Tips for Dealing with Bad Data

John Krautzel
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Accounting professionals are responsible for delivering top-quality data to their employers or clients. Bad accounting data often occurs when quality slips due to input errors or system issues. Accountants must often work with the data that they are given, especially if it was collected during a specific time window that has passed or is part of time-sensitive calculations. When going back and doing everything over for better data quality isn't an option, accounting professionals must deal with the bad data.

The first tool that skilled accounting professionals have for dealing with bad accounting data is the statistical model. By using averages of previous projects or accounting periods, it is possible to eliminate obvious outliers and bring data closer to expected results. Working with bad data inputs is often necessary when the errors are likely to have occurred at the initial collection point and span a specific time period. Since accountants cannot go back in time and retrain data collectors or data entry workers, they must work with the bad accounting data collected. Questionable data should be stored separately from other information and clearly marked so that it may be reevaluated to track down specific errors or make adjustments in the future.

The second common method of working with bad accounting data is to work with the reports that the data helps generate. Accounting tips often suggest that you should work with the reports themselves if you suspect data entry or collation errors. Managers rely on accountants and their accounting tips to make savvy decisions, and working with the final reports allows you to point out discrepancies and leave the decisions up to managers and owners instead of delivering reports based on accounting data reworked before calculation.

Bad data plagues experts in business and government entities. Accountants working in either the private and public sectors should strive to make prevention a major part of their work. Using the reports generated from either reworked inputs or reworked results makes it easier to illustrate the problem for employers. Government policies and business operations may be retooled to help prevent these types of errors from occurring in the future. Dealing with bad accounting data by reworking processes for the future can have excellent long-term benefits.

Bad data is a real problem for accountants in businesses of all sizes. Most accountants choose to rework inputs or results based on the type of data and confidence levels. Bad accounting data provides an excellent opportunity to troubleshoot issues and work to prevent those problems in the future.



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