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Data Gathering: Trash or Treasure?

by Ed Bannen

As technology continues to rapidly change the way we make decisions, it becomes increasingly more important to have accurate and timely data. Do you have system reports that only give you half the important data that you need? How long do you spend combining reports or editing data to make it into a usable report? The practice of obtaining the key information from a large data pool and putting it into a usable format with little effort is a sorely sought after task. Audit Data Standards are an attempt at trying to standardize data streams and data output into a reliable, efficient form that can be manipulated by the user.

Haven’t heard of Audit Data Standards? It’s not surprising; it is a relatively new idea developed by the AICPA’s Assurance Services Executive Committee’s Emerging Assurance Technologies Task Force (try and say that three times fast). The main reason you may never hear about these standards is because they are currently non-authoritative, which means they lack the ability to enforce and enact uniform change across the board. However, the goal is noteworthy; seeking to increase efficiency in audits and in management’s decision making.

Often in audits, requests for information are made to management who then forward those requests to the IT department with limited further involvement from the accounting or finance department. Typically, the IT department is not familiar with what the auditors are looking for and multiple attempts have to be made to produce usable data. From the management’s perspective, data analytics and forecasting information is a tedious process with numerous opportunities for errors, whether manual or system generated.  Audit Data Standards will help to standardize the format for fields and files commonly requested for audits and other related purposes. In addition, it will offer data consistency and opportunities for more extensive analysis.

The first issuance of the Audit Data Standards includes:

  • Base Standards – includes formats for files fields, users listing, business unit listing and segments listing.
  • General Ledger Standards – information specific to GL accounts
  • Accounts Receivable Sub-ledger Standards – information specific  to AR sub-ledger

Now that we have covered the pros of these standards, it is important to understand the draw backs. First, standards can be vague in the extreme and especially difficult to understand. Second, adoption of these standards can be difficult and costly. The most important factor to evaluate when considering adoption of these Audit Data Standards is this – will the benefits of these standards out weight their cost of implementation? For most small companies, these standards will not make sense unless easily implemented. Large companies with more complex environments will benefit more from establishing standards around data output for audits and management reports.

Contact GBQ with inquiries on how your system’s data output can be improved and how you, as management, can make better decisions with more reliable data.

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