities in

the circuit level design, the price has be as high as $500,000. In order to sell this product,

however, the company will have to directly compete with the big, established companies

such as Cadence and Avanti. Therefore, SYCON will have to devote massive resources

to distribute and promote the products. Hence, the distribution consists of both direct

sales and distributors (initially equally divided between these two), and promotion must

consists of all types at a large scale.

Since Aggressive is a very risky strategy, involving fierce competition and big

investments, we try to minimize the risk using conjoint analysis to determine more

precisely what attributes interest potential customers most (see discussion of conjoint

analysis below). However, though the risk is great, if SYCON succeeds with this

strategy, this strategy will generate the most income.

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• Niche Player

From our conversations with industry experts, this seems to be a moderate strategy in

terms of profit, but the associated risk is also moderate. The library will consist of all

features currently in the Tempest-Lib. The price of this product is around $150,000.

Since the target customer base is quite small, the appropriate distribution channel seems

to be direct sales. In the same spirit, it is feasible to use the more personal direct

marketing that is effective yet at a moderate cost appropriate for the moderate revenue.

• Floorplanning (Low-End)

According to industry experts, there is high demand for automatic floorplanner because

none of the companies in the industry offers this feature. SYCON has succeeded in

devising a top-down floorplanner that can predict the capacity of the final chip, thus

cutting down significant amount of design time. So although the value of the market for

a floorplanner is relatively small, we have confidence that if SYCON were to focus in

this segment, it has the potential to capture most of the market, making this alternative

very attractive. The price that SYCON can charge for this product would be around

$150,000. Due to the relatively mass market nature of this segment, advertising would be

an appropriate promotion scheme. Further, because the profit margin for this product is

relatively low, it is not worth it to hire a large and expensive sales force but better to use

distributors.

Uncertainties

Along with the sponsor and industry experts, we have identified three most significant

uncertainties that may affect SYCON’s situation. Their relationships with SYCON’s

decision situation are depicted in the decision diagram in Figure 2.

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Revenue

Cost

Value

SemiConductor's

Economy

Competitor(Technology)

Market Share

Competitor(Price

Cutting)

MarketDemand

Sycon'sStrategy

Growth in Semiconductor Industry

Due to the direct dependence of designing activities on the growth of the semiconductor

industry in general, this uncertainty directly affects the sales of SYCON’s product.

Although our modeling horizon is five years (see discussion on horizon length below in

the value model), we assume the growth in the semiconductor industry to be constant

over our modeling horizon on advice of the industry experts.

Competitors’ Technological Breakthrough

As with any other segments in the semiconductor industry, it is important for an EDA

player to be a technological leader. If a competitor such as Cadence is able to catch up

with SYCON’s technology, the company’s sales can be greatly affected. This uncertainty

is a function of both the competitors’ ongoing R&D efforts and their possible reaction to

SYCON’s product launch. Therefore, we define this uncertainty to be the breakthrough

in the technology that SYCON chooses to launch. As a result, this uncertainty will be

influenced by SYCON’s strategy. For example, since in the niche market the

competition is not as fierce as in placement and routing, if SYCON chooses to target the

Figure 2. Decision Diagram

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former this uncertainty will probably not be as much of a threat as if the company

chooses the bigger market.

Competitive Price Cutting

Price cutting is a common strategy that companies use to drive out competition. Because

only the big companies can afford to do pursue this strategy, this uncertainty can have

profound impact on SYCON. Similar to competitors’ technological breakthrough, price

cutting that is aimed at weakening SYCON will depend on who the company’s

competitors are and how threatened they feel. Therefore, this uncertainty will be

influenced by SYCON’s strategy.

Value Model

We use net present value as the value measure for SYCON’s prospects. In order to

calculate the NPV for each prospect, we consider the following elements:.

Five Years Modeling Horizon

Given the present pace of technological advancement, it is very hard for us to build a

long term model. Both our research and industry experts indicate that it is very unlikely

that there will be a major breakthrough in the format of EDA tools in the next five years.

Thus, we conclude that 5 years will be an ideal modeling horizon.

Revenue

For each of the 3 marketing strategies, the yearly revenue is calculated using the

equation:

Revenue = Price * Market Share * Market Size. The price used is as defined in the

strategy table. The market share is obtained from our conjoint analysis and simulation

(see discussion of these analyses below). The market size is initially obtained from

Dataquest and then modified by an industry expert and SYCON's key executives. To

determine the present value of the revenues over the five-year horizon, we use the growth

rate of the market size and the yearly changes in the market share. The former is

provided by industry experts, while the latter derives from the scenario from which the

market share is calculated in the ACA simulation.

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Cost

Much of the cost-related data are obtained from SYCON. As SYCON is presently very

small, it is very hard for its executive the future cost of running the company as it gets

larger. For example, in building this model, SYCON assume that they will continue to

rent office space when it may be more economical for SYCON to purchase an office.

Much of these data are conservative estimate; thus, the reality can only be better than our

forecast.

A sample value model can be found in Appendix C.

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Analysis

Conjoint Analysis

Goals of Conjoint Analysis

Given the large number of potential features that can be incorporated into its product,

SYCON is extremely interested in determining the attractiveness of each of these features

to the customers. Specifically, SYCON would like to know how the inclusion or

exclusion of a feature would affect the customers’ preference for its product. In addition,

another objective for SYCON is to assess the sensitivity of the customers’ preference to

various pricing schemes in order to devise an appropriate pricing strategy.

Conjoint analysis addresses the aforementioned objectives in a quantitative manner. It is

a mathematical technique that can be applied in the field of market research to fathom

consumer preference and assess the effects of specific product features on the aggregate

preference for the product. Instead of simply conducting a “brute force” market survey

that strives to gather information from the customers about all the possible combinations

of features that can be incorporated into a product, conjoint analysis reduces the number

of possible combinations by including only a selected subset of product concepts for

evaluation. This reduction is mathematically based on the extensive use of highly

fractionated factorial designs.

As an offshoot from the results of conjoint analysis, a simulation of the competitive

market can be performed. Using the preferences of the consumers, a simulated market

composed of products with different combinations of features can yield the market share

for each product. Since the EDA industry is rather compact and the features and prices of

the competing products are fairly well-known, a simulation of this kind is especially

useful in providing SYCON with a reasonable estimate of its potential market share.

15

Process of Conjoint AnalysisThe process of conjoint analysis is carried out through the use of the ACA System

(Version 4.0), a software package designed by Sawtooth Software. Among the many

capabilities of the software, we targeted our efforts to utilize the program in the following

areas:

• designing and testing the conjoint questionnaires

• collecting actual respondent data

• determining the set of product features that would provide the customer’s with the

highest utility, i.e., strongest preference for the product

• performing simulation based on the conjoint data to obtain the likelihood of purchase

and market share of SYCON’s product given SYCON’s launch strategy and its

associated outcome.

Design and Implementation of Conjoint Analysis

In building the conjoint questionnaire, we worked closely with SYCON to construct a list

of attributes that is appropriate for our analysis. Since one of the objectives is to forecast

SYCON’s product market share, it is necessary to include all the attributes that are

important to the purchase decision. However, the set of all possible features includes 14

attributes and hence exceeds the limit of 10 attributes on the ACA software. Therefore,

we identified coherent groups among the attributes in order to decrease the number of

attributes. For example, instead of allowing “Standard Cell Placement”, “Optimized Data

Path Placement”, and “Control Logic Integration” to be three independent attributes, we

grouped them together under the new attribute of “Placement and Routing” whose levels

consist of the various combinations of the three underlying attributes.

Along with the construction of an appropriate list of attributes, another important

dimension in designing the conjoint questionnaire is the specification of the questionnaire

parameters which govern the format of the six types of questions that could be included

in an ACA survey. Below is a summary of each type of question:

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1) Unacceptables. The are questions aim to determine if there is a level within each

attribute which the respondent would not accept under any circumstances. We

included this Unacceptables section in our design in order to eliminate irrelevant

attribute levels so that the ensuing questionnaire would be more logical to the

respondent. In addition, regarding SYCON’s product, some attributes may have a

large number of levels because of the formation of new attribute through the grouping

of original features as mentioned previously and the large number of resulting

combinations of features that make up the levels. Therefore, the inclusion of

Unacceptables also helps to narrow down those attributes with many levels.

2) Preference Rankings. In this section, the questions are designed to find out the

respondent’s preference ranking for each of the levels of all the attributes. This type

of questions is mandatory in the ACA program.

3) Most Likelies. For each attribute, this type of question serves to determine which of

the associated levels the respondent is most likely to have in the product if he/she

does indeed purchase it. Even though the Most Likelies section is optional in the

questionnaire design, we decided to retain it in order to reduce the number of levels

so that only the most relevant and realistic ones remain for the rest of the interview.

This aids in maintaining the respondent’s interest in the interviewing as well as

shortening the length of the interview.

4) Importance Ratings. These questions explore the relative importance of the

attributes. The objective is to determine the importance of a specific attribute in the

desirability of a product. For each attribute, the respondent is asked to decide how

important it is for them when considering two products which are almost identical

except that one has the least favorite level of the attribute while the other has the most

favorite, as defined in the Preference Rankings section. The Importance Ratings are

mandatory in ACA.

5) Paired-Comparison Trade-Offs. This section consists of a series of questions which

ask the respondent to indicate a preference between two product concepts which are

almost identical except for two attributes. The pairings are chosen by ACA so that

the respondent is also indifferent between the two alternatives. Each pair of concept

is selected according to the previous answers of the respondent. The purpose of the

17

questions is to refine the respondent’s utility estimates by generating increasingly

equivalent pairs of product concepts. Paired-Comparison Trade-Offs are mandatory

in ACA.

6) Calibration Concepts. This section consists of questions that ask the respondent to

evaluate the different product concepts. Responses from this section are used to

calibrate respondent utilities and to detect inconsistency in the respondent’s answers.

Calibration Concepts are mandatory in ACA

After setting up the questionnaires, we interviewed 13 EDA industry experts using the

ACA software. The responses were merged into one file and the results can be found in

the following section.

Results of Conjoint Analysis

• Optimal Product Concept. The utility results of our conjoint analysis indicate that the

optimal product design (if SYCON pursues the Aggressive strategy) will include all

the possible features in Tempest-DP. See Appendix D for detailed utility data.

• Likelihood of Purchase. The optimal pricing scheme for the Aggressive strategy is

around $350,000. According to the graph for purchase probability below, the

likelihood of purchase drops dramatically as the price increases from $350,000 to

$450,000. The graphs assumes that SYCON is launching the optimal product

concept as stated above.

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Probability of Purchase vs. Price

64

66

68

70

72

74

76

78

0 100 200 300 400 500 600 700 800

Price ($K)

Pro

babi

lity

of P

urch

ase

(in %

)

Figure 3. Probability of Purchase for SYCON’s Optimal Product

Simulation Using Conjoint Results

Using the results from conjoint analysis, we simulated the competitive environment under

different scenarios. Each scenario is defined by the marketing strategy and the outcome

of the ensuing uncertainties. In terms of the simulation, these translate into changes in

the type and number of features as well as the price for SYCON’s and its competitors’

products. The results of the simulation are the market share for each of the products in

the market. In our simulation, we included four products which represented SYCON,

Cadence, SVR and Avanti. For example, in the “base case”, SYCON is pursuing the

Aggressive strategy with its optimal product concept while it is assumed there is no

technological breakthroughs or competitive price-cutting. The products of Cadence, SVR

and Avanti consist of features as indicated in the SYCON vs. Competition Matrix in

Appendix A. Choosing the “Share of Preference with Correction” simulation model in

ACA, we can obtain the following market shares:

SIMULATION RESULTS

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==================

(Respondents Included = 13)

Share of Standard Product Preference Error -------------------------------- ------------ ---------------

1 SYCON 95.37 3.08

2 Cadence 1.53 2.71

3 Avanti 1.53 2.71

4 SVR 1.53 2.71

Note that the share of preference represents the market share for each company’s product.

In addition, the low standard errors indicate that the results are statistically reliable.

Using the same procedure, the market shares for all possible scenarios in our decision

model are determined. The results, in conjunction with the market size forecast, are

incorporated into the value model to generate revenue estimates.

Decision Model

Assessment of UncertaintiesIn a decision model, the distributions of uncertainties should reflect the decision-maker’s

beliefs. However, since our sponsor consists of former end-users (from Intel and IBM)

rather than experienced suppliers, we turn to our industry experts for additional

information that would complement the sponsor’s fragmented beliefs whenever the

sponsor seems unsure about any aspect of the uncertainties. Combining the two sources

of information we identified three possibilities for each uncertainty and assessed the

associated probabilities. These values can be found in Appendix E.

Probabilistic Model of SYCON’s DecisionGiven the probabilities assessed for each of the uncertainties, we are able to construct a

decision tree to evaluate SYCON’s marketing strategy. The tree consists of 27 end

branches for each of the 3 marketing strategies defined earlier. Hence, the entire tree

structure is made up of 81 end branches. A generic version of this decision tree is

included in Appendix F.

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EvaluationSince the decision tree mentioned above is composed of a substantial number of

branches, we utilize the DPL decision analysis software to aid the evaluation. The 3

strategies have the following expected NPV’s:

• Aggressive: $56.7 million

• Niche Player: $5.8 million

• Floorplanning (Low-End): $19.6 million

Therefore, the optimal strategy is Aggressive.

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Appraisal

Sensitivity Analysis

To see how robust the Aggressive strategy is, we performed sensitivity analyses on the

uncertainties and risk attitude of SYCON. These are discussed below.

Sensitivity to Growth In Semiconductor Industry

Because the anticipated growth rate for the semiconductor industry is 15%, we perform

analysis on this level of growth. In other words, we vary the probability that the growth

will be 15% while keeping the ratio of the probabilities of the other two possible growth

rates fixed. Figure 1 in Appendix G shows that as the probability of 15% growth rate

increases, the NPV for Aggressive decreases slightly (the range is only about $5 million).

This is due the increasing marginal cost of maintenance. Nevertheless, one can see that

the Aggressive strategy is extremely robust to the 15% growth rate since its NPV

dominates the other strategies for all probabilities.

Sensitivity to Competitors’ Technological Breakthroughs

One of the biggest concerns for SYCON at this moment is how soon its competitors will

achieve the necessary technological breakthrough that will take away SYCON’s

competitive advantage. If competitors can achieve this in two years, SYCON’s position

can be badly damaged. If it happens in three years, SYCON will probably be established

by that time and the damage will probably be minimal. Therefore, we choose to do

sensitivity analysis on the two-year lead time to see how it might affect SYCON. Recall

that we defined breakthrough to be that in the field of each specific strategy. In other

words, the line representing Aggressive in Figure 2 in Appendix G is a function of

probabilities that competitors will catch up with all designing activities. But the line for

floorplanning is a function of the probability that competitors will come out with just an

automatic floorplanner. We simply put all strategies in the same graph for convenience.

Similar to the previous analysis, we vary the probability that the competitors will catch

up within two years while keeping the ratio of the probabilities of the other two

possibilities, which are three years and none, fixed. From Figure 2 in Appendix G, we

22

see that the more likely competitors can catch up with the Aggressive product in two

years, the lower is the NPV of this strategy because its market share will be threatened.

Even though the range of the NPV is quite large (about $20 million), however, the graph

also shows that Aggressive is the optimal strategy for all probabilities as this strategy

always dominates others.

It is worth noticing that if the probability of the 2-year technological breakthrough in

floorplanning exceeds approximately .06, the Floorplanning strategy will yield

increasing NPV. Though this may seem illogical, it is accurate because Floorplanning

has increasing marginal cost. Therefore, it is not optimal to get all the market shares in

the floorplanning market.

Sensitivity to Competitive Price Cutting

Because fierce price cutting would hurt SYCON the most, we do the analysis for this

degree while keeping the other two’s ratio fixed. Again, even though this uncertainty is

influenced by SYCON’s strategy, we have put the three strategies on the same graph in

order to compare them. In this case, NPV of Aggressive is quite insensitive to the

changing probability, and this strategy again always dominate the other alternatives (see

Appendix G, Figure 3).

Sensitivity to Risk Attitude

In the value model we use NPV as the value measure for prospects, thus assuming that

SYCON is risk-neutral. Since it is not always wise assume risk-neutrality, we perform

sensitivity on risk attitude to see whether we should refine this aspect of the model any

further. In the sensitivity analysis, we then try using exponential utility function and vary

the risk tolerance from $1-70 million. It turns out that although the certain equivalent of

Aggressive varies quite a lot (the range is $30-57 million), this strategy is still robust in

terms of being the optimal one (see Appendix G, Figure 4). This confirms that risk-

neutrality is a reasonable assumption and that this issue needs no further investigation.

23

Other Insights

1. Other than sensitivity analysis, we also generated the cumulative distribution of the

NPV for each strategy (see graph in Appendix H). These distributions show that the

Aggressive strategy, other than yielding the highest NPV, also stochastically

dominates the other strategies. In other words, for any given level of NPV,

Aggressive has a higher probability of generating that NPV or more.

2. When generating the Aggressive strategy with SYCON, we initially used a 50-50

distribution method (50% outside distributor and 50% in-house sales force). In our

analysis, however, we varied the distribution ratio and found that there exists other

ratios that may be more cost-effective. The graph in Appendix I shows the costs

associated with each distribution method over the 5-year period, assuming SYCON

can only pursue in one of them. The graph suggests there exists a lower bound on the

distribution costs, achieved by fully utilizing outside distributors for the first three

years and employing in-house sales force for the last two years. This result is

somewhat misleading because we model a learning curve effect such that the sales

and the distributors become more effective over time; thus, without the first three

years experience of selling, the in-house sales force cannot possibly become as

effective as indicated in the graph. Nonetheless, this graph does give an important

insight that there may exist a different distribution ratio other than the present 50-50

method that can be more cost-effective.

3. As mentioned in the sensitivity analysis on competitors’ technological breakthrough,

if for any reason SYCON ever decides to market a floorplanning-only product, the

company should not blindly try to get the highest market share. This is because the

floorplanning market yields small profits relative to the maintenance costs. To pursue

this strategy, therefore, SYCON must find the optimal market share given the current

market size and aim for that share.

Future DirectionsOur analysis has gone through a few decision analysis cycles, but there still exist further

refinements and investigations which could be done given more time. In light of this we

suggest a few possible directions for further study.

24

1. Upon SYCON’s request, we have framed our analysis such that it is the policy of the

company to retain ownership until it becomes a public company, which the goal of

SYCON. From industry research, however, we found that it is the common trend for

start-up companies to merge with the bigger players in the industry. This is because

small companies do not have the financial strength necessary to survive in the

competitive environment of EDA. Moreover, large companies often see the value of

innovative start-ups and are willing to acquire them at huge premiums. Therefore, it

may be more profitable for SYCON to simply merge with, for example, Cadence or

Avanti.

2. In this study, the possible strategies for SYCON are static. In other words, once the

decisions on the 4 P’s are made, they are fixed for the entire modeling period. As the

result on the distribution ratio shows , however, it may be more optimal to vary our

strategies over the 5 years. Therefore, SYCON may wish to consider this issue if

they are to go through additional cycles on decision analysis.

25

Conclusion

RecommendationBased on the results of our study, we recommend that SYCON pursue the Aggressivestrategy, i.e.:

• compete directly with the major EDA suppliers

• include floorplanning, placement, and routing in its product

• set the price around $350,000

• promote aggressively, using personal selling, direct marketing, and

advertising

• distribute via both internal direct sales force and outside distributors.

SYCON can achieve the highest net present value with this strategy, which is about

$56,725,000.

This optimal strategy is a result of our decision frame and assumptions. If SYCON

wishes to do further investigations, we recommend a reconsideration of the corporate

policy of going public. The company may also wish to extend the analysis by using time-

based, as opposed to static, strategies.

Lessons LearnedWhen we first talked to SYCON, they asked us to develop a complete five-year business

plan. So for a while, we struggled with framing an analysis for this goal. Though

obvious in retrospect, it took us some time to realize that the scope of their request was

too broad for us to tackle. Thus, framing was the main difficulty that we experienced but

the lesson learned was most valuable: that an important first step in a study is to narrow

down the scope of the problem in order to make meaningful analysis feasible. We also

learned that the challenge in doing so lies in identifying a balanced focus. In other words,

while we do not want to make the problem too complicated, we also do not want make it

so simple that it drifts too far from reality.

Another lesson that we learned is in the same selectivity spirit as above. For the conjoint

analysis, we initially struggled with many tools (for example the ACA and the CBC

26

software), each with its own benefits and tradeoffs. When it was time to make a choice,

we realized that our indecision stemmed from our failure to prioritize among the benefits

and drawbacks. This realization allowed us to choose the tool that would produce the

most insightful results, ones that best fit the scope of the problem.

Finally, although there are a lot of public information regarding the EDA industry, much

of the specific data can only be obtained from insiders of the industry. During

information-gathering, we encountered many difficulties in contacting and setting up

interviews with the industry experts. Fortunately, these difficulties were all eventually

resolved. Through these experiences, we have also significantly improved our

interpersonal and communication skills.

APPENDIX B-1: PORTER DIAGRAM

APPENDIX G: SENSITIVITY ANALYSIS

Determinants of Substitute Threats• None

Entry Barriers• Access to

Distribution• Expected

Retaliation

IndustryCompetitors

Arcadia, Cadabra,RubiCAD, Cascade,

Gambit,Sagantec

Determinants ofSuppliers Power• None

Determinants of BuyerPower• Buyer Concentration

Versus FirmConcentration

• Buyer Volume• Buyer Switching Costs• Buyer Information• Product Difference• Buyer Profits

Rivalry Determinants• Industry Growth• Product Differences• Switching Cost• Brand Identity• Diversity of

Competitors

$-

$10

$20

$30

$40

$50

$60

$70

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9 1

Probability

NPV

($

mill

ion)

Aggressive

Niche

F loorplanning

-40-30-20-10

010203040506070

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9 1

Probability of B reakthrough

NPV

($

mill

ion) Aggressive

Niche

F loorplanning

Figure 1. Sensitivity Analysis on 15% Economy Growth

Figure 2. Sensitivity Analysis on 2-Year Tech. Breakthrough

$-

$10

$20

$30

$40

$50

$60

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9 1

Probability of F ierce Pricing Cutting

NPV

($

mill

ion)

Aggressive

Niche

F loorplanning

-80

-60

-40

-20

0

20

40

60

1.E

+06

6.E

+07

1.E

+08

2.E

+08

2.E

+08

3.E

+08

3.E

+08

4.E

+08

4.E

+08

5.E

+08

5.E

+08

6.E

+08

6.E

+08

7.E

+08

7.E

+08

Risk Tolerance

NP

V (

$ m

illio

n) Aggressive

Niche

Floorplanning

Figure 3. Sensitivity Analysis on Fierce Price Cutting

Figure 5. Sensitivity Analysis on Risk Tolerance

APPENDIX D: UTILITY RESULTS FROM CONJOINT ANALYSIS

AVERAGE UTILITY VALUES

Average Utility Data Flow Analysis 33

No Data Flow Analysis 9

Placement and CompilersStandard Cell Placement 24Optimized Datapath Placement 19Control Logic Integration 24Standard Cell Placement + Optimized Datapath Placement 35Standard Cell Placement + Control Logic Integration 25Optimized Datapath Placement + Control Logic Integration 33All Available Placement and Compilers Features 53No Placement and Compilers 19

Floor PlanningManual Floor Planning 4Automatic Floor Planning 15Manual Floor Planning + Automatic Floor Planning 28No Manual Floor Planning / No Automatic Floor Planning 5

Routing 1Complete Control Over Final Placement and Routing Results 53No Complete Control Over Final Placement and Routing Results 1

Routing 2Cell Level Density Optimization- Diffusion and Power Bus Sharing 45No Cell Level Density Optimization 5

Routing 3Optimized Bus Routing and Control Signal Routing 28No Optimized Bus Routing and Control Signal Routing 3

Routing 4Clean-Up Routing 9Chip Top Level Routing 20Clean-Up Routing + Chip Top Level Routing 37No Clean-Up Routing No Chip Top Level Routing 2

Routing 5Hierarchical Placement and Routing 97No Hierarchical Placement and Routing 2

Routing 6Chip and Block Level Routing Acceleration 48No Chip and Block Level Routing Acceleration 8

• Note: The bold figures represent the level with the highest utility in each attribute group.

APPENDIX I: DISTRIBUTION CHANNEL

$-

$5.00

$10.00

$15.00

$20.00

$25.00

$30.00

$35.00

$40.00

1 2 3 4 5

Year

Cos

t

Sales

Distributors

APPRENDIX B-2: Porter's Five Forces Analysis

SYCON’S Five year Distribution Channel Plan

To identify the key elements affecting the success of Sycon, the project group firstconduct a Porter's Five Forces analysis. EDA companies do not need suppliers and thereare not any substitute products.

Barrier to Entry• Access to distribution. There are two ways to distribute the EDA products,

i.e. distributors or direct sales force. Direct sales force, since they know theproducts much better than the distributors, is more efficient. Establishedplayers in the EDA industry, such as Cadence and Avant!, have a large salesforce. Small and new players will lack the manpower to compete head onwith the larger players.

• Expected Retaliation. A common tactic that the big players use to fend offcompetition is price-cutting. There are commonly three forms of price-cutting. They can do a straight out price cut, provide new features for free andlower the maintenance cost.

Rivalry Determinants• Industry growth. The EDA is growing at moderate pace. The present players

can easily satisfy this growth.• Product differences. Most of the products are very similar. The large players

all concentrate on high profit margin product. There are a few small playersthat concentrate on areas generally neglected by the large players.

• Switching cost. Chip makers usually have to do a lot of fine-tuning toincorporate the newly added EDA tools into their own design system. Thisfine-tuning process may take up to months; thus, the chip makers often havelow incentive to switch from product to product.

• Brand Identity. There are already some well-developed players in the hi-endEDA industry. Established players usually have a good after sales support.New startups like Sycon will have a hard time catching up with the establishedplayers in this respect.

• Diversity of Competitors. The EDA industry is highly competitive. There aremany players with the top two players taking up 80% of the market share.

Bargaining power of buyersBargaining Leverage

• Buyer Concentration Versus Firm Concentration. The concentrations in this caseare very even.

• Buyer Volume. The volume varies with the total number of chip designingprojects going on. In general, the volume will not be too high.

• Buyer switching costs. Switching costs are relatively low as compare to the profitof buyers.

• Buyer information. The buyers usually can get information regarding the priceand the features of products easily.Price Sensitivity

• Product Differences. The competing products in the EDA industry are all similar.• Buyer profit. These companies generally high profit margin.

Sycon has developed a breakthrough algorithm that makes its product outperform that ofits competitors. It can also perform tasks that was previously impossible. Sycon also hasgood connections with Intel and AMD. If Sycon can successfully launch its products tothese two major chip makers, Sycon can distinguish itself from its competitors. Aftercreating a brand identity, distribution of the products would be easy. One disadvantagethat Sycon has is its size. Buyers may be concerned with the financial viability of thecompany since after sales support is important. Fortunately, Sycon has a strong financialbacking from its venture capitalist. Ideally, Sycon will not want to receive further outsidefinancial aid and give away more shares of the company. Sycon may still use its financialbacking to create credibility.

APPENDIX A: COMPETITIVE MATRIX

APPENDIX H: CUMULATIVE DISTRIBUTION OF EXPECTED NET PRESENT VALUE

Aggressive

Niche

Floor Planning

0 50 100

NPV ($ million)

150-50

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0.4

APPENDIX J: NET PRESENT VALUE ASSOCIATED WITH DIFFERENTMARKETING STRATEGY

Key Uncertainties NPV associated with different Market ing StrategyTechnol ogi cal Breakt hrough

Sem iconduct or Indust ry G row th

Com petitive Pri ce Cutting

Aggressi ve Niche Fl oorpl anni ng

2 YEAR HIG H FIERCE 35,450,746.72$ 3, 258,010.20$ 30, 923,390.26$ 2 YEAR HIG H M O DERATE 42,851,029.20$ 3, 824,337.64$ 30, 491,603.05$ 2 YEAR HIG H NO NE 38,269,378.54$ 8, 569,652.63$ 26, 634,969.13$ 2 YEAR M O DERATE FIERCE 30,542,167.97$ 2, 960,587.65$ 33, 337,101.45$ 2 YEAR M O DERATE M O DERATE 37,037,133.64$ 3, 477,344.66$ 33, 591,170.22$ 2 YEAR M O DERATE NO NE 33,076,018.68$ 7, 677,384.96$ 30, 152,836.93$ 2 YEAR LO W FIERCE 24,433,079.31$ 2, 592,864.16$ 36, 330,342.21$ 2 YEAR LO W M O DERATE 29,801,689.67$ 3, 048,333.92$ 37, 434,583.37$ 2 YEAR LO W NO NE 26,477,797.72$ 6, 574,214.49$ 34, 518,595.24$ 3 YEAR HIG H FIERCE 39,476,713.35$ 3, 635,122.97$ 18, 156,554.97$ 3 YEAR HIG H M O DERATE 46,414,188.43$ 4, 150,068.08$ 17, 392,177.14$ 3 YEAR HIG H NO NE 42,481,585.87$ 9, 152,326.70$ 13, 532,058.97$ 3 YEAR M O DERATE FIERCE 34,309,236.45$ 3, 253,548.41$ 21, 065,432.51$ 3 YEAR M O DERATE M O DERATE 40,375,930.47$ 3, 721,056.35$ 20, 994,864.81$ 3 YEAR M O DERATE NO NE 36,952,489.12$ 8, 167,341.97$ 17, 566,362.43$ 3 YEAR LO W FIERCE 27,851,006.13$ 2, 784,234.80$ 24, 757,279.97$ 3 YEAR LO W M O DERATE 32,837,466.77$ 3, 193,453.27$ 25, 548,882.96$ 3 YEAR LO W NO NE 30,042,878.71$ 6, 950,590.32$ 22, 659,353.00$ NEVER* HIG H FIERCE 151,599,606.18$ 7, 724,095.46$ ( 59,414,665.75)$ NEVER* HIG H M O DERATE 151,902,487.91$ 8, 658,845.43$ ( 68,238,633.17)$ NEVER* HIG H NO NE 152,726,160.92$ 12, 603,174.26$ ( 65,627,274.71)$ NEVER* M O DERATE FIERCE 132,826,670.07$ 6, 834,310.83$ ( 46,543,756.25)$ NEVER* M O DERATE M O DERATE 132,826,670.07$ 7, 669,919.95$ ( 53,641,336.91)$ NEVER* M O DERATE NO NE 133,552,695.34$ 11, 179,504.81$ ( 51,417,469.58)$ NEVER* LO W FIERCE 108,875,770.82$ 5, 733,979.88$ ( 30,556,794.83)$ NEVER* LO W M O DERATE 109,088,930.14$ 6, 447,014.50$ ( 35,517,395.35)$ NEVER* LO W NO NE 109,689,725.05$ 9, 419,686.46$ ( 33,767,465.41)$

*NEVER means the competitors never make the effort to catch up

APPENDIX E: PROBABILITIES ASSESSMENTSUNCERTAINTIES

Competitive Price Cutting Marketing Strategy Fierce Moderate NoneAggressive 0.7 0.2 0.1

Niche Market 0.3 0.3 0.4Floorplanning 0.1 0.3 0.6

Competitors' Technological Breakthrough Marketing Strategy 2 years 3 years NeverAggressive 0.1 0.7 0.2

Niche Market 0.2 0.1 0.7Floorplanning 0.7 0.2 0.1

Semiconductors Industry Growth Marketing Strategy Good (20%) Moderate (15%) Bad (8%)Aggressive 0.3 0.65 0.05

Niche Market 0.3 0.65 0.05Floorplanning 0.3 0.65 0.05

APPENDIX F: GENERIC TREE

AGGRESSIVE

NICHE

FLOORPLANNING .65 .65 MODERATE (15%)

.65 MODERATE (15%)

GOOD (20%)

BAD (8%)

.30

.05

GOOD (20%)

BAD (8%)

.30

.05

GOOD (20%)

BAD (8%)

.30

.05

TWO YEARS

.7 THREE YEARS

NEVER

TWO YEARS

.7 THREE YEARS

NEVER

TWO YEARS

.2 THREE YEARS

NEVER

FIERCE

.2 MODERATE

NONE

.7

.1

FIERCE

.3 MODERATE

NONE

.3

.4

FIERCE

.3 MODERATE

NONE

.1

.6

.1

.2

.2

.1

.7

.1

.65 MODERATE (15%)

SEMICONDUCTORECONOMY GROWTH

COMPETITORS’TECHNOLOGICALBREAKTHROUGH

COMPETITIVEPRICE CUTTING

APPENDIX C COST MODELGrowth

Year# of licences sold

(15% Growth )15% Growth

Market Share (%)

Revenue

1 311.42 120,000,000.00$ 90.83% 108,996,000.00$ 2 357.62 138,000,000.00$ 90.70% 125,166,000.00$ 3 128.59 158,700,000.00$ 28.36% 45,007,320.00$ 4 121.81 182,505,000.00$ 23.36% 42,633,168.00$ 5 140.08 209,880,750.00$ 23.36% 49,028,143.20$

Year# of employees /

License# of employees (mainteance)

# of employees (Sales)

Salary / employee (maintenance)

Salary / employee (Sales)

Comission Overhead Cost

1 6.00 1868.50 622.83 50,000.00$ 30,000.00$ 21,799,200.00$ 10,276,765.71$ 144,286,$ 2 4.00 1430.47 715.23 54,000.00$ 32,400.00$ 25,033,200.00$ 1,327,817.14$ 126,879,9$ 3 3.00 385.78 160.74 36,000.00$ 34,992.00$ 9,001,464.00$ (2,884,866.34)$ 25,729,$ 4 2.00 243.62 93.70 38,880.00$ 37,791.36$ 8,526,633.60$ (10,320.03)$ 21,629,2$ 5 2.00 280.16 46.69 41,990.40$ 40,814.67$ 9,805,628.64$ 688,221.14$ 24,263,6$

Year ProfitOperating Profit

marginPrice 350,000.00$

1 (35,290,137.14)$ -32% Maintenance (15%) 52,500.00$ % from Dist.2 (1,713,910.86)$ -1% Workstation price 3,500.00$ % from sales3 19,278,120.24$ 43% Variable Cost 2,000.00$ 4 21,003,959.74$ 49% Promotion Cost 100,000.00$ 5 24,764,450.09$ 51% Distributor's Comission 20%

Sales' Comission 10%# of license sold / sales 0.5Risk-free rate 7%

NPV $14,938,786.90