Robert Kugel's Analyst Perspectives

Until recently, dedicated consolidation software had been a sleepy category. First introduced in the 1980s as a tool designed to run on personal computers (freeing the accounting department from reliance on its IT department), offerings basically achieved feature and function parity by the next decade. The last major technology innovation—moving the software to the cloud—began in the mid-2000s. Cloud-based software reduces the cost and complexity of ownership, making dedicated software a more practical and attractive option for companies with between 500 and 2,500 workers.

We are now on the cusp of a major artificial intelligence-driven wave of innovation that will make dedicated consolidation software more compelling to an even wider set of enterprises. This will amplify an existing trend to increase adoption by finance and accounting organizations looking to boost productivity and shorten the accounting close process.

Although they seem like a single thing, almost all enterprises with 500 or more workers consist of multiple legal and management entities. Consolidation is the process of combining the financial statements of multiple entities within an organization to present the financial performance and position of the entire group as a single economic entity. All financial management systems (which may be part of a full ERP system) must be able to perform a statutory consolidation, one that presents corporate financial statements at a headquarters level using the generally accepted accounting principles of that parent company.

Built-in consolidation functionality in an ERP system is not always the best choice for an enterprise. Dedicated consolidation software is useful to corporations with even moderate corporate complexity. Most often, this is due to using ERP systems from multiple software providers. Our Next Generation ERP Benchmark Research found that 69% of enterprises with more than 1,000 employees have an ERP system from more than one software provider, and 27% have four or more.

Complications to the consolidation process arise when there are multiple legal entities, multiple currencies or intricacies in the ownership structure of its legal entities—such as partial ownership, cross holdings or joint ventures. Enterprises operating in more than one country may have to present consolidated financial statements that include the subset of entities in that jurisdiction or to a regulatory body that’s different from the headquarters. This might require using multiple standards, such as International Financial Reporting Standards (or IFRS) for a business division and US-GAAP for the parent corporation. In some cases, one or more legal entities may have to use accounting treatment and consolidation methods prescribed by regulation for that form of business, which may be defined differently depending on the location.

Dedicated software that manages the consolidation process has been around for decades, but until recently, there was very little change and, therefore, very little to comment on. However, the pandemic lockdowns forced finance and accounting executives to focus on ensuring the resiliency of their departments. Moreover, the substantial number of experienced accountants who retired between 2020-2022, especially in the U.S., has increased the need to use technology to enhance staff productivity. In turn, this shortage is causing executives to take a fresh look at software that manages the full close-consolidate-report cycle end-to-end. One important objective is to manage this portion of the accounting calendar as a controlled, repeatable process. Ventana Research asserts that by 2027, one-half of midsize and larger enterprises will use close management software to speed the close and achieve greater control of the process.

Although there are compelling reasons for enterprises to use dedicated consolidation software, over the years our benchmark research has found that 37% use it, while 27% rely on the functionality of the core financial management system. The remainder either use spreadsheets or some home-grown application. As noted, some enterprises are not especially complex and, therefore, don’t see the need for dedicated software. Some use either spreadsheets or spreadsheets in conjunction with the core ERP system to do the work, even if this choice might be less efficient or take longer to complete. Another consistent finding is that organizations replace systems at long intervals—the average age of the software is about a decade. This is changing.

Despite the maturity of the dedicated consolidation software category, I began to refocus on it a few years ago because I saw evolving business needs and technology capabilities that necessitated increased adoption. The disruptions caused by office lockdowns motivated companies to digitize more accounting tasks, while the shortage of accounting talent caused by pandemic-era retirements placed greater emphasis on using software to boost productivity. More recently, the potential of embedding AI and GenAI in consolidation software is likely to increase its adoption because it can automate and streamline repetitive actions and sequences to gain productivity and shorten the process. Among software providers, quickly and successfully enhancing the utility and performance of systems may dictate market share.

Embedded AI promises to significantly increase the speed and productivity of the consolidation by automating a considerable percentage of the rote, repetitive steps that characterize much of the statutory consolidation process. Some tasks, such as reconciliations that can be accomplished with basic matching routines (not machine learning), are already automated.

The next level of automation will include parts of the process that can only be accomplished with relatively trivial pattern recognition and machine learning. Not all numbers can be matched for a long list of reasons, so accountants use methods that require some inference and shortcuts built on systemic knowledge and experience to get the work done. A significant percentage of these techniques can be “learned” by the system and can be an inherent part of the software, refined by the practices of individual enterprises. And because AI using ML is built around statistical observations, embedded AI systems’ decision support won’t be binary. Where an even modest amount of statistical uncertainty exists about the “right” decision, conclusion or recommendation, systems can ask a human to make a choice, even providing them with prompts showing the likeliest next steps and dispatch an agent to perform the recommended series of actions. GenAI is not likely to play a significant role in the consolidation process but, for example, it can speed up the creation of routine journal entries.

AI agents have substantial potential to boost departmental productivity because the close involves tasks performed relatively infrequently: Once a month, once a quarter and once a year. Inevitably, there’s a learning curve that need not exist. Some routines aren’t invoked every close, and those where chaining together fragments eliminate almost all latency in how long it takes to complete the task. The close is almost never a smooth, step-by-step execution. There are always last-minute changes that ripple through the numbers. It’s a reasonable hypothesis to expect that eliminating latencies, measured in time between tasks, will have a noticeable and perhaps even a profound cumulative impact in shortening the consolidation process.

The rapid development and embedding of AI and GenAI capabilities in dedicated consolidation software will present buyers with a more complicated set of choices. As a rule, selection decisions are dictated first by cost considerations, then by software provider or system integrator preferences in the context of the buyer’s scalability and performance requirements. Next are system considerations, such as the headquarters ERP system provider. In an era of feature and function parity, the final choice between several packages might rest on less objective matters such as a user interface design or better congruence with the department’s process peculiarities. These assessments also usually involve multiple stakeholders with different priorities and influence on the final decision. However, over the next five years, consolidation software providers’ embedded AI capabilities are likely to advance at different rates.

 The availability of embedded AI consolidation software will accelerate demand in the market, either to replace existing on-premises systems or to provide this technology to enterprises that use spreadsheets to manage all or a significant part of the close process. In some cases, an enterprise using a cloud-based consolidation system may decide to switch providers. I strongly recommend that finance and accounting departments adopt AI-enabled consolidation software as soon as possible. The software will almost certainly increase staff productivity over the next five years and can be a catalyst to accelerate the close. Our recent Fast Close Dynamic Insights Research found that more than one-half of enterprises take more than six business days to complete the quarterly process, despite widespread agreement that the benchmark is a business week. Departments don’t have to be at the bleeding edge of technology adoption to begin the process because all software providers have a strategy to introduce AI-enabled capabilities as they are feasible and provide limited risk.

That noted, making choices based on existing versus promised innovations will not be straightforward because software providers will advance at different paces over the coming years. Promised innovations, as usual, will be realized unevenly by each provider. Departments must closely monitor the market to understand what’s available and have a roadmap for adopting AI and GenAI to assist in managing the close.

Regards,

Robert Kugel