New approaches in digital finance benchmarking

By Paul Brunda, VP and Benchmarking Practice Leader, Trianz
Discover how benchmarking finance operations can drive better efficiency and productivity...

As the finance industry pushes deeper into digitalization, the quantity of statistical data is exploding. Data can be leveraged through key performance indicator (KPI) monitoring and visualized reporting, or be curated from external sources to benchmark your finance operations as well as your competitors’ capabilities.

The benchmarking process is vital as it helps assess the relative efficiency and productivity of your processes against leading competitors within your industry. Benchmarking helps to appropriately target your finance investments—revealing areas in which you lead, and areas where you fall short of the competition.

Let us explore methodologies for benchmarking finance operations, and how new technologies can increase your financial maturity level.

What are the benefits of benchmarking finance?

Financial benchmarking helps businesses define fact-based short- and long-term financial goals. It is often the case that targets are set by opinion, only for the business never to achieve them. The same applies when meeting targets too quickly, reducing foresight and dampening progress by lowering expectations.

By leveraging benchmarking for finance, enterprises can better analyze competitor successes to guide their own internal targets. This prevents disappointment when unrealistic targets are ineffective while providing sufficient challenge to motivate and drive workforce productivity.

Benchmarking finance also offers guidance around technological maturity. Modern finance software can offer functionality like artificial intelligence (AI), robotic process automation (RPA), and optical character recognition (OCR) for paper documents, to name a few. By assessing the technological maturity and comparing to competitor's finance operations, you can identify areas for improvement and drive increased productivity and operational efficiency.

Finding data for benchmarking finance

Most enterprises are unlikely to share detailed information about their finance areas, technologies, and strategies. However, Trianz—a leading US-based digital transformation consulting firm—has created the Digital Enterprise Evolution Model™ or DEEM. This allows clients to view anonymized data from its sister company Trasers, where more than 5,000+ individual companies across 20 industries have been surveyed

The model compares respondents across five DEEM stages of maturity, helping enterprises understand their current positioning and identify pathways to increase the critical role of digital maturity.

Areas of interest for benchmarking finance

Finance is an integral part of business management, encompassing supplier relationships, customer relationships, workforce management, tax, compliance, and regulatory systems.

To start, an enterprise should focus on benchmarking these key areas:

  • Gross and net profit margins – In basic terms, profit margins are determined by subtracting costs from sales revenues. Gross profit would consider the cost of producing and distributing a product against revenues generated. Net profit would include all business costs, including tax, payroll tax, sales tax, and more.

If competitors have a higher margin on equivalent products or services, this may indicate two things. First, expenditure is too high, with inefficient procurement processes and excessive overhead. Second, the prices you charge to end-consumers may be too low. 

The New York University Stern School of Business offers relevant data on average margins by industry sector, with more detailed reports showing competitors in each industry. Using data, you can determine whether you align with industry norms, exceed them, or lag behind.

  • Cost per employee – Salaries are among the most significant expenses incurred by businesses today. They include basic salary rates, payroll tax for social security, 401k contributions, and supplementary benefits like healthcare insurance—all of which contribute to Cost Per Employee (CPE).

The Bureau of Labor Statistics (BLS) offers monthly reports containing detailed CPE information, albeit with three months of reporting latency. Alternative data sources could be leveraged for near real-time responses to CPE trends in the market, but the BLS offers reliable data across a broad range of industries and career levels.

Full financial maturity - 1% of enterprises

At a technical level, the most mature finance operations rely on analytics, visualized reporting, and AI/RPA automation and orchestration.

Using analytics as an example, there are four stages of technological maturity:

  • Descriptive – In this case, the analytics tool simply describes what happened.
  • Diagnostic – Along with descriptive functions, diagnostic analytics also shows you why an event happened.
  • Predictive – Along with descriptive and diagnostic, predictive analytics tells you what might happen in the future after considering trends and current state of a system, process, or workflow.
  • Prescriptive – This is where fully mature financial operations peak. Along with descriptive, diagnostic, and predictive capability, prescriptive analytics tell you how to respond for maximal benefit. The analytics tool calculates hundreds or thousands of possible resolution pathways, prescribing an optimal solution to meet the business or technological challenge.

Prescriptive finance analytics can be considered a virtual consultant for critical financial decisions. This augments your workforce by providing always-on, real-time strategy optimization recommendations. An enterprise at this level is moving away from relying principally on the highest-paid person's opinion (HiPPO), and toward adopting a data-driven methodology for critical decision-making processes.

This article was contributed by Paul Brunda, VP and Benchmarking Practice Leader, Trianz

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