Data Source Differences

From time to time, many of us have found discrepancies when we have compared one data source with another. Sometimes, those differences can be considerable-sufficient to make a pronounced difference in the outcome of our stock studies depending upon which source we use. Oddly enough, data can be quite different, yet quite correct. How can this be?

Data sources or providers each have different types of clients. Each is interested in providing data to its clientele that will best suit their unique purposes. They will therefore make use of the latitude that is granted under "Generally Accepted Accounting Principles" (GAAP) that will best suit the types of clients they serve. Each of the providers offers "accurate" data; but, the way it is reported varies considerably in practice. The most important areas of difference are disclosed below.

Terms

The first consideration in understanding the differences between data sources is to distinguish between original and restated data.

Original data is as it was originally reported at the closing of the period for which the data applies.

Restated data (often referred to as "pro-forma" data) refers to data that has been retroactively altered to show what "might have been" had the company operated in the configuration it now operates; i.e., after spinning off a division or discontinuing the operation of a portion of the company. This data is an educated estimate of value to the analyst.

The second consideration is the difference between as reported and data that has been modified by the data provider.
As reported data is what the company reports at the end of a fiscal period. What may be confusing is that FASB (the Financial Accounting Standards Board - the private sector organization in charge of establishing standards of financial accounting and reporting) requires that companies alter their past reports to conform to the accounting practices that are currently imposed.
The data provider may modify data reported by a company to best suit its clientele. Two examples of modified data are "standardized" data and "normalized" data.

Standardized data has been modified by the provider to place income and expense items in common categories in order to permit meaningful comparisons between companies. Data "buried" in footnotes may be assigned to those categories as well.

Normalized data has been modified to exclude the effect of "non-recurring gains or losses"

Excluding the Effects of Non-Recurring Gains/Losses

Different professions that use data are interested in different perspectives. We, as analysts, are more interested in the "heartbeat" of a company-the financial basis for the company's earnings growth-than in the treatment of the various items that, for example, underwriters or insurers may wish to examine in order to do their work.

Thus, of importance to us are the matters of history that are relevant; and, events that have little chance of recurring are, to us, irrelevant. It is therefore desirable for us to obtain data that has deleted such items from the historical data that we study.

Under APB (Accounting Principles Board) guidelines, all companies must "break out" (report as separate items) such Extraordinary Items and/or Discontinued Operations. By definition, these items are reported "net of taxes," meaning that these items appear in the financial statements after taxes have been deducted from them. Since the separate reporting of these items is required, all data sources have the ability to provide this information; and, those that deduct these items report "Earnings from Continuing Operations, excluding Extraordinary items."

Occasionally, a special gain or loss will not meet the FASB definition of Discontinued Operation or Extraordinary Item. Such items are called "Non-recurring" or "Special" items and must be reported as part of a company's operations before taxes. You must be careful not to confuse such items with the "net of taxes" items discussed in the preceding paragraph.

Normalized data excludes the Non-recurring or Special items from net profit and earnings as though they were in the same category as Extraordinary Items; i.e., it deducts them net of taxes. This is difficult to do accurately since the analyst must apply an estimated tax rate to the pretax gain or charge. Thus, the tax rate calculated (by dividing the pre-tax income by the after-tax income) by a provider that normalizes its net income and earnings may not accurately reflect the actual tax rate the company paid. And this can sometimes represent a significant difference.

Note:

We believe that this information, compiled by Inve$tWare Corporation with the assistance of Cy Lynch, Dave Anderson, and Linda Penfold, is accurate. Our thanks also goes to Karen Von Seekamm of S&P Compustat who has also contributed to making this complex issue more understandable.

However, it was assembled from analysis of the data and does not rely upon any proprietary definitions provided by any data source. This information is subject to change should either the data change or should we receive any better information from data providers whose input we have solicited.

The following is not offered, nor should it be construed, as a recommendation for the use of any specific data source.

COMPUSTAT data is Copyrighted 1999 by The McGraw-Hill Companies, Inc. and Standard & Poor's Compustat

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