Jacket Frenzy is a small clothing manufacturer, specializing in
creating custom, one-of-a-kind jackets. They
exclusively sell their product through their online store.
Jacket Frenzy is run by a team of three staff members: April,
Beatrice, and Claudia.
April and Beatrice work together to manufacture jackets. Claudia
manages orders, sales and delivery.
Jacket Frenzy receive requests through their online store, and
Claudia responds with a quote, after
consulting with a member of the manufacturing team. If the customer
confirms their order, April and
Beatrice manufacture the ordered products, and Claudia organizes
delivery.
Currently, the process for generating a quote is entirely
subjective, based on the requested material and
jacket size. Staff members quote an amount based on their personal
experience.
For several months, staff have been keeping track of the quote
date, material, size, quote amount, and
manufacturing cost for each order in a spreadsheet. As each product
is hand-made, the manufacturing
cost may vary between similar orders.
If a quote was not accepted by the customer, then manufacturing
cost is not included.
This spreadsheet is available below
Quote date | Material | Size | Quote amount | Manufacturing cost ($) |
2018-06-04 | Cotton | S | 76.3 | 25.3 |
2018-06-05 | Cotton | L | 68 | 31 |
2018-06-06 | Wool | L | 80.3 | 47.1 |
2018-06-06 | Leather | XL | 247.6 | 71.8 |
2018-06-06 | Wool | L | 78 | 46 |
2018-06-07 | Wool | M | 94.8 | 39.6 |
2018-06-08 | Wool | XS | 154.1 | 30.3 |
2018-06-08 | Wool | L | 121 | 44 |
2018-06-11 | Wool | XS | 63.3 | 31.3 |
2018-06-11 | Tweed | XL | 169 | 82 |
2018-06-12 | Wool | XS | 91.3 | 32.1 |
2018-06-13 | Wool | L | 111.6 | 45.8 |
2018-06-13 | Tweed | XL | 238 | 81 |
2018-06-13 | Wool | XXL | 114.8 | 56.6 |
2018-06-14 | Wool | L | 123.1 | 46.3 |
2018-06-14 | Wool | M | 107 | 39 |
2018-06-14 | Wool | XXL | 116.3 | 56.3 |
2018-06-14 | Cotton | XL | 94 | 31 |
2018-06-15 | Wool | XL | 156.3 | 52.1 |
2018-06-18 | Silk | S | 363.6 | 86.8 |
2018-06-18 | Wool | XS | 74 | 32 |
2018-06-18 | Cotton | M | 83.8 | 26.6 |
2018-06-19 | Cotton | L | 70.1 | 28.3 |
2018-06-20 | Tweed | XXL | 198 | 97 |
2018-06-20 | Cotton | M | 71.3 | 24.3 |
2018-06-21 | Leather | XXL | 231 | 75 |
2018-06-21 | Tweed | XL | 222.3 | 82.1 |
2018-06-22 | Silk | M | 236.6 | 93.8 |
2018-06-22 | Wool | L | 166 | 50 |
2018-06-22 | Wool | M | 154.8 | 42.6 |
2018-06-25 | Wool | XS | 100.1 | 34.3 |
2018-06-26 | Wool | S | 93 | 41 |
2018-06-26 | Cotton | L | 91.3 | 29.3 |
2018-06-27 | Wool | L | 100 | 49 |
2018-06-27 | Wool | L | 103.3 | 49.1 |
2018-06-27 | Cotton | L | 79.6 | 28.8 |
2018-06-27 | Wool | XL | 129 | 54 |
2018-06-28 | Wool | S | 155.8 | 42.6 |
2018-06-29 | Wool | XXL | 156.1 | 64.3 |
2018-07-02 | Cotton | M | 64 | 24 |
2018-07-02 | Wool | XS | 106.3 | 35.3 |
2018-07-03 | Cotton | L | 86 | 29 |
2018-07-03 | Cotton | S | 78.3 | 22.1 |
2018-07-04 | Wool | XS | 106.6 | 35.8 |
2018-07-04 | Cotton | S | 64 | 22 |
2018-07-04 | Wool | L | 122.8 | 52.6 |
2018-07-05 | Tweed | XS | 250.1 | 55.3 |
2018-07-06 | Cotton | XXL | 100 | 34 |
2018-07-06 | Cotton | M | 84.3 | 25.3 |
2018-07-06 | Cotton | L | 92 | 28 |
2018-07-09 | Tweed | XS | 173.3 | 55.1 |
2018-07-09 | Cotton | XS | 70.6 | 19.8 |
2018-07-09 | Leather | XS | 160 | 42 |
2018-07-09 | Cotton | L | 89.8 | 28.6 |
2018-07-10 | Wool | L | 115.1 | 53.3 |
2018-07-10 | Cotton | M | 73 | 24 |
2018-07-10 | Silk | S | 384.3 | 88.3 |
2018-07-10 | Leather | L | 206 | 60 |
2018-07-11 | Wool | M | 127.3 | 46.1 |
2018-07-11 | Tweed | XS | 211.6 | 56.8 |
2018-07-11 | Cotton | XXL | 104 | 33 |
2018-07-11 | Wool | XXL | 155.8 | 64.6 |
2018-07-12 | Wool | S | 165.1 | 42.3 |
2018-07-12 | Wool | XS | 125 | 36 |
2018-07-13 | Tweed | S | 276.3 | 68.3 |
2018-07-13 | Wool | S | 144 | 42 |
2018-07-13 | Wool | XL | 134.3 | 57.1 |
2018-07-13 | Wool | XXL | 192.6 | 63.8 |
2018-07-16 | Wool | M | 122 | 48 |
2018-07-17 | Cotton | XL | 75.8 | 31.6 |
2018-07-18 | Cotton | XS | 58.1 | 18.3 |
2018-07-18 | Tweed | XXL | 316 | 105 |
2018-07-19 | Wool | M | 129.3 | 50.3 |
2018-07-20 | Wool | XXL | 173 | 69 |
2018-07-23 | Leather | XS | 182.3 | 38.1 |
2018-07-23 | Wool | XXL | 135.6 | 70.8 |
2018-07-23 | Wool | S | 121 | 44 |
2018-07-23 | Leather | L | 249.8 | 57.6 |
2018-07-24 | Cotton | S | 66.1 | 22.3 |
2018-07-24 | Cotton | L | 81 | 28 |
2018-07-24 | Cotton | S | 70.3 | 22.3 |
2018-07-24 | Wool | XS | 113 | 39 |
2018-07-25 | Cotton | XS | 74.3 | 18.1 |
2018-07-25 | Tweed | M | 230.6 | 76.8 |
2018-07-26 | Silk | XL | 291 | 130 |
2018-07-26 | Cotton | L | 84.8 | 27.6 |
2018-07-26 | Wool | XS | 114.1 | 38.3 |
2018-07-26 | Leather | S | 110 | 47 |
2018-07-27 | Cotton | XS | 53.3 | 18.3 |
2018-07-30 | Wool | XS | 107 | 38 |
2018-07-31 | Leather | XS | 193.3 | 37.1 |
2018-07-31 | Cotton | XS | 73.6 | 18.8 |
2018-08-01 | Leather | S | 222 | 44 |
2018-08-01 | Silk | XL | 532.8 | 127.6 |
2018-08-02 | Silk | S | 170.1 | 96.3 |
2018-08-02 | Wool | XXL | 189 | 71 |
2018-08-03 | Cotton | XXL | 95.3 | 33.3 |
2018-08-06 | Silk | M | 499 | 103 |
2018-08-07 | Leather | L | 213.3 | 55.1 |
Task - Price consistency
Using Excel, analyse the historical data you have available, and
create a spreadsheet that allows a member
of the Jacket Frenzy team to enter the jacket material and size,
and gives a quote amount.
Ensure that you include enough text and formatting to make your
spreadsheet usable by a member of the
Jacket Frenzy team (or by a University lecturer).
You may base your quote amount either on historical averages, or to
ensure that Jacket Frenzy makes a
profit.
Validate your quoting approach by applying your formula to
historical data.
Justify your approach in word file (approximately 150 words), and
attach your Excel file
Helper | Material | Size | Avg Quote | ||||
CottonL | Cotton | L | 82.51 | Material | Silk | ||
CottonM | Cotton | M | 75.28 | Size | M | ||
CottonS | Cotton | S | 71.00 | Quote | 367.80 | VLOOKUP(G2&G3,A1:D26,4,0) | |
CottonXL | Cotton | XL | 84.90 | ||||
CottonXS | Cotton | XS | 65.98 | ||||
CottonXXL | Cotton | XXL | 99.77 | ||||
LeatherL | Leather | L | 223.03 | ||||
LeatherS | Leather | S | 166.00 | ||||
LeatherXL | Leather | XL | 247.60 | ||||
LeatherXS | Leather | XS | 178.53 | ||||
LeatherXXL | Leather | XXL | 231.00 | ||||
SilkM | Silk | M | 367.80 | ||||
SilkS | Silk | S | 306.00 | ||||
SilkXL | Silk | XL | 411.90 | ||||
TweedM | Tweed | M | 230.60 | ||||
TweedS | Tweed | S | 276.30 | ||||
TweedXL | Tweed | XL | 209.77 | ||||
TweedXS | Tweed | XS | 211.67 | ||||
TweedXXL | Tweed | XXL | 257.00 | ||||
WoolL | Wool | L | 112.12 | ||||
WoolM | Wool | M | 122.53 | ||||
WoolS | Wool | S | 135.78 | ||||
WoolXL | Wool | XL | 139.87 | ||||
WoolXS | Wool | XS | 104.98 | ||||
WoolXXL | Wool | XXL | 154.15 |
Explanation to prepare Excel:
The given above data file is analysed and a PIVOT table can be prepared with Rows containing Material and Size and the Values containing average of Quotes.
Next we can paste special the Pivot Table, use a concatenate formula for column material and size, to prepare a helper column and use the above Vlookup formula in a cell to get the quote, the user needs to enter the material and size and will the formula cell will return the Quote.
In the above excel the material and size needs to be entered or inputed and the Quote will be returned by the spreasheet.
Jacket Frenzy is a small clothing manufacturer, specializing in creating custom, one-of-a-kind jackets. They exclusively sell...
Scenario details Jacket Frenzy is a small clothing manufacturer, specializing in creating custom, one-of-a-kind jackets. They exclusively sell their product through their online store. Jacket Frenzy is run by a team of three staff members: April, Beatrice, and Claudia. April and Beatrice work together to manufacture jackets. Claudia manages orders, sales and delivery. Team hours Most of the time, team members work the following shifts: April works 7.5 hours on Mondays, Tuesdays and Wednesdays; Beatrice works 7.5 hours on Thursdays...
Provide the syntax answers for the following script, doesn't matter what table or columns. CREATE TABLE customer (c_id NUMBER(5), c_last VARCHAR2(30), c_first VARCHAR2(30), c_mi CHAR(1), c_birthdate DATE, c_address VARCHAR2(30), c_city VARCHAR2(30), c_state CHAR(2), c_zip VARCHAR2(10), c_dphone VARCHAR2(10), c_ephone VARCHAR2(10), c_userid VARCHAR2(50), c_password VARCHAR2(15), CONSTRAINT customer_c_id_pk PRIMARY KEY (c_id)); CREATE TABLE order_source (os_id NUMBER(3), os_desc VARCHAR2(30), CONSTRAINT order_source_os_id_pk PRIMARY KEY(os_id)); CREATE TABLE orders (o_id NUMBER(8), o_date DATE, o_methpmt VARCHAR2(10), c_id NUMBER(5), os_id NUMBER(3), CONSTRAINT orders_o_id_pk PRIMARY KEY (o_id), CONSTRAINT orders_c_id_fk FOREIGN...