ISYS2056 Business Computing Report: Pete's Cheap Car Sales Analysis

This business computing report analyzes the performance of "Pete's Cheap Car Sales", a small second-hand car yard, focusing on stagnating profits and sales staff performance. The report examines sales data from January to June 2018, analyzing car sales based on manufacturing year and the duration cars remained in the car yard. The analysis reveals that cars from 2017 had the highest sales but also the longest holding period, particularly for private/retail vehicles. The report also evaluates individual salesperson performance, identifying the top performer, Jules Ng, who generated the highest profit and sold the most vehicles. The report concludes with recommendations to improve profitability, such as focusing on fleet customers and considering factors beyond sales figures for staff promotions.

business computing report
Business Computing 1 (ISYS2056)
Ali Bangash, S3657986
Tutors:
Ana Bianca Ananieve
Terry Sheehan

BUSINESS COMPUTING REPORT
Table of Contents
Introduction...............................................................................................................................2
Analysis regarding the stagnating profits and review of sales staff..........................................2
Analysis on the stagnating profits..........................................................................................2
Analysis on the review of sales staff......................................................................................4
Results of the Analysis................................................................................................................5
Results from analysis on the stagnating profits.....................................................................5
Results from analysis on the review of sales staff.................................................................6
Discussion regarding other factors............................................................................................6
Conclusion..................................................................................................................................6
Recommendations.....................................................................................................................6
Bibliography...............................................................................................................................7
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BUSINESS COMPUTING REPORT
Introduction
“Pete’s Cheap Car Sales”, is a small second-hand car yard situated in Melbourne, Victoria.
This small business consists of not more than four employees and facing a downward slope
in their business activities. The purpose of this report is to analyse the performance of this
business in regards to its profitability level, as well as staff performance, in order to help this
business in achieving their goals of increased profits and reduced vehicle turnover time. In
this report, the staff performance is also analysed as one of the senior salesperson has
announced retirement so a junior salesperson will be promoted in that place. This report
will help to understand the current situation of the business so that recommendations can
be provided to make necessary changes in their business.
Analysis regarding the stagnating profits and review of sales staff
Analysis on the stagnating profits
From the given sales data of January to June 2018, the analysis has been carried out to find
the total sales value of cars based on the manufacturing year. The table below represents
the total value of cars sold as per the year:
Year Fleet private/retail Grand Total
2004 $ 4,500.00 $ 4,500.00
2005 $ 3,500.00 $ 4,700.00 $ 8,200.00
2006 $ 3,500.00 $ 3,500.00
2008 $ 45,000.00 $ 45,000.00
2009 $ 29,300.00 $ 47,000.00 $ 76,300.00
2010 $ 73,052.00 $ 75,200.00 $ 148,252.00
2011 $ 98,800.00 $ 98,800.00
2012 $ 16,500.00 $ 153,499.00 $ 169,999.00
2013 $ 53,298.00 $ 78,649.00 $ 131,947.00
2014 $ 91,450.00 $ 164,250.00 $ 255,700.00
2015 $ 281,309.00 $ 575,406.00 $ 856,715.00
2016 $ 648,518.00 $ 1,293,925.00 $ 1,942,443.00
2017 $ 1,012,288.00 $ 1,825,386.00 $ 2,837,674.00
2018 $ 280,749.00 $ 623,288.00 $ 904,037.00
Grand Total $ 2,493,464.00 $ 4,989,603.00 $ 7,483,067.00
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BUSINESS COMPUTING REPORT
2004 2005 2006 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018
$-
$500,000.00
$1,000,000.00
$1,500,000.00
$2,000,000.00
$2,500,000.00
$3,000,000.00
Total Sales
Fleet
private/retail
From the above analysis, it has been identified that the cars of 2017 has the highest sales.
Another analysis that has been conducted is the number of days the cars were in caryard
prior to sales based on the type of fleet sales and year. The table below has been presented
to demonstrate the analysis so that decision can be made on the sales patterns:
Year
2004
2005
2006
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
Fleet 3 13 16
7
81 15 25 99 22
5
851 704 18
4
private/
retail
1 21 20
6
9 21
9
17
3
15
3
23
0
16
0
58
8
106
1
158
9
18
7
Grand Total 1 24 13 20
6
17
6
30
0
17
3
16
8
25
5
25
9
81
3
191
2
229
3
37
1
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BUSINESS COMPUTING REPORT
F l e e t p r i v a t e / r e t a i l
3
21
13
167
9
81
219
15
153
25
230
99
160
225
588
851
1061
704
1589
184
187
1
206
173
Vehicles in caryard 2004
2005
2006
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
In the above analysis, it has been identified that cars manufactured in 2017 were being held
more in the caryard and that that too it was Private/Retail type vehicles.
Analysis on the review of sales staff
In this analysis, the total profit achieved by the individual salesperson has been calculated.
The table below represents the value of total profit generated by the four salesperson:
Salesperson Total profit
SALES001 $ 259,234.00
SALES002 $ 261,091.85
SALES003 $ 400,926.10
SALES004 $ 104,607.50
Grand Total 1025859.45
25%
25%
39%
10%
Total profi t
SALES001
SALES002
SALES003
SALES004
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BUSINESS COMPUTING REPORT
In the above analysis, it has been determined that salesperson “SALES003” that is Jules Ng
contributed the most with a total sales value of $ 400,926.10.
Next, the number of vehicles being sold by the salesperson was calculated according to the
types of vehicles. The table for the data collected on the vehicle sales is presented as below:
Salesperson Fleet private/retail Grand
Total
SALES001 15 52 67
SALES002 54 16 70
SALES003 13 62 75
SALES004 5 32 37
Grand Total 87 162 249
SALES001 SALES002 SALES003 SALES004
15
54
13
5
52
16
62
32
Type of Vehicles Sold
Fleet
private/retail
From the above analysis, it has been identified that salesperson “SALES003” (Jules Ng) has
sold the most number of vehicles that is 75.
Another analysis that was being conducted for analysing performance of the staffs is the
total sales with respect to the count of vehicles being sold by the individual salesperson.
Salesperson Vehicles Sold Total Sales
SALES001 67 $ 1,856,117.00
SALES002 70 $ 1,975,764.00
SALES003 75 $ 2,567,337.00
SALES004 37 $ 1,083,849.00
Grand Total 249 $ 7,483,067.00
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BUSINESS COMPUTING REPORT
SALES001 SALES002 SALES003 SALES004
0
500000
1000000
1500000
2000000
2500000
3000000
67 70 75 37
$1,856,117.00 $1,975,764.00
$2,567,337.00
$1,083,849.00
Total Sales
Vehicles Sold
Total Sales
The above analysis depicts that salesperson “SALES003” (Jules Ng) has the most total sales
with a value of $ 2,567,337.00.
Results of the Analysis
Results from analysis on the stagnating profits
The analysis being carried out with respect to the stagnating profits demonstrates that most
of the cars which were being held in the caryard for more duration is manufactured in the
year 2017 and that too those were of Private/Retail types. This means that the popularity of
the Private/Retail types is less than the Fleet type cars. However, the most sales was
achieved from the cars of 2017 year that is $2,837,674.00. From the count of vehicles being
held in caryard, it has been determined that there is less demand from private/retail
customers about $ 4,989,603.00 but the total sales was higher as compared to Fleet
customers. Hence, it is recommended that the business should focus more on private/retail
customers.
Results from analysis on the review of sales staff
From the analysis on review of sales staff, it has been identified that the salesperson “Jules
Ng” is the most suitable salesperson for the position of senior salesperson. Jules Ng is
considered appropriate for the promotion as the analysis shows “SALES003” has the most
count of vehicles sold and it contributes to most of the sales being done by the business.
Discussion regarding other factors
The other factors that has to be taken into consideration before making final decision for
the staff promotion is the behavior and other competitive skills. The technical skills along
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BUSINESS COMPUTING REPORT
with the loyalty of that staff have to be analyzed and evaluated prior to promotion. The
sales figure should not be considered as the single criteria for promoting to senior
salesperson.
Conclusion
From the overall analysis from the provided sales data of “Pete’s Cheap Car Sales”, it has
been identified that the main reason behind stagnating profits is sitting of certain cars in the
car yard for longer periods of time. The review of staffs with respect to the total sales and
count of vehicles being sold demonstrates that Jules Ng is the most suitable person for
promotion to senior salesperson.
Recommendations
 The focus should be given on fleet customers so that the cars could be sold at
increased rate and there is no stock overflow in the car yard.
 The sales figure only should not be considered while promoting the staff.
 The purchase of the vehicles from auction should be done more of latest vehicles
rather than old make and model.

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BUSINESS COMPUTING REPORT
Bibliography
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Kumar, B.A. and Rahamathulla, V., 2018. A Novel Approach of Quantitative Data Analysis using
Microsoft Excel.
Mondal, H. and Mondal, S., 2016. Sample size calculation to data analysis of a correlation
study in Microsoft Excel®: A hands-on guide with example. International Journal of Clinical
and Experimental Physiology, 3(4), p.180.
SlezÃ, P., Bokes, P., Pavol, N.Ã. and WaczulÃkovÃ, I., 2014. Microsoft Excel add-in for the statistical
analysis of contingency tables. International Journal for Innovation Education and Research, 2(5),
pp.90-100.
Tanavalee, C., Luksanapruksa, P. and Singhatanadgige, W., 2016. Limitations of using
Microsoft excel version 2016 (MS excel 2016) for statistical analysis for medical
research. Clinical spine surgery, 29(5), pp.203-204.
Winston, W., 2016. Microsoft Excel data analysis and business modeling. Microsoft press.
Zhu, J., 2014. Quantitative models for performance evaluation and benchmarking: data
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