If you start a new business, create a new product, or change a business model, break-even
analysis lets you find out at what stage your company, product, or service will become
profitable. Break-even point is the stage where you have no profit yet but have no
loss already. However, there are many preceding and following stages important for the
investor. The investor wants to know not only how quickly the initial investments will pay off,
and extra income will be received, but also how quickly the normal profit and the economic profit
will be earned.
A revenue the company generates from selling the products or providing the services should cover the
fixed costs, variable costs, and leave a contribution margin. The point where the total operating
margin (the difference between the price of the product or service and the variable costs per item
or customer) covers the fixed costs is called a break-even point.
Excel pie charts are useful to display fractions of a whole by splitting a circle into
sections. Each section looks like a slice of a pie and represents a category. Such
a layout makes it easy to observe relationships between parts, but the smaller becomes
the slice (less than 10%) – the harder becomes to estimate it visually.
Pie and bar charts greatly simplify the understanding of percentages distribution for
one categorical variable but fail to build a meaningful representation of two and more
variables. A quite recent innovation in data visualization real is the Mosaic plot,
which helps to grasp the correlations within marketing, sales, and other financial data.
You will not find this chart among Excel standard charts, but you can build one.
The distribution of market shares or stocks of the investment portfolio often is illustrated
by pie or doughnut charts. The illustration of multi-market shares and multiple investment
portfolios calls for different approaches. The Marimekko chart (also known as
Mekko chart, or mosaic plot) comes to the rescue.
A Heatmap or Heat Map chart looks like a table, which cells colors
depend on the cell value. These charts are popular in biology, web and other analytics,
geography, etc. Tabular data transformation for time series data projects one-dimensional
data into two-dimensional time matrices, which simplify frequent pattern analysis.