Project Management Eriksson and Kovalainen 2022

PROJECT
MANAGEMENT
STUDENT ID:
[Pick the date]

PART A
 The following are the key attributes related to the given dataset (Eriksson and Kovalainen,
2015).
1) There are very few values which are missing in the data which implies that this
problem can be resolved without impacting the original data set in any significant
manner. Also, the missing values seem to be random only.
2) The sample size considered by the dataset is quite large which allows better
comparison and relationship building across the given variables.
3) The relevant variables which would be of interest to the user such as sales and profit
have been included. Additionally, the variables influencing these two have also been
reflected in the dataset.
4) Considering that the dataset is not skewed towards the use of a particualr type of data
i.e. quantitiative or qualitative, hence the range of tools available for analysis
increases.
 Considering the above reasons, the data quality does not pose much concerns and hence
has a superior quality.
 The given data provides information on randomly selected 8399 customer purchases.
 The data presented for each of these customer purchases has used qualitative as well as
quantitative variables which provides extensive information about the transactions.
 Some of the qualitative variables included in the dataset are producr category, mode of
shipping, product sub-category, order priority etc.
 Some of the quantiative variables included in the dataset are are unit sales, profit, sales,
discount, order quantity etc.
PART B
 The impact of the various factors on profitbaility has been analysed based on the
correlation matrix between the potential variables.
1) It would be expected that higher order quantity would typcially lead to higher profits
but the relationship witnessed based on given data is weak in strength despite being
positive. This may be attributed to lower pricing for bulk orders.
2) The sales and profits tend to have a moderately strong positive relationship which is
not surprising.

3) It is evdient that highest profits on average are attributed to the products which are
transported through truck. This may be attributed to this transportation means having
lower cost than other transportation means.
4) Technology seems to have the highst profit margin which is not expected as the
margins are quite high in this product segment owing to the variables costs being quite
limited and the selling price being quite high.
5) In technology also, the highest amount of profits are seen in copiers and faxes. This
implies that product sub-category also drives profitability.
 The impact of the various factors on sales has been analysed based on the correlation
matrix between the potential variables.
1) Unit price is a key determinant since sales is directly proportional to the changes in
unit price but the relationship is moderate in stregnth.
2) The order quantity also influences the sales but the relationship is weaker than
expected which may be attributed to potential discounts being given on bulk orders.
3) The average selling prices of different product and sub-categories differs as technology
driven copies and fax tend to have higher sale price leading to higher sales.
4) A noteworthy aspect is that the sales is not driven by discounts in any significant
manner.
PART C
Some of the key visualisations for the given data using MS-Excel as attached beow.
 Key observations are as follows.