Finance Benchmarking Metrics: How Does Your Department Size & Cost Compare?

In brief:

• Finance benchmarking metrics can identify opportunities to automate, streamline staffing, and increase focus on more strategic activities.
• As AI and automation accelerate, benchmarks provide an important baseline for measuring whether technology is actually improving performance.
• Not all benchmarks are created equal. Finding the proper alignment of business traits will help you effectively measure the health and quality of your operations.
• Always view benchmark data in context of the entire operational picture to set realistic targets and avoid misleading conclusions.

Leveraging finance benchmarking metrics to compare your department’s performance against your peers can be a valuable step in understanding the existing health and quality of your finance & accounting (F&A) operations. 

By benchmarking your finance department size and cost, you can uncover areas of opportunity to restructure your organization, take advantage of AI and automation, streamline headcount, and increase focus on more strategic activities. But are all benchmarks created equal? Do general industry standards reflect the specific characteristics and dynamics of your business?  

And as AI and automation become more embedded in finance operations, another question is becoming increasingly important: Are those investments actually improving the cost, productivity, and efficiency metrics that matter? 

There are many resources like the American Productivity & Quality Center (APQC) that provide data for finance function benchmarking, including accounting department size benchmarks and other critical measures segmented by company size, industry sector, revenue size, geography, public vs. private ownership, and other business characteristics. Most break down the data into levels such as Top Performer (75th percentile and above), Median Performer (50th percentile), and Bottom Performer (25th percentile and below) – aimed at helping you understand where you are today and where you can reasonably aspire to reach. 

But to utilize the benchmarking process effectively, you need to find the proper alignment of business traits. Comparisons with similar companies in the same industry can provide more meaningful insights, but differences in business models, company size, and transaction volumes must also be considered. For example, comparing a publicly traded retail organization to a privately held professional services firm is not going to present an effective measurement – reflecting vastly different operational and regulatory complexities and transaction volumes. 

Determining where you are situated compared to benchmark levels without understanding the underlying business characteristics would not be a valuable form of analysis. 

In this blog, we will help you understand how to use financial benchmarking to determine the optimal size and cost for your finance function – providing two real-world examples of how we helped companies use key financial metrics to drive greater efficiency and performance. 

Benchmarking in finance: Should your goal be Top Performer?

Most people naturally want to target the Top Performer level for their organization, but is this realistic?  

When you look at the characteristics of a Top Performer, you will likely find an organization that has standardized their business processes and systems, limited the number of variations and exceptions in their transactions, simplified their business rules, and implemented AI and automation solutions to reduce the amount of manual work. They have made significant investments in their operations, and the ROI was considered sufficient to warrant that investment. 

The performance gap can be substantial: the latest APQC data shows Top Performers maintain an operating cost that is 30-60% below their industry peer groups. They are also 3x more efficient in overall staffing of their finance functions.

Most F&A departments are happy to be “moving on up” from the tenements of Bottom Performer to the more upscale Median Performer neighborhood. Realistically, the Median Performer level is where most organizations find themselves (hence the term), and if you are not there yet, it is a great (and attainable) goal. 

If you are at the Median Performer level, then it becomes a question of ROI – is it worth investing in the technologies, process changes, and organizational restructuring needed to elevate your performance level?  Such investment decisions should consider the expected ROI. 

Technology is adding another dimension to that performance equation. AI and automation can create new opportunities to improve traditional benchmarks, but technology alone does not create Top Performer results. Achieving that level of performance typically requires standardized and optimized processes, quality data, integrated systems, skilled talent, and a finance operating model capable of supporting continuous improvement – all of which require investment.  

It can be costly and difficult to get there, so finance leaders should carefully consider their drivers, expected outcomes, and level of payback before embarking on this path. 

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AI and automation are changing the finance performance equation

It used to be enough to periodically compare financial performance against benchmarks. But as technology and operating models evolve, finance leaders need greater visibility into how their performance is changing – and to prove whether improvement initiatives are delivering the expected results. 

APQC’s expanding measure inventory reflects that shift, with 65 AI and automation measures assessing the capabilities behind performance – including automation coverage, touchless processing, Digital Worker Equivalents (DWEs), AI-assisted processing, and AI investment and ROI. 

These emerging measures complement rather than replace traditional benchmarks. A lower cost per invoice, shorter close cycle, or higher transaction volume per FTE tells you what changed; automation coverage, touchless processing, or digital worker capacity can help explain how that change was achieved. 

At the same time, traditional benchmarking establishes a baseline that helps identify where AI can have the greatest impact – and enables organizations to track performance changes over time.

For example, benchmarks for the number of full-time equivalents (FTEs) required to do the work of a finance organization are trending downward as automation picks up many of the manual tasks typically associated with these roles. Repetitive tasks like data entry, invoice processing, and accounts receivable receipt processing can now be completed with minimal human intervention.  

AI is extending that opportunity into more complex, multi-step finance activities. Emerging agentic capabilities can interpret unstructured information, identify anomalies, manage exceptions, recommend resolutions, and enable increasingly touchless processing. 

The impact is already visible in AP productivity.  

That shift coincides with automation technology becoming more accessible beyond the largest and most sophisticated finance organizations.  

But productivity tells only part of the story. Over the same period, the average AP cost per invoice across performance levels increased approximately 18% despite those productivity gains – reflecting, at least in part, the impact of rising labor costs.  

This is why finance benchmarks are most useful when viewed together. Relying on a single measure can create a misleading picture of performance.  

Technology alone is not a magic bullet for peak performance. As AI becomes more embedded in finance, the real measure of success will be whether those investments translate into better outcomes across cost, productivity, cycle time, accuracy, and workforce capacity.

Learn more about how AI is redefining finance benchmarking in our related blog.

Using finance benchmarking metrics to optimize your organization

Understand that benchmarks are data points, one part of a broader analysis that must be undertaken to clearly identify if the way your organization is structured is optimal. However, sometimes those data points are like neon signs illuminating areas of opportunity, pointing to where a focused analysis can provide details needed to solve problems. 

Consider a $1 billion healthcare organization with an accounting department of 33 people – more than double the industry Median Performer benchmark of 13.8 FTEs, according to APQC. This makes it a Bottom Performer. 

But is this an “apples-to-apples” comparison? The healthcare company maintains more than 70 clinics that generate revenue, compared to other healthcare organizations comprised of a few large hospitals. Greater geographic diversity brings additional operational and regulatory complexities, significantly higher transaction volumes, and overlapping staff at the various locations – all driving additional headcount.   

Through data collection and analysis of the healthcare company’s transaction volumes, the Auxis Grant Thornton team determined each of the 70+ clinics needed to reconcile 40-50 general ledger (GL) accounts monthly – for a total of 3,000 accounts. The regional operational structure created inconsistencies in the way accounts were structured and treated. Accounts were also reconciled manually, using Excel.   

Combined, these factors created a time-consuming, grueling process – one that stretched the month-end closing cycle to the middle of the next month.  

The Median Performer benchmark for managing GL accounts is 28 accounts per FTE. If you do the math using that benchmark, the company would need more than 100 FTEs to reconcile all its accounts monthly – considerably more people than it had in its accounting department.  

As a result, accountants were not reconciling every account every month. Considerable time was spent cleaning up issues with the unreconciled accounts, with staff generating numerous journal entries to resolve variances.  

Many errors required rework and extensive oversight. The accounting organization was spending all its time reconciling, correcting, updating, and closing – leaving no time for any type of analysis or business insights. 

So, instead of being overstaffed, was the organization actually understaffed? Clearly, the situation was more complicated than the initial benchmark suggested.  

The benchmark pointed us in the right direction, and a further, rather quick analysis helped identify areas driving the performance gap and highlighted the root causes of the issues. The solutions were readily apparent (and not that complicated): 

• Standardize the account structure and reconciliation process across all locations 
• Reduce the number of accounts reconciled monthly, focusing on the most material accounts 
• Implement an automated account reconciliation platform such as BlackLine, Trintech, and OneStream to reduce the manual work needed to manage these accounts, focusing just on variances 
• Reduce the number of journal entries created by the effort to clean up unreconciled accounts  
• Restructure and streamline the accounting organization, bringing a more structured and focused process with the ability to provide real-time quality control and oversight. 

Meeting the finance team size benchmark: what’s the impact? 

As you can see below, the organization was able to considerably reduce the number of FTEs from 33 to 14, bringing it almost directly in line with the Median Performer benchmark of 13.8 FTEs.

While the company’s complexity prevented it from becoming a Top Performer in terms of FTEs, the process and efficiency improvements that brought it to the median level are considered a big win.  

You generally don’t want to risk making too big of a jump (i.e., from Bottom Performer to Top Performer) because you don’t want to be too disruptive to your operations at once. Optimization can take time, and people need to adjust to changes.  

It’s better to gauge the impact of your initial actions and be prepared to take further steps after the operational dust has settled as you become more aligned with your benchmark targets.  

What’s the takeaway? Benchmark data by itself did not provide the answers to help this company optimize its accounting operation, but it clearly showed us where to look to optimize efforts.  

Too often, organizations can’t “see the forest for the trees” as they are so busy running on that treadmill, and they can’t take a step back to analyze what is really going on. Benchmarking can help you to see the trees, and, in particular, see which ones need to be chopped down.

Look below the surface of benchmarking in finance to find real solutions  

Sometimes benchmark data can give you a false impression of your operational performance. Always view data in context of the entire operational picture before drawing conclusions and action plans. 

Consider a $250 million property management company that operates approximately 400 residential properties across multiple geographies. Due to the nature of its business, the company manages (and pays) a large number of vendors across its properties. Its 15,000 monthly invoice volume equates to a consumer-packaged goods (CPG) or retail company with more than four times its revenue. 

On the surface, the company appears to be doing a good job with its AP function. With 9.5 FTEs, its processing productivity approaches the Top Performer range (achieving 1,500+ invoices per FTE per month), while its overall AP headcount appears to be around the Median Performer level. 

But a deeper dive into the company’s operations tells a different story.   

Actual invoice processing occurs at individual properties, where 18 administrative assistants located in the buildings receive, index, code, and enter invoices into the AP system. Since they are not dedicated AP staff, the company had excluded them from its AP headcount.  

However, an Activity Survey found they spend a considerable amount of time handling invoices, while the corporate AP team is solely focused on managing invoice exceptions and processing payments. The Activity Survey also found the decentralized structure forced 10+ members of the company’s accounting team to spend time on research, reclassification, and cleanup of errors happening at the properties such as miscoded or erroneously processed invoices that weren’t being caught by the AP team. 

In reality, the actual number of FTEs allocated to AP processing was 38, revealing a dramatically different performance picture than the surface-level benchmark suggested. 

Such great inefficiency created a ripple effect on other critical industry benchmarks as well: 

• Adding up the actual cost of all the company’s AP resources placed its cost per invoice at $17.11 – more than three times the median benchmark of $5.50 in the services industry. 
• With excessive time consumed by AP activities, the accounting team only had bandwidth to handle 15 properties per accountant, below the industry median benchmark of 20. This impacted overall productivity and property support, while hindering the team’s ability to provide operational insights, scale and grow the operation, and support onsite team members in maintaining service quality for residents.     

This is a case where a surface-level review of benchmark data would have failed to provide great insight into the company’s operational challenges. A deeper dive was needed to understand the true nature of the issues it was confronting and the “spillover” effect on other impacted areas.   
 
Starting with benchmarks gives you an idea of where things lie on the surface; it’s up to your team to then consider all angles that may be leading to a “false positive” result. 

Using finance benchmark data to drive an action plan

In the example above, “cleaning up” the AP area would improve efficiency across the entire F&A organization. But how could the company do this without incurring significant cost increases?  

Moving AP processing from the properties to the corporate AP team seemed like an easy fix. But the median benchmark shows you need about 15-16 people to process these invoices (at ~1,000 invoices processed per FTE).   

At a fully loaded cost of about $70,000 per FTE, that would result in an operating expense increase of more than $1 million. (Remember, property staff also performed other duties so you would not be replacing any of them to grow your AP team.) This was obviously untenable. 

Incorporating an automated AP processing solution with Intelligent Document Processing (IDP) enabled the company to target 70% “touchless” AP processing, leaving only 30% requiring manual inputs. As a result, the company only had to add five AP processors to handle the remaining 4,500 invoices.     

The new cost per invoice (including the cost of automation and additional AP staff): $4.94, more than 10% below the median industry benchmark of $5.50. 

More important, these improvements allowed the company to free up the equivalent of eight accounting FTEs from AP-related tasks, delivering a “soft” annual cost savings of about $1 million by eliminating the need to hire additional accountants. The company also was able to increase the number of properties per accountant to 20, the industry median benchmark! 

This real-world example reveals how benchmark data can guide an organization from identifying a performance gap to taking action and then measuring whether those actions delivered meaningful results such as cost reductions and productivity improvements.    

It also illustrates why technology success should be measured through business outcomes. The 70% touchless processing rate is meaningful because it translated into lower processing costs, greater workforce capacity, and improved productivity – not simply because more transactions were automated.  

Finance benchmarking metrics can provide valuable insights into the current state of your F&A operation and help identify areas where key operational challenges reside. This insight can support strategic decisions about where to focus improvement efforts, while establishing a baseline for measuring whether improvement initiatives are actually moving the needle.   

Benchmarks should not be used as standalone metrics to drive an efficiency program. But given the need for finance organizations to be leaner, scalable, and flexible, they can be an important part of a broader business analysis that supports better decision making, helps shape that program, and measure its outcomes. 

Turn benchmark insights into better finance performance  

Benchmarking reveals significant gaps between an organization’s current performance and its target performance level. But closing those gaps can require a combination of ongoing process optimization, organizational restructuring, AI and automation, and operating model changes. The right approach depends on what is driving the performance gap and the expected business case for improvement.  

For organizations that lack the technology or specialized expertise to make those changes, a strategic partnership can make a significant difference. By leveraging a finance and accounting outsourcing model, organizations can tap into a provider’s deep process expertise and gain access to specialized talent.  

A quality outsourcing partner can also bring standardized processes, continuous improvement capabilities, and enabling technologies that help improve performance against key finance benchmarks.   

Looking to improve the performance of your finance and accounting organization? Schedule a consultation with our finance transformation experts today! Or, visit our resource center to learn more finance transformation tips, business strategies, and success stories.    

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