Recognizing revenue under ASC 606 for a large population of customer contracts presents challenges for companies when combining multiple orders into one contract, determining standalone selling price, allocating the transaction price to the performance obligations, and recognizing revenue as performance obligations are satisfied. These situations prompt further challenges when using spreadsheets compared to data analytics software, which may increase efficiency and accuracy while reducing time and costs.
Disadvantages of Spreadsheets
Using spreadsheets is much more manual than using data analytics and increases the effort to comply with ASC 606. In addition to the higher risk of errors, there are other areas where spreadsheets do not provide sufficient functionality to ensure ASC 606 compliance.
Data cleaning and aggregation. There is inherent complexity in running reports from multiple data sources and then preparing the accumulation of the data into a single source file. More specifically, the customer contracts may be collected in a cloud-hosted, sales/CRM platform, in an accounting/ERP platform, or even in a home-grown platform/database. Extracting data from all of these platforms poses a considerable challenge. If the same contracts are captured in more than one platform, there is no single source of truth system, resulting in additional effort to eliminate data ambiguity and ensure that all contract data is unique, complete, and accurate.
Configurable rules and templates. Spreadsheet functionality is not capable of capturing all complex use cases that accurately describe performance obligations. It’s necessary to create complex formulas to recognize revenue for different permutation of terms in the customer contracts—for example, contracts with payment upfront versus monthly payment terms or standalone selling prices changing over the reporting period.
Flexible data models and implementation of complex calculations. Spreadsheet software lacks the capabilities for easy creation of formulas to calculate contract assets and contract liabilities for each contract, including short-term and long-term portions.
Ability to readily refresh data and add new data sets. Once the spreadsheet is created, it takes more effort to make changes to the file if there are additional contract terms.
Automate audit process simulation. With a spreadsheet, it is challenging to audit the data in the reports back to the data sources and audit the completeness and accuracy of the spreadsheets. It is expected that after the revenue recognition process is completed, random samples of data records will be audited and reviewed to ensure ASC 606 compliance.
Advantages of Using Data Analytics
Spreadsheets are generally excellent tools for storing and viewing a relatively small amount of data and offer basic functionality for manipulating and organizing data. However, using data analytics tools provides advanced capabilities for data extraction, processing, and analyzing large volumes of data. Data analytics platforms reduce implementation time, provide a variety of data preparation methods, and generate far more flexible solutions than spreadsheets in order to comply with ASC 606. There are several other advantages of using data analytics.
Extract, transform, load capabilities. Advanced functionality to import and process data from various platforms and transform them to identify performance obligations.
Advanced data aggregation. Accumulate multiple purchase orders that are required to be combined into a single contract.
Flexible data mapping. Analyze contractual prices to help evaluate and conclude on standalone selling prices.
Automate allocation methods and assumptions. Allocate the transaction price to performance obligations and recognize revenue using the appropriate measure of progress.
Handle complexities that ERP accounting software can’t address. Accounting software such as Oracle NetSuite, Microsoft Dynamics 365, or Intuit QuickBooks provides built-in or third-party modules to address ASC 606 compliance. However, these modules are not able to capture complex performance obligations and incorporate data from other platforms—eg, CRM system.
Ability to forecast revenue. As an additional step in the ASC 606 process, it is very important to be able to derive revenue forecasting with recognized and forecasted values on multiple revenue source data. Analytics tools provide several statistical methods for forecasting, unlike traditional spreadsheets software.
Best Practices for Data Analytics Software Tools
When utilizing data analytics software tools, several practices will ensure that the full benefits of the solution are realized.
Combine skills with software. Blindly using low-code or no-code data analytics platforms to implement ASC 606 rules always leads to erroneous results. The best and most efficient approach always combines a team of data scientists and engineers with the right software tool. It is essential for the ASC 606 technical team to understand in depth how analytics platforms work and possess the software skills to develop custom solutions, as revenue recognition engagements are unique because of the complexities of the input datasets.
Pair experienced accountants with data analytics professionals. It’s not sufficient just to have a great data team or a top accounting team to complete an ASC 606 compliance project. You also need collaboration between individuals who understand ASC 606 and individuals with data engineering backgrounds.
Build audit simulation tools. The output files must be thoroughly tested for potential inaccuracies. It is essential for the data team to build statistical sampling software modules that simulate the audit process and confirm that ASC 606 rules are implemented as expected.
Advantages of Outsourcing Data Analytics
One of the primary advantages to using a third-party provider for the technical accounting aspects of ASC 606 and for the data analytics is the knowledge that they have significant expertise with ASC 606. They also will use the best practices as much as possible during the process. Using a third-party specialist also helps finance departments by reducing workloads to be able to meet financial reporting deadlines, increasing the likelihood of accurate revenue recognition under ASC 606 and reducing audit risk.
Companies with large populations of customer contracts may consider complying with ASC 606 in house because it can be viewed as more cost-efficient. That may or may not be true, as audit costs could increase in addition to a potential increase in costs due to an increase in time, effort, and strain on internal resources.
Selecting the right provider is part of the puzzle to successfully using data analytics to comply with ASC 606. Companies should consider the following when choosing a provider:
- Does the provider have significant ASC 606 technical accounting knowledge and data analytics capabilities?
- Does the provider have the current capacity to meet the deadlines?
- Will the project leader maintain a high level of involvement on the project to ensure high-quality and timely deliverables?
When properly utilized, data analytics can help to ensure a company’s compliance with ASC 606 while saving money and reducing the headaches associated with managing a large volume of consumer contracts in a simple spreadsheet software.
This article does not necessarily reflect the opinion of The Bureau of National Affairs, Inc., the publisher of Bloomberg Law and Bloomberg Tax, or its owners.
Brad Burch is a managing director in the Accounting & Reporting Advisory practice at Stout. He advises both public and private clients in a broad range of industries on complex technical accounting matters and financial reporting, including initial public offerings.
Fotis Konstantinidis is a managing director at Stout, leading the Digital & Data Analytics practice. He started his career as a brain researcher and held leadership positions delivering AI-driven products and services at McKinsey & Co., Accenture, Visa, and CO-OP Financial Services.
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