Data Analysis Software Brings Value for ASC 606 Compliance


Recognizing revenue under ASC 606 for a large population of customer contracts presents challenges for companies when combining multiple orders into a single contract, determining stand-alone selling price, allocating transaction price to performance obligations and recognize revenue when performance obligations are satisfied. These situations pose additional challenges when using spreadsheets versus data analysis software, which can 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. Besides the higher risk of errors, there are other areas where spreadsheets do not provide enough functionality to ensure compliance with ASC 606.

Data cleaning and aggregation. There is an inherent complexity in running reports from multiple data sources and then preparing to accumulate the data into a single source file. Specifically, customer contracts can be collected in a cloud-hosted sales/CRM platform, in an accounting/ERP platform, or even in an in-house platform/database. Extracting data from all these platforms is a considerable challenge. If the same contracts are captured across multiple platforms, there is no single source of truth system, resulting in additional efforts to eliminate data ambiguity and ensure that all contract data is unique, complete and accurate.
Configurable rules and patterns. The spreadsheet functionality is not capable of capturing all complex use cases that accurately describe performance obligations. It is necessary to create complex formulas to recognize revenue for different permutations of terms in customer contracts, for example, contracts with upfront payment versus monthly payment terms or stand-alone selling prices changing over the period reporting.
Flexible data models and implementation of complex calculations. Spreadsheet software lacks the capabilities to easily create formulas to calculate contract assets and liabilities for each contract, including the short-term and long-term portions.
Ability to easily refresh data and add new datasets. Once the spreadsheet is created, it takes more effort to make changes to the file if there are additional contract terms.
Automate the simulation of audit processes. With a spreadsheet, it is difficult to verify data in reports to data sources and verify the completeness and accuracy of spreadsheets. It is expected that once the revenue recognition process is complete, random samples of data records will be audited and reviewed to ensure compliance with ASC 606.

Benefits of Using Data Analytics

Spreadsheets are generally excellent tools for storing and displaying a relatively small amount of data and provide basic functionality for manipulating and organizing data. However, the use of data analysis tools offers advanced features for extracting, processing and analyzing large volumes of data. Data analytics platforms reduce implementation time, provide a variety of data preparation methods, and generate solutions that are much more flexible than spreadsheets in order to comply with ASC 606. Using data analytics has several other benefits.

Extraction, transformation and loading capabilities. Advanced functionality to import and process data from various platforms and transform it to identify performance obligations.
Advanced data aggregation. Accumulate multiple purchase orders that need to be combined into a single contract.
Flexible data mappings. Analyze contract prices to help evaluate and close on stand-alone selling prices.
Automate allocation methods and assumptions. Allocate transaction price to performance obligations and recognize revenue using the appropriate measure of completion.
Manage complexities that ERP accounting software can’t solve. Accounting software such as Oracle NetSuite, Microsoft Dynamics 365, or Intuit QuickBooks provide built-in or third-party modules to meet ASC 606 compliance. However, these modules are unable to capture complex performance obligations and incorporate data from other platforms, for example, the CRM system.
Ability to forecast revenues. As an additional step in the ASC 606 process, it is very important to be able to derive revenue forecasts with recognized and predicted values ​​across multiple revenue source data. The analysis tools provide several statistical methods of forecasting, unlike traditional spreadsheet software.

Best practices for data analysis software tools

When using data analysis software tools, several practices ensure that the full benefits of the solution are realized.

Combine skills with software. Blindly using low-code or no-code data analysis 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 that the ASC 606 technical team have a deep understanding of how analytics platforms work and have the software skills to develop custom solutions, as revenue recognition engagements are unique due to the complexity of the data sets. of entry.
Pair experienced accountants with data analytics professionals. It’s not enough to have a great data team or a top accounting team to complete an ASC 606 compliance project. You also need collaboration between people who understand ASC 606 and people with a background in data engineering.
Build audit simulation tools. Output files should be carefully tested for any inaccuracies. It is critical that the data team build statistical sampling software modules that simulate the audit process and confirm that ASC 606 rules are implemented as intended.

Benefits of Data Analytics Outsourcing

One of the main advantages of using a third-party vendor for the technical accounting aspects of the ASC 606 and for data analysis is the knowledge that they have significant expertise with the ASC 606. They will use also best practices as much as possible during the process. Using a third-party specialist also helps finance departments by reducing workloads to meet financial reporting deadlines, increasing the likelihood of accurate revenue recognition under ASC 606, and reducing audit risk.

Companies with large customer contract populations may consider complying with ASC 606 internally, as it may be considered more cost effective. This may or may not be true, as audit costs could increase in addition to a potential cost increase due to increased time, effort, and strain on internal resources.

Selecting the right vendor is part of the puzzle to successfully using data analytics to comply with ASC 606. Companies should consider the following when choosing a vendor:

  1. Does the supplier have significant technical knowledge of ASC 606 accounting and data analysis capabilities?
  2. Does the supplier have the current capacity to meet deadlines?
  3. Will the project manager maintain a high level of involvement in the project to ensure high quality and timely deliverables?

When used properly, data analytics can help ensure a company’s compliance with ASC 606 while saving money and reducing the headaches associated with managing a large volume of data. consumer contracts in a simple spreadsheet.

This article does not necessarily reflect the views of the Bureau of National Affairs, Inc., publisher of Bloomberg Law and Bloomberg Tax, or its owners.

Author Information

Brad Burch is Managing Director of the Accounting & Reporting Advisory practice at Stout. He advises public and private clients in a wide range of industries on complex technical accounting and financial reporting matters, including initial public offerings.

Fotis Konstantinidis is Managing Director at Stout, leading the Digital & Data Analytics practice. He began his career as a brain researcher and has held leadership positions delivering AI-based products and services at McKinsey & Co., Accenture, Visa, and CO-OP Financial Services.

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