by James Ritter, Chief Financial Officer
Considering the multi-dimensional challenges CFOs are facing, establishing a roadmap to transforming the finance organization to improve visibility and efficiency would appear a difficult endeavor. Here, we outline a series of recommended steps that CFOs can take to move the needle on their journey to digital transformation in finance operations.
The role of the Finance function has fundamentally changed in the past decade. Finance organizations have evolved from a back-office reporting function to a strategic advisory role to the CEO. In fact, more than 50 percent of the CFO’s time is now spent on activities that fall firmly outside the traditional role of accounting and focused more on risk mitigation, compliance, and organizational transformation.
To support this transition, Chief Financial Officers (CFOs) need greater visibility than ever into finance operations—cash flow and working capital allocation, financial forecasting, internal and external controls, and strengthening vendor relationships.
Accounts payable (AP) automation is an essential tool in providing this visibility. Realizing efficiency gains in finance operations, such as straight-through processing of invoices, empowers finance organizations to reallocate scarce resources to higher value activities. McKinsey research found that best-in-class finance organizations spend 19 percent more of their resources on higher value strategic activities.
While many organizations have already improved efficiency in their transactional functions such as accounts payable, there remains much room for growth and expansion. Research from the Institute of Finance & Management (IOFM) in 2022 found that more than 75 percent of AP teams report processing more invoices in the most recent quarter (up from 66 percent in the prior two quarters), and 80 percent report an increase in invoice spend, contributing to significant increases in invoice processing transaction costs.
So even today, accounts payable automation continues to represent significant opportunities for efficiency gains. But AP automation is just one dimension of what concerns finance teams today. What else is keeping CFOs up at night?
Considering the multi-dimensional challenges CFOs are facing, establishing a roadmap to transforming the finance organization to improve visibility and efficiency would appear a difficult endeavor. Here, we outline a series of recommended steps that CFOs can take to move the needle on their journey to digital transformation in finance operations.
The steps outlined above can be achieved with investment in two automation technologies that provide the visibility needed to effect significant change in finance: process mining and intelligent document processing.
Think of process mining as a first step in diagnosing inefficiencies in finance processes and enabling you to make data-driven decisions for process optimization. It’s kind of an x-ray of your process data that captures your processes and their variations.
Process mining can help you gain granular visibility into your finance processes by enabling you to visualize how they behave and develop suitable measures for optimization. You can continuously monitor whether your measures are effective and react quickly to changes by improving them. As Gartner has found, CFOs are now investing in process mining technologies as a cornerstone for their data-driven decisions related to finance process optimization:
Finance processes are complex, exception-heavy, and reliant on judgment and subject-matter expertise.
…CFOs are turning to a suite of complementary efficiency technologies, such as process mining, which will remain a future driver of growth for robotic process automation (RPA) in the coming years.
Process mining helps you to answer the following questions:
With the data to support the answers to those questions, the next step entails making data-driven decisions about automation opportunities, such as investing in more advanced intelligent document processing that improves efficiency and throughput in processing large volumes of invoices and extracts not only invoice header information but complex line items. A low-code / no-code intelligent document processing service can enable your AP staff to access more AI and machine learning without coding.
For example, using a low-code / no-code platform of intelligent document services that are delivered as “skills” enables staff with no coding expertise to apply AI to understand documents in a fast and simple way. Business users can access a set of out-of-the-box, pretrained AI skills that form the bases for simplifying and scaling AP automation processes.
First, the solution digitizes the invoices, analyzing and perfecting their quality, resulting in high extraction and recognition accuracy for line items and tables on invoices. It uses advanced AI to classify documents regardless of their structure and variations, such as invoices, POs, expense reports, etc. Then, it extracts invoice data and turns it into structured and meaningful information that business users can analyze and use to make decisions. No coding, no training, no expertise needed to use these pretrained document skills. Drag, drop, and deploy into your AP application.
When these two technologies are implemented in finance organizations and used to facilitate process improvement and data-based decision-making, they deliver results impacting process efficiency, throughput, and reduced transaction costs. At ABBYY, we’ve seen customers experience results such as:
Learn more about ABBYY’s AI tools to support today’s CFO with increasing visibility and efficiency in procure to pay.