The Critical Impact of Data Quality

Every time a company migrates its data from one system to another – whether from a legacy system to a new system, from an in-sourced administration to an outsourcer, or from one outsourcer to another – systemic errors are introduced into the data.

The same applies when companies merge with or acquire other firms. Virtually without exception, the two companies have different data-reporting formats, definitions and categories, resulting in numerous systemic errors as the databases are merged.

These errors only grow over time. The result? Incorrect data that can negatively impact systems, processes, financial results, pension payments and sales results – virtually all of the information that modern corporations rely upon for state and federal reporting requirements, communicating to shareholders, the media, customers, employees and retirees, and making their business processes function with maximum efficiency.

One of Loreto's traditional areas of emphasis has been defined-benefit pension plan data. Like many other areas of corporate responsibility, the management of pension funds depends upon accurate data.

For example, when pension payments are too low, they can cause serious headaches for HR or for the pension-plan administrator who must field complaints and oversee corrections. On the other hand, when the payments are too high, the company may never know about the error – meaning that it can't use the volume of complaints it receives to measure the scope of the problem. And when such excess payments are multiplied by hundreds or even thousands of such errors, it can cause substantial financial losses. Losses can stem from duplicate payments, payments that go to the wrong address, payments that go to deceased or non-existent persons, and many other otherwise undetectable errors.