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Friday, March 22, 2013
Monday, December 3, 2012
Understanding the Degree of Operating Leverage
The operating, or “fundamental,” risk of a company is the
risk a company faces because of the business it is in. For example, the profits a firm makes depend
on the demand for its goods and the costs of producing the goods, so it
inherently faces the risk that costs could increase and/or demand could fall,
which would affect the profits of the firm.
Operating risks result from the investment decision of the firm, and are separate from financial
risk, which results from the financing
decision. One way to measure
operating risk is through activity
analysis, which studies how the operating activities of the company
generate profits, see below.
Fundamental Risk and
Beta
A different measure
of risk, beta, is based on stock returns.
It measures the sensitivity of a stock’s return to the market as a
whole. In its pure form, it does not pay
attention to fundamentals. However,
people have developed the concept of a “fundamental beta” which takes into
account information such as operating and financial risk. One argument in favor of this approach is
that beta typically is calculated using historical data, while fundamentals
provide information about the future performance of a firm.
So one question you can ask is whether beta reflects
fundamental risk. For example, do firms
with high operating risk have high betas, or more broadly, if there is a
systematic relationship between beta and fundamentals.
Operating Risk
Operating risk in
“Activity Analysis” is measured by the “Degree of Operating Leverage.” The ideas underlying this measure can be
developed as follows. From the firm’s
financial statements we can first estimate a firm’s Earnings Before Interest
and Taxes (EBIT) which provides a measure of the operating income for a firm. One measure of operating risk is the Degree
of Operating Leverage (DOL) defined by
Degree of Operating
Leverage (DOL) = % Change EBIT/% Change in sales revenue
This definition is related to the concept of elasticity in economics: it measures the
percentage change of one variable due to a percentage change in another. So here, operating risk is defined as the elasticity
of a firm’s EBIT to Sales Revenue.
Why is this measure of operating risk? Because it tells you how sensitive profits
are to changes in sales. If they are
very sensitive, then it could mean, for example, that the firm has high fixed
costs, so it is more exposed to a downturn in sales than a firm with low fixed
costs. Numerically, consider a firm that
has a fixed cost of $50m and then a variable cost of $1 per unit. If it sells 100m units at $2 each, it has a
profit of $50m (200m in revenue minus 100m in variable costs minus 50m in fixed
costs). If sales drop by 10% to 90m
units, profit drops to 180m – 90m – 50m = 40m, which is a 20% drop in
profit. If the same firm had zero fixed
costs, its profit would drop by 10% if sales dropped by 10%.
In the lesson, you will learn how to calculate the DOL for
Wal-Mart and Intel. Then, you will
compare them to the betas, and see if a higher DOL is associated with a higher
beta. At the end of the lesson is an
exercise that lets you conduct a more systematic analysis of the relationship
between operating risk and beta.
To access the lesson, from the FSA module, simply select it
from the Lessons menu:
Taming Big Data with the Interactive Financial Statement Analysis Module
Big data refers to the amount of data a typical organization
now processes to solve business problems.
This rapidly developing area is reshaping approaches to business
education as has recently been discussed in Business Education Journals such as
BizEd (November/December 2012). For
example, in their lead article “Where Technology meets Business” it was
observed that:
“… in today’s world,
where everyone can buy databases, technology alone isn’t a competitive
advantage. The advantage rests in how an
organization uses it. …. Tomorrow’s CEOs won’t need to connect wires and
switches---but they will need to
connect the dots…”
The Interactive Financial Statement Analysis (IFSA) is
designed to meet these demands. First, it
provides immediate access to big data.
This data includes the interactive financial reports now required by the
SEC from publicly listed corporations. Second,
IFSA combines big data with technology to provide the conceptual framework
necessary for connecting the dots. This conceptual
framework steps you through a structured and visual approach to understanding a
company from the financial data it generates.
These steps include:
·
Analyzing financial reports including the business
model and strategy
·
Common Size Analysis (horizontal and vertical
analysis)
·
Analyzing Profitability
·
Analyzing Operations
·
Analyzing Risk
·
Analyzing Reporting Quality
·
Analyzing price ratios to connect the dots
between fundamentals and returns
Today’s business environment places increasing demands on
the user to combine business analytics with big data because the sheer
complexity of the problem forces a user to understand
the underlying economic drivers of the data. In the blogs on this site we illustrate how
business analytics lets you work with big data to generate increasingly finer information. For example, Understanding the Degree of
Operating Leverage blog introduces you to the problem of analyzing operating
risk. This is the risk associated with operating
leverage, measured by combining business analytics with the horizontal analysis
of a corporation’s cost behavior. The
technology lets you pull of this analysis quickly for any publicly listed
corporation and its competitors, but as the quote in the introduction asserts,
the comparative advantage is not created
from the database and the technology, but
from knowing how to use this information.
The Interactive Financial Statement Module shows you how to acquire
these skills -- by doing!
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