Worldscope Database Datatype Definitions Guide

Data Quality
Analyst Training
Automated Testing
Supervision and Auditing
Issue 6
Introduction to Worldscope
At Worldscope, quality assurance begins with the recruitment of multilingual corporate
data analysts, generally with accounting or financial academic qualifications. About
twenty-five major languages are represented within Worldscope, either by native
speakers or fluent non-native speakers. Worldscope analysts undergo extensive and
detailed training before being allowed to make any meaningful contribution to the
updating and analysis process. A further period of three to six months is spent in onthe-job
training under supervision. Detailed country-specific accounting and financial
practices documentation has been developed to assist Worldscope data analysts in
their understanding of international accounting and reporting practices. These
manuals define each discrete database item in considerable detail, so that
information is interpreted accurately and consistently throughout all countries across
all analysts.
Every piece of information entered into the database is subjected to a rigorous series
of 2,300 computerized balance, magnitude, correlation and alpha tests, many of
which are industry or country specific.
1. Balance tests check that formulas which should theoretically add up actually
do. e.g. Total Assets (Field 02999) = Total Liabilities & Shareholders' Equity
(Field 03999), or Operating Income (Field 01250) = Net Sales or Revenues
(Field 01001) - Operating Expenses (Field 01249).
2. Magnitude tests compare data items in the current fiscal period with the
same items for prior periods, and query items which exceed predetermined
variances, e.g. Net Sales or Revenues (Field 01001) in the current year
should be within a range of 100% to 125% of the prior year's figure.
3. Correlation tests are similar, but examine the relationships between
appropriate data items in the same period, e.g. profitability and leverage
ratios, for apparent outliers.
4. Alpha tests check the validity of alphanumeric (textual) data, e.g. checks for
correct date formats, valid industry codes and correct field lengths.
Where these tests fail, analysts must recheck and if necessary make corrections. No
information is allowed onto the database if any failed tests remain unresolved.
When data for any company is updated, the computer automatically generates a
report for that company, listing the last five years of historical information, including
the year that has just been updated. This is reviewed by the analyst's group leader for
consistency and accuracy. The group leader must be satisfied that errors have been
corrected before 'signing-off' on that company.
All quality is monitored and controlled by a team of auditors. This department is
charged with the task of examining and rechecking in great detail a random sample of
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