Perspectives

January 2004

Beyond Elevator Analysis

By Brian Hamilton

Many bankers use the uncomplimentary term “elevator analysis” to describe how some analysts discuss companies: “This ratio is up, that ratio is down; this metric is up, that metric is down.” Elevator analysis focuses on how metrics change from one period to another rather than on what the changes mean. Moreover, it is a habit of looking at many different components rather than focusing on the important ones, or of misguidedly generalizing about metrics across industries or industry segments.

Net Margin

The margin of net operating income is probably the metric that most accurately reflects performance. This number is calculated as earnings before interest, taxes, depreciation, and amortization (EBITDA), divided by sales. Essentially, the ratio indicates how many cents of profit the company is earning from each dollar of sales it generates from operations. This ratio is important because it shows management’s effectiveness at watching the costs of the business against its sales. In addition, the net margin gives managers good insight into how they can grow a company. Typically, companies are most efficient when operating at particular sales levels (sometimes called relevant ranges). For example, pharmaceutical companies need a large volume of sales to be profitable. Consequently, a manager’s key job is to drive sales as much as possible during the earlier stages of growth.

Bakeries are another interesting example, because they tend to lose or gain efficiency as they grow. From $0 to $1 million in sales, the average net margin of retail bakeries is 4.4% (Robert Morris Associates’ 2001 survey). Retail bakeries with between $1 and $5 million in sales earn a net margin of 7.8 %. When a retail bakery business’ annual sales surpass $10 million, however, the average net margin falls to 6.0%, and once sales grow to over $25 million, the net margin average drops to 3.8%. This means managers need to plan expenditures accordingly as they grow their business within these sales ranges. The most profitable operating range is $1 to $5 million. Margins (and cash) would probably be most squeezed when companies reach $25 million in sales.

Although other industries follow the same pattern as bakeries (margins get smaller as companies get larger), there are too many exceptions to generalize. Reviewing the net margin shows at what sales level the company would be most efficient, at least in general within certain industry categories. Also, there is no better long-term indicator of a company’s cash flow than its net margin. While balance sheet transactions do have a major effect on short-term cash flow, the net operating margin indicates how much money the company generates from its core activities.

Many people want to know a specific rule of thumb that would indicate a healthy net margin of any company in a given industry. Giving an across-the-board number is difficult, however, because of slight variations in optimal healthy net margins across certain industries. Yet, a net margin above zero is a good starting point for companies that are profitable in operations versus those that are unprofitable. This may seem obvious, but the point is not trivial. According to Multex, a Reuters company, in April 2003, 49% of publicly traded firms were losing money. This interesting statistic is reflected in the poor overall performance of the equity markets in the past several years. Profit performance will always be the largest driver of prices in equity markets.

Growth of Resources Against Growth of Profits and Sales

This series of metrics is more difficult to calculate, but important. Finance professionals should remember that managers have only a few resources at their disposal: assets (they can buy them), people (they can hire them), and debt (they can borrow money). On the other side, these resources can help generate only two positive important events: increased sales or increased profits (by increasing sales or decreasing costs). How asset and debt levels change in conjunction with sales and profits must be watched carefully. Often no one, even finance professionals, monitors the relation of these items until it is too late. In the case of assets, there is a direct relationship between this dynamic and return on assets (ROA) and return on equity (ROE).

Some people like to compare the rate of growth of good things (sales or profits) to the rate of growth of bad (assets or debt). The general formula can be expressed as follows:

% Change of Net Profit (or Sales) Since Last Period
% Change in Assets (or Liabilities) Since Last Period

This involves calculating the percentage growth in profits (or sales) divided by the percentage change in the resource. This will show how a change in the denominator (the bad thing) drives a change in the numerator (the good thing). A value greater than 1 would indicate that a change in the denominator is affecting the numerator/profits by even a greater rate, which would be a positive result.

Although interpreting this ratio can be confusing when the denominator is negative (assets or debt go down), the dynamic is worth following. The analy-
tical method is helpful because it can be applied to monthly, quarterly, yearly, or even historical data.

Example

The XYZ Company had net profits after taxes of $100 in 2003. Its total asset base is $1,000. During 2004, net profits grow to $125, a 25% increase, and its asset base grows to $1,100, a 10% increase. In the formula, the increase of net profits (25%) is divided by the increase of assets (10%), for a ratio of 2.5. Therefore, every dollar invested in assets returned $2.50 in net profits. Notice that ROA has increased as well, from 10% in 2003 ($100/$1,000) to 11.33% in 2004 ($125/$1,100). The point is to track how management decisions on using resources affects profits over time. This type of analysis can be used with any resource available to managers (e.g., fixed assets, inventory, or people). Sometimes, however, the two factors are not always related, and the change in profits is the result of something that did not happen in the denominator. Basically, using this tool requires watching for false positives and false negatives. For example, if a company does not buy any fixed assets for the period, the formula will yield an answer of infinity. Although this is a good result, fixed assets may have had no real effect on profitability at all. Therefore, even though the formula helps track important trends, one still must know what is going on in the business.

This formula is best applied when a company is buying bad things (increasing debt or assets), to see the effect of such decisions on good things (increasing sales and profits). This technique can be used as a way to catch early negative trends before they result in poor overall economic performance, such as when the company’s acquisitions are outstripping its profit growth.

Some finance professionals will argue that sales are not always a good thing. For example, because sales affect cash flow, increasing them can decrease cash flow in the short run. In addition, an increase in sales does not always mean an increase in profits. Both sales and profits need to be examined in relation to how managers choose to expend resources, so the economics of the company can be better understood. In this way, the technique here is useful in evaluating multiple resources and results.

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