Using Data Visualization for Budgeting

DA$25\mathrm{.}2$ Data visualization can be used to analyze seasonality is sales.

Seasonality of sales can have a big impact on budgeting. Think of when people are more likely to buy cars. Data for Honda's worldwide unit sales from January $2018$ through December $2019$ are presented here.

Date

Jan$-18$

Feb$-18$

Mar$-18$

Apr$-18$

May$-18$

Jun$-18$

Jul$-18$

Aug$-18$

Sep$-18$

Oct$-18$

Nov$-18$

Dec$-18$

Jan$-19$

Feb$-19$

Mar$-19$

Apr$-19$

May$-19$

Jun$-19$

Jul$-19$

Aug$-19$

Sep$-19$

Oct$-19$

Nov$-19$

Dec$-19$

Data Set $1$

Worldwide

Total Unit

Sales

$474,030$

$407,870$

$484,955$

$429,250$

$435,838$

$449,394$

$421,050$

$418,546$

$441,930$

$479,680$

$492,757$

$421,713$

$476,794$

$391,060$

$479,608$

$443,654$

$460,163$

$440,896$

$429,636$

$416,138$

$430,196$

$428,502$

$410,944$

$363,004$

Data for Honda worldwide unit sales from January $2013$ through February $2020$ are presented here.

Date

January

February

March

April May

June

July

August

September

October

November

December

$2013$

$342,808$

$328,298$

$357,437$

$354,715$

$347,682$

$339,881$

$338,933$

$339,930$

$382,757$

$419,224$

$398,227$

$348,488$

$2014$v

$378,817$

$352,824$

$401,607$

$384,411$

$380,466$

$389,381$

$363,497$

$343,542$

$390,267$

$402,627$

$371,259$

$355,071$

Data Set $2$

$2015$

$2016$

$363,155$

$404,259$

$306,107$

$396,470$

$398,915$

$455,362$

$379,052$

$403,742$

$355,932$

$398,075$

$394,647$

$425,303$

$389,347$

$372,422$

$358,282$

$403,487$

$394,816$

$449,591$

$413,777$

$410,306$

$422,143$

$458,822$

$379\mathrm{.}502$

$409,587$

$2017$

$412,713$

$416,614$

$487,323$

$396,758$

$427,046$

$446,392$

$397,135$

$434,399$

$455,229$

$452,930$

$481,869$

$428\mathrm{.}434$

$2018$

$474,030$

$407,870$

$484,955$

$429,250$

$435,838$

$449,394$

$421,050$

$418,546$

$441,930$

$479,680$

$492,757$

$421,713$

$2019$

$476,794$

$391,060$

$479,608$

$443,654$

$460,163$

$440,896$

$429,636$

$416,138$

$430,196$

$428,502$

$410,944$

$363,004$

$2020$

$385,750$

$289,255$

Instructions

There are four parts to this problem. Use Excel or the visualization software of your or your instructor's choice to perform the following:

$$List the months you think would experience higher and lower sales on average for worldwide sales. Explain your choices. What factors do you think may influence sales in a particular month?

$$Using data set $1,$ create a line chart with total worldwide unit sales for all months in $2018$ and $2019$ to see the seasonality on the y$-$axis and months on the x$-$axis. Include a descriptive chart title and labeled vertical axis. Ensure the y$-$axis dates are properly formatted. Designate a lower bound of $300,000$ and an upper bound of $550,000$ unit sales on the y$-$axis. What seasonality do you see?

$$Using data set $2,$ create a second line chart with unit worldwide sales by month for each year except $2020$ to visualize the seasonality on the y$-$axis and months on the x$-$axis. Include a descriptive chart title and labeled vertical axis. Designate a lower bound of $300,000$ and an upper bound of $550,000$ unit sales on the y$-$axis. Does this chart change your perspective on seasonality, or do the years look similar? Explain the seasonality patter.

$$What are the implications of seasonality on budgeting and production?