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Apollo Systems Quantitative Analysis

By:   •  September 26, 2018  •  Case Study  •  1,283 Words (6 Pages)  •  30 Views

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Quantitative Analysis Exercise

Apollo Systems

Apollo Systems (AS), a technology services solution provider, is considering the profit impact of its new software product tentatively called SysView.  SysView is a hardware systems management tool that will allow IT managers to remotely gather and monitor vital information about networked hardware devices without having to physically touch each one; it includes a license compliance solution that is several state government and regulatory bodies have recently mandated for organizations of certain scale (e.g., > 1,000 employees).  LAN-Watcher, the only other product ready for the marketplace, has experienced several problems in preliminary market tests.  It seems that LAN-Watcher sometimes interferes with the performance of the hardware it manages; additionally, several beta-testers have complained about possible security threats associated with LAN-Watcher’s bi-directional communication protocol.  SysView uses a patented communication scheme of unidirectional encrypted packets sent over the Internet to avoid both performance interference and security problems.  AS has already spent $375,000 to develop SysView.

Jay Lopez, Senior Business Development Manager at AS, predicts that the fixed costs associated with the SysView product will be $85,000 per year.  Additionally, Mr. Lopez knows that the variable unit cost of SysView is $22.  After consulting with the field sales force, Mr. Lopez plans to recommend a wholesale selling price of $119 to AS’s retail distributors.  These retailers, in turn, plan to offer SysView at a price of $199 in the retail business products marketplace.  LAN-Watcher has a wholesale price of $79 and a retail price of $159.  A recent market research survey suggests that the total market for all hardware systems management products is likely to be 4,000 units in the upcoming year.

  1. Channel Margins
  1. What is AS’s margin (“unit contribution”) on SysView?
  2. What is the retailer’s percentage margin on SysView?  
  3. Strictly considering financial incentives (i.e., “all else equal”), would the retail network be more interested in selling SysView or LAN-Watcher to IT managers?  Why?  (Please limit your explanation to at most 3 sentences.)

  1. Break-even volumes
  1. Using only the fixed cost, variable cost, and price data provided above, what is the break-even volume for SysView in the first year?
  2. Now suppose that Mr. Lopez is instructed that SysView’s development costs are to be treated as fixed costs for the purpose of determining product profitability. Now what is the break-even volume for SysView in the first year?  
  3. If AS Management requires that all products at least break even in the first year of sales, do you recommend that Mr. Lopez proceed with this product?  Why/why not?  (Please limit your explanation to at most 3 sentences.)

 

After analyzing likely market acceptance of SysView, Mr. Lopez decides to introduce the product.  With much fanfare and to moderate market acceptance, the new software offering is launch, and initial sales results are in. After reviewing the sales performance of SysView and that of LAN-Watcher, Mr. Lopez decides to conduct some basic market research in order to assess the impact of advertising expenditures on sales of SysView.  He contracts with D.C. Nelson, a leading discount market research agency, to conduct a controlled test market campaign in the Western region of the United States.

Mr. Lopez instructs D.C. Nelson to conduct a 76 week test market involving a panel of businesses drawn from the Western United States.  The panel is exposed to a base level of advertising in the first 52 weeks.  For the last 24 weeks, the panel receives twice the level of advertising as before.  The dependent variable is obtained by aggregating SysView unit sales over all businesses in the panel that purchase SysView each week.  Two independent variables are SysView’s price and the price of the chief competitor, LAN-Watcher.  Additionally, a dummy variable labeled “DUM” is created; DUM takes the value 0 for the first 52 weeks and 1 for the last 24 weeks.  Thus, the variable DUM can be considered a PRE/POST variable, i.e., a variable that measures change in the last 24 weeks (when advertising expenditure was doubled) relative to the first 52 weeks.

D.C. Nelson conducts the advertising experiment in accord with Mr. Lopez’s wishes, collects the data, and analyzes it using ordinary least squares regression techniques.  The specific data it collects are these:

  • Week—week number, ranging from 1 to 76
  • Sales—SysView unit sales in the panel
  • SVPrice—SysView’s price to businesses in the panel
  • LWPrice—LAN-Watcher’s price to businesses in the panel
  • DUM—dummy variable equal to 0 in weeks 1-52 and equal to 1 in weeks 52-76

Using this weekly date, D.C. Nelson estimates the following regression model.

Salesw = a + b*SVPricew, + c*LWPricew + d*DUMw + error

The firm employed ordinary least squares to estimate the unknown parameters a, b, c, and d.  Unfortunately, due to the discount nature of the research agency, D.C. Nelson fails to provide any interpretation of its findings.  Instead, the results are given to Mr. Lopez; he, in turn, forwards them to you.  The summary regression results are provided below[1].

SUMMARY OUTPUT

Regression Statistics

Multiple R

0.9466

R Square

0.8961

Adjusted R Square

0.8918

Standard Error

118.8051

Observations

76

ANOVA

 

df

SS

MS

F

Significance F

Regression

3

8764580.5897

2921526.8632

206.9855

0.0000

Residual

72

1016254.2918

14114.6429

Total

75

9780834.8816

 

 

 

 

Coefficients

Standard Error

t Stat

P-value

Lower 95%

Upper 95%

Intercept

3961.0630

405.8077

9.7609

0.0000

3152.1007

4770.0253

SVPrice

-3.9158

1.3959

-2.8053

0.0065

-6.6984

-1.1332

LWPrice

3.6098

2.0759

1.7389

0.0863

-0.5284

7.7480

DUM

778.2245

36.2773

21.4521

0.0000

705.9071

850.5420

...

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