Accuracy in disclosure data

Accuracy in disclosure data
June 25, 2014

Pretty good isn't good enough when it comes to the pieces of data contained in the footnotes of your disclosures—they have to be accurate.

Think back to where the information for your disclosures comes from. Do you trust your data, or are you a part of the 72% of CFOs who don't trust their numbers?1

Knowledge workers waste up to fifty percent of their time hunting for data, identifying and correcting errors, and seeking confirmatory sources for data they do not trust.2 The potential for error is hard to eliminate. Structured data is difficult to design, develop, and implement in an environment that can capture all of the information needed by your organization.

Getting all the information you need can be challenging. Your ERP, general ledger (GL), and other data systems don’t capture everything you need, and it’s up to you to track down the missing pieces from unstructured data sources. Unstructured data can take many forms, and it’s information that is stored on local workstations, in Excel® files and PDFs—even in file cabinets.

Today you have to manually gather all this missing information from subsidiaries, subject matter experts, regions, business units, and numerous other contributors. After you repackage it, this number ends up in your filings and other high-level reports. But think, are you one 100% confident in the accuracy of this number?

Don't be part of the 72%. Follow your numbers and see what improvements can be made.


1. On The Pulse: Information Security Risk in American Business." (2013). Stroz Friedberg. Retrieved from

2. Redman, T. "Data's Credibility Problem." (2013). Harvard Business Review. Retrieved from

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Mike Sellberg

About the author

Mike Sellberg is Executive Vice President and Chief Product Officer at Workiva. He is the former EVP and CTO at iMed Studios and the former Divisional General Manager at Engineering Animation, Inc.