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2002.01 Spring 2002
Senior Design Project for Verizon Wireless Communications
Mohamed Fahim
Senior Design Project for Verizon Wireless Communications - Applying Analytic Hierarchy Process, Two-Way Factor Analysis and Engineering Economy
Methods, to Help Verizon in their Decision Making Process to Choose Their New E-mail Systeni'
By: Mohamed Fahim Professor: Thomas Siems
May 7, 2002
I I Table Of Contents
I I I. Management Summary
I II. Background and Description Of the Problem
I Ill. Analysis of the situation
I IV. Technical Description of the Analytic Hierarchy Model
I V. Technical Description of the Statistical Experiment
I VI. Technical Description of the Engineering Economy Methods
I VII. Conclusions and Critique
I I I I I I I I I
I I
Management Summary
For the past several months, Verizon Communication has been conducting an
analysis of whether to keep their internal Email system or replace it with another. They
can either keep using their current system or chose one of two new system options.
Verizon is highly considering all three systems. Using Verizon's collected data for each
product, I did an experimental analysis to help Verizon choose the best system for their
needs and hence make the best decision.
After looking through given data, I decided to divide the analysis approach into
two parts, qualitative and quantitative studies. The first part, the qualitative study, has
two components. First, I applied the Analytic Hierarchy Model to analyze and compare
the three proposed systems. I realized that comparing the three products in a
mathematical form would enable Verizon to obtain a much clearer picture of each
system's potential both in the present and future. I categorized my results based on the
four judgmental categories that Verizon had determined. I was then able to demonstrate
the best system in each category.
The second component of the qualitative approach was to determine which
product would work the best with Verizon's advanced digital feature, VECTR. VECTR is
an advanced digital email feature that Verizon relies on for their emailing process.
Verizon's judgmental decision will be heavily based on what product can best work with
VECTR. Based on Verizon's twelve-month collected data, I designed a two-factor fixed
effects experiment to study the effects of design factors on a response. The two fixed
I I I I I I I I I I I I I I I II 1
factors are: (A) with and without VECTR and (B) the three Products. The response
represented the number of users complaints.
Next, the quantitative part of the project used applied engineering economy
methods. Engineering economy deals with the concepts and techniques of analysis useful
in evaluating the worth of systems in relation to their cost. I did my analysis based on the
cost values for each product that Verizon had given. Verizon had provided three cost
categories: (1) vendor costs, (2) IT costs, and (3) additional costs. After using various
formulas and methods, I was able to obtain results useful for Verizon' s judgmental
process.
Based on the results in both the qualitative and quantitative parts, I was able to
provide Verizon with valuable information that will be included in the study conclusions.
I
I1 2
I I
Background and Description of the Problem
IRecently, Verizon Communication has been debating whether to keep their
internal Email system or replace it with one of another two system options. The problem
originally started when Verzion's Technical Managers realized that their system is a very
high cost product and yet not performing to their level of satisfaction. After numerous
complains about the system, Verizon decided to look for other systems that could
possibly better meet their level of satisfaction and demand. After studying several other
products, Verizon chose two systems to test. The first of the two tested systems is a
system that had developed by Verizon's employees. The second one is a promising
product that has been used by several other companies. Thus, my analysis tests three
systems, Verizon's current email system and two others. For confidential reasons Verizon
could not reveal to me the name of their three debatable systems. Thus, I named them as
Product One (Verizon's current system), Product Two (internally built system by
Verizon), and Product Three. Verizon did provide real informational data of each
product with their actual costs.
The experiment's goal is to offer as much guidance and information as the data
reveals to help Verizon chose the best system for their needs. It is an important issue for
Verizon, and I thus tried to obtain the most accurate results in order to best assess the
problem and make their decision easier.
Several types of decisions and measurements were involved within each part of
the study. Given that it a decision making study, these types of decisions and
measurements were key roles of the problem. In this section, I provide background
I I I I I I I I I I I [1 [] 1 I I ci
HQMO4C66 919 Hidden Ridge Irving, TX 75038
I would like to inform you that Mr. Mohammed Fahim has successfully completed the Mail Management analysis and evaluation. The report that he has produced documenting his evaluation will be considered as one of the key measures in the decision making process for the mail management platform. I hereby certify that Mr. Fahim has successfully completed his task and his deliverables matched our expectations.
Sincerely Yours Hazern Morsy Sr. e-Business Technical Manager Verizon Communications .Flazem.. Morsyverizon.. corn
:1 I information and descriptions for each part of my analysis. As mentioned earlier, I divided
the analysis approach to two parts, qualitative and quantitative. Let's first proceed to
describe the qualitative approach.
Verizon had informed me that they chose the three debated systems because they
all fulfilled Verizon's four main requirements: e-center usage, features, maturity, and
development. But an important question arose here, which system can fulfill the most
requirements? Each system had its own pros and cons in each of the four categories.
Thus, just looking at the collected-data was not sufficient for Verizon to make a decision.
After studying the given data, I realized that a model was needed that could perform a
comparison between the four categories of the three products. Thus, I decided that the
Analytic Hierarchy Method would be the best model for the specific problem. The
Analytic Hierarchy Process is a mathematical theory that was developed by Thomas L.
Saaty. The theory is a methodology for modeling unstructured problems. I describe the
theory and how it has been used in the following section.
The second part of the qualitative approach is to study the effect of Verizon's
advanced feature, VECTR, on each of the three products. VCTER is an advanced digital
email feature that Verizon relies on for their emailing process. Thus, Verizon' s
judgmental criteria will be heavily based on what product can best work with VECTR.
Moreover, Verizon had been receiving numerous complaints from their employees
regarding conflicts between Product one and the feature VECTR that often led in loss of
information and emails. Verizon managed to collect twelve-data for each product with
and without the usage of the feature VECTR. The data represented the number of
Verizon employees' complaints for each month about each system. Using the collected
I1 4
I I I I I I I I I I I I I I I I I I I
data, I designed a statistical experiment to test the three products' compatibility with and
without VECTR that would enable Verizon to see which product works the best with
VECTR. I used SAS programming to run the experiment and base my conclusions on the
SAS output.
Let's move now to the quantitative approach that was done using Engineering
Economy methods. Engineering Economy is concerned with the evaluation of
alternatives. These alternatives are usually described by estimating the amount and timing
of future receipts and disbursements. Based on the given data about each product's cost
and values, I calculated the incremental cost for each product, the equal payment sinking
fund factor for n number of years, and the current paid costs.
5
I II
Analysis Of The Situation
For the Qualitative Approach:
(I) Using the Analytic Hierarchy Method
From the project's start, I had to make a decision regarding the best study
approach. I decided the main strategy would be to find a way to analyze the data in a
categorized order, and thus divided the approach into qualitative and quantitative parts. I
first investigated the several factors that Verizon needed to obtain in their product.
Maturity level, features, supporting to new technologies and application, and accessibility
to their e-center usage were the four main factors that Verizon expected to have in their
product.
I then used the conclusive data about each product to draw a general picture of the
strengths and weaknesses, according to Verizon expectations, in each of those four
factored categories. Using the results obtained for each product, I was able to make a
general comparison between the three products in each of those categories. Breaking up
the informational data for each product, I saw that the real problem existed in how to
develop a mathematical method to perform an analytical comparison between the three
products and ultimately come up with an optimal solution or at least suggested one.
In general, decision-making problems involve several kinds of concerns: (1)
planning; (2) generating a set of alternatives {i.e. product one, product two, product
II 6
three); (3) setting priorities (i.e. the four factors); (4) designing solving systems (i.e. the
analytic hierarchy process); (5) optimizing and resolving conflict (i.e. choosing the best
product). After several investigation and trials of how to obtain an optimal result from
the given data, I concluded that applying the Analytic Hierarchy Process would be the
best fit for the problem.
The Analytic Hierarchy Process is a decision making model and also a
mathematical theory that Thomas L. Saaty developed. The model's theme is to
decompose the data by hierarchies and synthesis by finding relations through informed
judgment. The theory is a methodology for modeling unstructured problems. I describe
the theory in the following writings.
To apply the Analytic Hierarchy Process, I first needed to recognize the
unstructured problem, which in this case was finding the most suitable email system
based on Verizon's given data. I then named the set of measurements that would be
needed in the judgmental process. In this case, the set of measurements were the three
debatable email systems. The set of measurements were based on mathematics usage to
construct the right kind of theory to produce numerical scales of judgments. The third
component of the theory was the formulation of hierarchies. A hierarchy is a particular
type of system, which is based on the assumption that the entities (i.e. three products)
which we have identified can be grouped into disjoint sets called factors. However, the
factors are always dependent on their elements. Thus, each factor has its own elements,
called sub-factors. Sub-factors are always independent. The hierarchy looks as follows:
I I I I I I 1 I I I I I Li I LI II I 11 7
I 1 I I I I I I I I I I I I I I I I I
VERIZON
Product 1 I (Product 2
I Product 3l
I factors for each product: a- Maturity b- Features c- Supporting Technology d- [-center Usaqe
78 sub-factc,s Ic, each Icctcr Of eathprcduci!
Charting the hierarchy structure is a helpful tool: it provides visual details of the
system's structure and an overview of all the actors and their purposes. The chart also
shows the level of flexibility within the system, and it describes the priority in levels {i.e.
how changes at the priorities of upper levels affect the priority of elements in the lower
levels).
So far, I have explained how the structural process of the method enabled me to
put the problem in a systematic perspective. Now, I move to the mathematical and
analytical part of the method from which the judgments are mainly based.
The problem has three variables (product one, product two and product three) and
four judgmental factors to compare among the products. For instance, consider the first
factor, features, remembering that we are looking for which product has the best
"features." Since I structured each factor with ten sub-factors for each product, I now
8
I I I I I I I I I I I 1 I •1 I I I I I
compare the products' sub-factors to one another and scale the results in a certain way.
To continue with the example, let's say we are examining which system has the highest
sub-factor, web base access, of the factor "features". The judgments, when comparing
product one, product two, and product three will be based in the following manner:
• If the sub-factor "X" is equally existed in both products, give each 5 points.
• If the sub-factor "X" is weakly stronger in product one than in product two, give 6
and 4 points respectively.
• If the sub-factor "X" is stronger in product one than in product two, give 7 and 3
points respectively.
• The sub-factor "X" is very strongly in product one than in product two, give 8 and 2
points respectively.
• The sub-factor "X" absolutely stronger in product one than in product two, give 9 and
1 points respectively.
• The sub-factor "X" doesn't exist on either one of the products, give 10 and 0 points
respectively.
• The sub-factor "X" neither found in both products, give each 0 points.
I scaled the comparison based on an agreement with Verizon, as I show in more detail in
the next section.
After comparing product one to product two and assigning points, then compare
product one to product three and assign the points, and lastly compare product two to
9
product three. Going back to the sub-factor, web base access, assume that by comparing
the three products we found the following:
(Product one vs. Product two)- Product one received 7 and product two received 3.
(Product one vs. Product three)- Product one received 2 and product three received 8.
(Product two vs. Product three)- Product two received 5 and product two received 5.
Now, by adding each product's points, we get 9 points for product one---8 points for
product two--- and 13 points for product three. Thus, we can conclude that product three
has the highest point value and the best web base access among the three products.
By repeating the same procedure to all the sub-factors that existed in each factor
category, I obtained a total score for each product in each factor category. Finally, I
added each product's scores from the four factor categories, compared them, and ranked
the products in order of highest to lowest scores.
(II) Performing Statistical Experiment on the system VECTR Within the three
Products:
The main part of the study, experimental procedure, consists of the design of the
experiment that tests the effects of two controllable design factors on a quantitative
response. As mentioned, the two controllable design factors are (1) with and without the
system VECTR (2) the three e-mail products. The quantitative response of the
experiment is the number of registered Verizon employee complaints. I introduce the
I I I I I I I I I I I I I I I I I II 10
table below to illustrate the different steps in the procedure. The table emphasizes the
different steps used in the experimental procedure.
Using VECTR Without Using VECTR
Number of 1- 399 1- 729 complaints 2- 487 2- 911
registered for 3- 348 3- 520 Product(l) Number of 1- 258 1- 334 complaints 2- 321 2- 316
registered for 3- 291 3- 355 Product(2) Number of 1- 88 1- 110 complaints 2- 111 2- 126
registered for 3- 69 3- 101 Product (3)
Ilie/1/! cep is I he proccss of scict hg the I hrec -mouth data for ever y case shown in
the table. There are six cells and thus six different data sets were looked at to make a
selection. I looked at the six different data sets and randomly selected three for eaci
Given the twelve-month data set for each of the six sets, the randomization process
done as follows:
(I) I put the values of the twelve-month data given by Verizon before and after
the usage of VECTR in an order from 0 to 11 for each set.
(II) Using the Randomization table, I randomly chose a column, remembering
that the numbers in the table are from 0 to 9, and used the first two columns
from that raw.
(Ill) I assigned combinations between the random Raw and the data sets. For
example, if 04 was seen in the random table then I chose the month 4.
(IV) I repeated the process for each case of the six data sets.
In the second step, I named the first factor, with or without the System, as factor A
and the three Products as factor B. The main idea being to determine whether the factors
A and B affect the response either individually or collectively.
I ended up with eighteen values, nine in each column, and three in each cell. I then
introduced the term Yijk, where i is the level of factor A from 1 to 2, j is the level of
factor B from 1 to 3, and k is the replication from 1 to 3. For example, to know the value
of the termY23 1, look at the 2nd level of factor A that is the 'without VECTR' column,
and the P business center with the 1st replication that is 110.
For the Quantitative Part
(III) Applying Engineering Economy Methods and Techniques
As mentioned in the Management Summary, we used the Engineering Economy
methods and techniques for it. I figured that applying only the Analytic Hierarchy
Method would not be sufficient in order for Verizon to make a decision. I realized that
'cost saving' yet 'higher quality' was a big part of the decision and in order to reach the
optimal solution we needed to divide the problem into two approaches.
In the previous section we illustrated the qualitative part using the analytic
method and were able to find which system has the 'highest qualities' according to
Verizon's needs and expectations. Next, I wanted to calculate which product had the
I I I I I I I 1 I Fi I I I I I I I II 12
I I highest overall costs and which had the lowest. Since I am not the decision-maker, I
I wanted to provide Verizon with the most information about each system. Using the data
given to us, I determined several objectives important for Verizon. They are as follows:
I 1- Calculation of the Equal-Payment-Series Sinking-fund factor for each product
I total cost, in 1, 2, and 3 years.
2- Calculation of the "Current Paid Costs" that Verizon already paid for each
'I product.
I 3- Calculation of the Incremental Costs for each product.
I 4- Tabulation and interpretation of the calculations.
I I I I I I I I I I I 13
Technical Description Of The Usage Of The Analytic Hierarchy Model
The best way to describe the hierarchy model is to see it as a matrix, in this case
it's 30 matrix that is repeated several times for each sub-factor. Back to our Sub-Factor
example: Web Base Access. Thus the matrix will be as follows
lilt,r . . .
Producti Product2 Product3
oduct1 70 7 2
Product2 (0 5
oduct3 B •. . S 0
Looking back at the matrix we can see the various relations between the three
products. Notice that the sum of the first rows is 9 and that's the total points of the sub-
factor: Web Base Access, for product one. Same for product two we get 8 and for product
three we get 13. Therefore product three has the highest score. Notice also that the total
of the three "sum of the rows" is 13 + 8 + 9 = 30, and that's because the scale weight is a
total of 10 points distributed on each comparison between the three products and every
time there is 3 comparisons. { e.g. PlvsP2; PlvsP3; P2vsP3}
Thus, for each sub-factor, 30 points are distributed among the three products, and
since there are 10 sub-factors in each of the four judgmental factors, therefore 10 30 =
300 points are distributed over the three products in each factor category. Moreover,
since there are 4 judgmental factors each have 300 points. Therefore the total amount of
14
r I points is 300 x 4 = 1200 and should be ultimately distributed over the three systems. The
I system with the highest points should then become the top in our considerations.
I Before proceeding to apply the method, I need to introduce and describe the term
I
Pijk. Thus:
Pijk refers to the sub-factor k of the factor j for product i:
Where i is from 1 - 3, referring to product 1, product 2 and product 3.
Where j is from 1 -* 4, referring to the 4 judgmental factors (Features, E-Center,
Maturity, Development and Technology)
Where k is from 1 -+ 10, referring to the 10 sub-factor in each factor category.
For example, P238 refers to the 8th sub-factor in the 34 judgmental factor category for
the 2 nd product.
The way the judgments were scaled was rather long and complex. That is because
I had to compare every product's sub-factor to one another and based on the results I
scaled the scalar judgments in a matrices form. Thus, for every factor category I
compared the three products' ten sub-factors to one another. The judgments were done as
follows; if:
The sub-factor "K" is equally existed in both products, give each 5 points
The sub-factor "K" is weakly stronger in product one than in product two, give 6
and 4 points respectively
The sub-factor "K" is stronger in product one than in product two, give 7 and 3
points respectively
The sub-factor "K" is very strongly in product one than in product two, give 8 and 2
points respectively
I I I I I I I I I I I I
I 15
The sub-factor"K" absolutely stronger in product one than in product two, give 9
and 1 points respectively
The sub-factor "K" doesn't exist on either one of the products, give 10 and 0 points
respectively
The sub-factor "K" neither found in both products, give each 0 points.
Note: The way I assigned points in the process of comparison was based on the
informational data given about each product.
The four judgmental factors categories that have been determined by Verizon are:
(1) Features (2) Maturity (3) E-Center Usage (4) Development and Technology. So let's
now study and apply the Analytic Hierarchy Process on each factor separately.
(I) Features
The first of the four factors is Features. Verizon realize that in order to make a
judgment among the three products, they need to know which product has the better
features according to Verizon needs. Verizon specified ten features that they will
definitely need in their product. Thus, those ten features were in priority over other
features. Thus, The ten features are:
1- Email Routing
2- Web Base Access
3- Online Monitoring
4- Mail Merge
5- Address Book
6- Customer History
7- Schedule Reports
8- Attachment
Management
9- Stability
10-Scale Ability
I U I I I I I I I I I I I I I I I II 16
The way the comparison was performed between the three products 10-sub-factors is
done as for example; comparing the "Email Routing" for product one and two, product
one and three, and product two and three. Based on the scalar comparison, insert the
needed points in each comparison and then add the received points for each product and
put in a matrix or table (3 x 10) as wee see in the following:
H CO E LE
U. : .
Product 11 14 12 15 14 10 14 14 2 4 ONE
Product 8 14 6 9 14 10 2 2 14 13 TWO
Product 11 2 12 6 2 10 14 14 14 13 THREE
After adding the total points received for each product I get the following:
Calculation:
Total Points for Product one: 110 Total Points for Product Two:
92 Total Points for Product Three: 98
We can see that Product one has the highest points among the three products. Thus, the conclusion is
product one has the best features according to Verizon's expectations.
(II) MATURITY
The second judgmental factor is Maturity. Verizon is looking for a high level of
maturity in their product. Verizon believe that the higher the level of maturity is the
longer the product will last and the less complains will receive. After studying several
17
I I I I I I I I I I I I I I I I I I I
other products, Verizon results came to a conclusion that the three products are very
similar and only a study can differentiate which is the better product. Thus, Verizon
specified ten judgmental sub-factors for this study to determine which system with a
higher maturity level. The ten Maturity sub-factors are:
1- User Management
2- Mail Box Management
3- Groups Management
4- Message Achieving
5- Preference Controller
6- In production Maturity
7- System Host
8- Stability Testing
9- Operational Data
10-Web Form Designer
After comparing the three products, the table or matrix will look as follows: (3x10)
ca
Co E 0
0
Product 10 10 10 10 14 6 15 15 14 15 ONE
Product 10 10 10 10 5 15 6 6 2 6 TWO
Product 10 10 10 10 11 9 9 9 14 9 THREE
After adding the total points received for each product I obtained the following:
Calculation:
Total Points for Product one: 134
18
I 1 I I I I I I 1 I I I I I I I I I I
Total Points for Product Two 74 Total Points for Product Three: 92
Looking at the table results, I concluded that Product one has the highest level of maturity
among the three products.
(III) DEVELOPMENT AND SUPPORT TO NEW TECHNOLOGY
The third the judgmental factor is Development and Support to New
Technologies. Verizon seek a flexible product that can be developed and updated in the
future time. They need a product that can support and work with new technologies,
Applications and different computer languages. (e.g. Java) They determined a set of ten
measurements that according to they will make their decision. I used these ten
measurements in the study.
The ten measurements are:
1-Chat
2- Online Fulfillment
3- KB Integration
4- External Applications
5- Foreign Language Support
6- Advanced Artificial Intelligence
7- HTML Rich Text
8-Support to Other Technologies
9- API Architecture
10-Clint's Hosting
19
I 1 After the three inserting the table matrix will look comparing products and points, or a
I
follows: (3x10
I I
I P 8 Product 12 12 12 2 14 2 20 11 4 12 I ONE
Product6 10 10 15 2 16 5 13 12 12 MO
I roduct PEE THR 12 8 8 13 14 12 5 6 14 6
I I
dd i*
C ICLJI' tID (Il - 1 Total Points for Product one: 102 Total Points for Product Two:
I- Total Points for Product Three:
98 Total
300 I I I 1 20
I I Looking back at the table results, I concluded that the three products are very close to
Ieach other in the Development and Support to New Technologies factor. However,
Product one slightly exceeded the other two products. I (IV) E-CENTER USAGE
I The last judgmental factor is the Accessibility to the E-Center Usage. Verizon's
I
B-Center Department plays such a vital role in the company's fast and accessible work.
As a result the company needs to provide them with an Email product that can fit them
I the most. After studying several features and measurements, E-center agreed on ten
I
measurements that they would need the most in their product. Thus, I applied the process
according to those ten measurements and they are as follows: II
i- Email Support Availability
2- SLA Implication
3- Usability 1 4- Keeping up with technologies
5- Distribution Administration
I6- Virus Detection
7- Email-Type supported
I 8- Web Pages Modified
9- Email Security
10- Customer Service Index IAfter finishing the appropriate calculations, the matrix will look as follows:
Hi C,)
.2 °O)
Cl) Q) uJ c
Z13 %C Q) 0
Prod Product ONE 14 18 10 10 14 18 8 6 10 9
I [1 I I 21
Product Two 2 6 10 10 14 6 11 16 10 9
Product 1 THREE 14 6 10 10 2 6 11 8 10 12
When I added the total points for each product I got the following:
Calculation:
Total Points for Product one: 117
Total Points for Product Two: 94
Total Points for Product Three: 89
Total = 300
Looking at the table results we see that Product one received the highest points. Thus,
Product one will be the most satisfying for the E-center usage.
The final step in the Hierarchy Process is to add up each product points that have
been calculated throughout the four judgmental factors. Thus, I calculated the following
table:
PRODUCT ONE PRODUCT TWO PRODUCT THREE
MATURITY 134 74 92
FEATURES 110 92 98
E-CENTER USAGE 117 94 89
DEVEOPMENT AND TECNOLOGIES
104 101 98
TOTAL 462 361 377
22
I I Looking at the table results, we see that Product One has earned the highest points
with 462 points, followed by Product Three with 377 points, and finally Product Two
with 361 points.
The Interpretations and conclusions will be followed in the Conclusions section.
11
H123
Technical Description of the Statistical Experiment
As mentioned, we use Two Factor fixed effects model to determine what product
works the best with the feature VECTR.
The Model used to test the experiment is: the Two Factor Model given as:
Yzjk = t+ài + Pj + (âJ)ij -i-Eijk
With the assumption of:
Za=0
There are three Hypotheses to be tested they are as follows:
1. Ho:âl=â2= ... =âi=O Hi: At least one of the âi's is not equal to zero
2. Ho :31=f32= ... =3j=O Hi: At least one of the 3j's is not equal to zero
3. Ho :(ãf3)il=(af3)12= ... =(af3)ab Hi: At least one of the (âJ)ij's is not equal to zero
The testing procedure will be as follows:
Step 1: Test for Interaction (3)
Step 2: If Interaction is not significant, Test for Main Effects (I, H) and perform
Duncans Multiple Range on Marginal Means.
Step 3: If Interaction is not significant, stop and do Duncans Multiple Test on Cell
Means.
24
Now, let's show the difference between the Marginal Means and the Cell Means. To do
that let's view the illustration table agaw
Using VECTR Without Using VECTR
Number of 1- 399 1- 729 complaints 2- 487 2- 911
registered for 3- 348 3- 520 Product (1) Number of 1- 258 1- 334 complaints 2- 321 2- 316
registered for 3- 291 3- 355 Product (2) Number of 1- 88 1- 110 complaints 2- 111 2- 126
registered for 3- 69 3- 101 Product(3)
For the Marginal Means:
Cwlculwtc the mean of the first, second. and third row, which Will he the sulillihlt R)I) 01'01C lie
six numbers of the first, second and third row divided by six, which they found to he
equal to 565.6, 312.5 and 102.5 respectively. Accordingly, run the Duncans Multiple
For ('cli Walls.
Calculate the means of each cell. Which i a t:a c.c \\ III C.
411.33 for (Center!, Using VECTR
290.00 for (Center2, Using VECTP
I'm r tCeiiter, t sin VICTk)
72().t)() tor ('eaten. 1ine V[('TR)
335.00 for (Center2, Using VECTR)
115.67 for (Center3, Using VECTR)
Using these means, run Duncans Multiple Range.
Using SAS, I wrote the following program with the given file data:
Where V refers to 'with VECTR'
W refers to 'Without VECTR'
And 1,2,3 refers to the three business centers.
The data file was saved in a file called Project.data and looks as follows:
Project.data' file:
V 1 399 V 1 487 V 1 348 V 2 258 V 2 321 V 2 291 V 3 88 V 3 111 V 3 69 W 1 729 W 1 911 W 1 520 W 2 334 W 2 316 W 2 355 W 3 110 W 3 136 W 3 101
26
I I I I I I I I I I I I I I I I I I I
The Following is the SAS statement:
FILENAME f 'project. data';
Options ls=80;
DATA one;
1NFILE f 1;
INPUT type$ center response;
PROC GLM;
Class type center;
MODEL response= type center type*center;
Title 'Project -- 2 Way ANOVA';
means type center/Duncan;
RUN;
PROC MEANS;
run;
27
After running the program, SAS gave the following output:
Project -- 2 Way ANOVA 20:48 Monday, April 29, 2002
The GLM Procedure Class Level Information
Class Levels Values type 2 VW center 3 123
Number of observations 18 Project --2 Way ANOVA
20:48 Monday, April 29, 20 Dependent Variable: response
Sum of
Source DF Squares Mean Square F Value Pr > F
Model 5 792423.7778 158484.7556 20.96 <.0001
Error 12 907440000 7562000€
Corrected Total 17 883 167.7778
R-Square Coeff Var Root MSE response Mean
0.897252 26.60224 86.95976 326.8889
Source DF Type ISS Mean Square F Value Pr > F
type 1 72200.0000 72200.0000 9.55 0.0094
center 2 645433.4444 322716.7222 42.68 <.0001
ypeenj 2 747903333 373951667 495 00271!
First, test for Interaction:
H°: (â3)1 1 = (â3)12 =. . .=( â3)ab Hi: At least one of the (6f3)ij's is not equal to zero
The highlighted cell refer to the interaction P-Value,
F = 4.95; P_value = .027
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I I I I I I I I I I I I I I I I I I I
Since 0.027 < 0.05, we reject the null h ypotheses and conclude that there is
Significant Interactiot
The next two stcps tie the raphi 01 Intetact on Plot and the Icst of I)uncwis NiuhtipIc
Ran o c on cells.
The second step is to run Duncans Multiple range 'lest on the cell means. The test
willa! low us to see when the number of complaints vas the highest and when it was the
I OW C st
Duncans Multiple Range Test on Cell Means:
Using VECTR Without Using VECTR
Number of 1- 399 1- 729 complaints 2- 487 2- 911
registered for 3- 348 3- 520 Product(]) Number of 1- 258 1-334 complaints 2- 321 2- 316
registered for 3- 291 3- 355 Product (2) Number of 1- 88 1- 110 complaints 2- 111 2- 126
registered for 3- 69 3- 101 Product (3)
The first step 1 s to calculate the mean of each cell and order them lroiii the liihiest to the
I&)\ esL
- We will use the following denotation to refer to the six celL
A: refers to cell (1, 1), (Product One, Using VECTR
ft dci to cell (2. I). (Product T o, sine VFC!R)
C; refcis to cell 3. I). Product Three, si ii Vl1( '['R)
29
D: refers to cell (1,2), (Product One, Without VECTR)
E: refers to cell (2,2), (Product Two, Without VECTR)
F: refers to cell (3,2), (Product Three, Without VECTR)
Thus, the values of the means are as follows shown from the highest to the lowest:
D A E B F C
720 411 335 290 115 89
the second step is to calculate the values of Rp's based on the following formula:
FNRp=rp
Where:
MSE: Mean Squared for Error taken from the SAS output
N: Number of observation for each cell
rp: Least Significant Ranges that are obtained from table A. 12 with 12 degrees of
freedom
p: Number of Compared Values
Here's the calculation for the Rp's, since there are six means to be compared, thus
I calculated R2 to R6,. The values are as follows
R2= 154.7
R3= 161.89
R4= 166.31
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1 I I 1 I I I I I, I I I I I I I I I I
R5= 169.174
R6= (170.68
The third step is to do the actual comparison:
Comparison p Rp Actual Difference
DvC 6 170 720-89>170
DvF 5 169.17 720-115>169.17
DvB 4 166.4 720 - 290 > 166.4
DyE 3 161 720-334>161
DvA 2 154 720 -411 > 154
AvC 5 169.2 411- 89>169.2
AvF 4 166.3 411-115>166.3
AvB 3 161.9 411 —290 NOT> 161.9
EvC 4 166.3 335-89>166.3
EvF 3 161.9 335-115>161.9
EvB 2 154 335-290 NOT > 154
BvC 3 161.9 290-89>161.9
BvF 2 154 290-115 NOT >.154
FvC 2 154 115-89 NOT> 154
Based on the above calculation we can Draw the following diagram:
DAEBFC
31
I I The above diagram shows that the cell D is Significantly Different than all other cells.
ICell A and E is Significantly Different than F and C. Cell B is Significantly Different
than cell C.
** The interpretation of our finding we will be shown in the conclusion of the project.
I I I I I I, 1 I I I I I I 32
Technical Description of the Usage of Engineering Econom y Methods
Ilic USaC of the En-Mcci-111 0 CC0110111Y MCth()dS allowed iiic to hriiiat the
financial data that has been given to me in an easier form that can be more visible to
Verizon in their studies.
The first step I intended to do was to bring all the financial information together
in one table. I designed the table as a comparison between the three products various
costs. Thus, by just looking at the table, Verizon can visualize the differences
between the costs. The table looks as follows:
Actual Costs Table
Cost Type Sub Cost Type Product One Product Two Product Three
Software 400,000 0 0 User's License 900,000 0 490,000
VENDOR COSTSProfessional services 300,000 0 600,000
H/W AND S/W 2,500,000 2,500,000 4,000,000 IT COSTS
D&E 300,000 500,000 2,700,000
Technical Support 557,000 550,000 550,000
ADDITIONAL
Call center Migration 400,000
400,000
450,000 COSTS
AGENTS TRAINING
300,000
300.000
Totals 5,657,000
4.250,000
9,090,000
Looktiic at the table. can cc that there aic tinec tvpe' ol cok; Vendor (ots, IT
costs and Additional Costs. The table allows us to conipare the costs of three products
in each type of cost
Thus, by breaking do n the cost \,t1tICS I obtained tile Io!lo\\ iiic rciiIt-:
1 I I I I I I I I I I I I I I I I I I
(I) Product three has the highest overall costs.
(II) Product two has the lowest overall costs.
(III) Product One has the highest Vendor costs
(IV) Product Two has no Vendor costs, thus Verizon will not be charged for any
software or License usage.
(V) Product Three has very high IT costs
Let's now proceed to our objective plan:
(1) Calculate the Equal-Payment-Series Sinking-Fund factor, for 2, 3 and 4 years.
The Equal-Payment-Series Sinking—Fund is the total amount required at the end
of period-payment. By looking back on the previous table, let's consider the last total
cost amount for each product as the 'Future Cost' amount that Verizon will eventually
need to pay in case of ordering the product.
Thus, in order to calculate the equal-payment-series, we need first to know what
interest rate is applied and the value of the future value for each of the three products.
After coordinating with Verizon, the interest rate was known to be 5% annual interest
rate and the future values for each product has been calculated from the previous table.
Now we can proceed for the calculation part:
(a) First let's introduce the formula for the Equal-Payments-Series. It's as follows:
A=E[ }
34
1 I I I I I I 1 I I 1 I I I I I I I I
A: the Equal-Payments-Series over n years.
F: the total amount calculated from the actual costs table.
i: the interest rate given as 5% per year.
Thus, for product one: at n =2:
A= 5,657,000[ 0.05
1 = $ 2,759,511.7 (1.05)2_i
Illustration: in case Verizon wanted to have a 2 years payment at 5% interest rate they
will have to pay 2,759,511.7 at the end of each year to get product one.
Product one at n =3:
A= 5,657,000[3 0.05
1 = $ 1,794,448.4
Illustration: in case Verizon wanted to have a 3 years payment at 5% interest rate they
will have to pay $ 1,794,448.4 at the end of each year to get product one.
Product one, at n =4:
A= 5,657,000[4 0.05
1 = $ 1,312,490.7
Illustration: in case Verizon wanted to have a 4 years payment at 5% interest rate they
will have to pay $ 1,312,490.7 at the end of each year to get product one.
35
Now, let's do the same for product two. Thus, the equal payments for product two
at the end of 2,3 and 4 years will be determined using the same as equation as above
however the Value of F (total cost for product 2) will change to $ 4,250,000.
Our calculation will be as follows:
Product Two at n =2:
A= 4,250,000[ 0.05
2 —1 = $2,073,170.4
Illustration: in case Verizon wanted to have a 2 year-payment at 5% interest rate they
will have to pay $ 2,073,170.4 at the end of each year to get product two.
Product Two at n =3:
A=4,250,000[ 0.05 (1.05) _1' = $ 1,348,136.1
Illustration: in case Verizon wanted to have a 3 year-payment at 5% interest rate they
will have to pay $ 1,348,136.1 at the end of each year to get product two.
Product Two at n =4:
05 A= 4,250,000[
0.] = $ 986,050.15
(1.05) 4 —1
Illustration: in case Verizon wanted to have a 4 year-payment at 5% interest rate they
will have to pay $ 986,050.15 at the end of each year to get product two.
W.
1 1 I I I 1 I I I I I I I I I I 1 I I
Following the same procedures for Product three as for Product one and two with
changing the total actual cost to $ 9,090,000, we will be able to get the following equal
payments at the end of 2, 3 and 4 years.
Product Three at n =2:
05
A= 9,090,000[ 0.
I = $ 4,434,145.56 (1.05)2_i
Product Three at n =3:
05
A= 9,090,000[ 0.
I = $ 2,883,425.2 (1.05) 3 —1
Product Three at n =4:
A= 9,090,000[ 0.05
I = $ 2,108,987.2 (1.05)4-1
Finally let's organize the calculated data on a table thus the information can be easier for
the reader:
Number ofValue of the Value of the Value of the
YearsEqual Payments Equal Payments Equal Payments
for Product 1 for Product 2 for Product 3
Two Years$2,759,511.7 $ 2,073,170.4 $4,434,145.56
Three years$ 1,794,448.4 $ 1,348,136.1 $ 2,883,425.2
$ 1,312,490.7 $ 986,050.15 $ 2,108,987.2 Four Years
37
The above table is a summarization of the previously shown calculations. Using the table,
Verizon can learn the cost of each product at the 5% interest rate at the end of 2, 3 and 4
years.
(2) Calculate the "Current Paid Costs" that Verizon already paid for each product.
After being informed that Verizon had made some payments regarding each
product, we thought it would be beneficial for them to know the exact amount that had
been paid for each product. After corresponding with Verizon, we realized that Product
one has been already installed within their email system thus the company has been
paying its fees. Verizon also ordered a trial usage period from the third email product that
they had to pay for. For product one, we have been informed that since Verizon
employees internally build the product, therefore the product didn't cost any fees. Thus
we gathered the data given and came to the following calculations shown in the table
below:
Product One Product Two Product Three
User's License $ 200,000.00 $0.00 $ 490,000.00
services Professional $ 300,000.00 $0.00 $ 600,000.00
Agents Training $ 300,000.00 $0.00 $ 0.00
Costs Total Current Paid $ 800,000.00 $0.00 $ 1,090,000.00
* The highlighted cells show the total Current Paid Costs for each product. Thus, Verizon
can know the total amount they already paid; we thought that might be useful to their
decision process.
38
I I I I (3) Calculate the incremental costs for each product.
I
I realized that calculating only the paid cost wouldn't be sufficient. Thus, I
thought providing information for the amount that still needs to be paid: Incremental
I
Costs, regarding each product would be beneficial. From the previous table, I showed the
exact current paid costs that was paid by Verizon. To get the Incremental Costs for each I product simply apply the following equation:
I Incremental Costs = Actual Costs - Current Paid Costs
I I Thus, the Incremental Costs for Product one = the Actual Cost of Product one (given in
' table 1) - Total current paid costs. Therefore it's equal to:
$5,657,000.00 - $800,000.00 = $4,857,000.00
I Therefore, Verizon would still need to pay $4,857,000.00 in order to get Product One.
IOn the other hand, The Incremental Costs for Product Three can be calculated as follows:
$9,090,000.00 - $1,090,000.00 = $8,000,000.00
Therefore, Verizon would still need to pay $8,000,000.00 in order to get Product Three.
Using the above Calculation we can compare the Incremental Costs in the following
table:
I Li I I I I 39
Cost Type Product One Product Two Product Three
Current Paid Costs $ 800,000.00 0.00 $1,090,000.00
Incremental Costs $4,857,000.00 0.00 $8,000,000.00
Note: hicrcnicntt1 Cot for Product o ht to bc Zero sincc the prodtict ha hccn hui It IocaII\. I
'
1 find that providing Verizon with Incremental cost information can be very usciul
to them, as they know now the rest of the payment amount in order for them to buy each
I product.
I I I
I I I I
I I I I
Ii I I
I I I I
40
Conclusions
My conclusions to Verizon are based on the results I obtained from both the
Qualitative and Quantitative parts of the project. Since I did three different tests on the
data collected by Verizon, my conclusions will be based on the results of those tests.
(I) Conclusions for the Analytic Hierarchy Process
Let's first look back at the results obtained from applying the Hierarchy process:
PRODUCT ONE PRODUCT TWO PRODUCT THREE
MATURITY 134 74 92
FEATURES 110 92 98
E-CENTER USAGE 117 94 89 DEVEOPMENT AND
TECNOL OGlES
TOTAL
104
462
101
361
98
- 377441*S
Looking at the table above I concluded that Product One has the highest overall collected
points through the comparison in each of the four judgmental factors. Product Two and
Three are very close to each other. Thus, according to Verizon needs and expectations to
their email system, I advise them that product one will meet their judgmental criteria the
best.
(II) Conclusions for The Statistical Experiment
By looking back at the SAS, Interaction Plots and Duncans Multiple Test results,
I concluded the following:
(a) There is a significant difference in the interaction between the three systems
before and after the usage of system VECTR.
41
(b) The highest number of employee's complaints happened in the case of using
Product One without the usage of VECTR. Thus, a critical conclusion here is
to advise Verizon not to use the Email system One without installing the
feature VECTR with it.
(c) The Third E-mail system has the lowest number of complaints when used with
VECTR. Thus, I concluded that the Third E-mail system is most compatible
with the VECTR feature.
(d) The number of complaints for the second Email system didn't change much
with and without the usage of VECTR.
(III) Conclusions for The Usage of the Engineering Economy Methods
Based on the following tables, I concluded my results:
Table shows the comparison between Incremental Costs and Current paid Costs for each
product:
Product One Product Two Product Three
Current Paid Costs $ 800,000.00 0.00 $1,090,000.00
Incremental Costs $4,857,000.00 0.00 $8,000,000.00
Thus:
(a) Product Three has the highest Current Paid Costs and Incremental Costs yet
it's not used yet. Those costs are the trial usage costs.
(b) Product Two has the lowest Current Paid Costs and Incremental costs. Since
it's internally built by Verizon employees.
42
1 I I I I I 1 1 I I I I I I I I I I 1
Final Conclusion
Based on the previous conclusions, I can summarize my findings for each product
as follows:
Product Three
(a) Highest cost product
(b) Has the best compatibility with the system VECTR
(c) Average in meeting Verizon' s four factors expectations
Product One
(a) Average cost Product
(b) Has an average compatibility with the feature VECTR
(c) Highest in meeting Verizon' s four factors expectations
Product Two
(d) Lowset cost Product
(e) Has a low compatibility with the feature VECTR
(f) Average in meeting Verizon's four factors expectations
43