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Balancing Cost Cutting with Innovation - The Future State of Finance Departments

by Anant Kale March 10, 2021

CFOs are frequently asked to do more with less. But during the COVID-19 pandemic, this expectation has been more pronounced than ever. Many tout automation technology as a savior of the finance department for many years, but what is the actual state of technology adoption?

During 2020, AppZen interviewed finance leaders from over 200 global organizations to evaluate their technology adoption, how pervasive automation in finance is, and what benefits they see from such solutions. The findings illustrate glaring levels of inequality in technology adoption and the benefit gained from it, between the haves and have nots. This blog explores the adoption of technologies such as automation and AI. It also highlights the areas where CFOs feel they see success and provides recommendations for focus areas into 2021 and beyond.

Work from Home: The Digital Transformation Accelerator

Embracing digital transformation has been imperative for businesses to weather the COVID-19 crisis, and continued focus on adopting digital technologies will allow organizations to thrive in a post-COVID climate. According to Gartner, “Nearly three in four CFOs plan to shift at least 5% of previously on-site employees to permanently remote positions post-COVID-19,” which contributes to cost-cutting measures that CFOs have already taken or plan to take in evasion of economic hardship.

For CFOs and finance leaders, COVID-19 presented an opportunity to leverage digital solutions like automation and AI to mitigate the adverse economic impacts of the pandemic. In fact, 86% of our survey respondents said that they accelerated digital transformation projects in response to the current climate, with over 40% looking to continue efforts to reduce manual processes and better equip the remote workforce moving forward.

Room for Improvement with Accounts Payable Automation

That said, even with a majority of CFOs promoting investment in digital transformation, there is much room for improvement, and the notion of “acceleration” may vary from one organization to the next. Two areas that have exposed weaknesses regarding financial automation are AI-based invoice processing and expense auditing. Only 40.9% of respondents currently automate ingestion and extraction of data from invoices, while 43.5% of organizations still take seven or more days on average to process an invoice. This is a far cry from the 2.9 days recorded by organizations with more proficient automated processes.

What’s hampering progress for these companies? With the abrupt transition to remote work and the unexpected turn of events over the past year, financial departments may have had difficulty developing and implementing a clear, long-term vision and strategy. Defining a breakdown of which technologies merit priority investment and deployment is a challenging task. CFOs and company leaders who, in many cases, need to cut spending quickly have to focus on more reactionary measures versus deliberate, well thought out initiatives.

Too Little Too Late? Those Not Investing May be Falling Behind

The technology adoption gap is large in finance departments  – and it is growing. Companies who have already adopted and mastered the basics of automating invoice processing and expense management are now focusing their investment on emerging key areas of focus that could boost business success, including advanced analytics, AI, and RPA.

Nearly half of CFOs surveyed wish they had invested more in technology adoption for finance over the last five years, with 67% of respondents acknowledging a missed opportunity within advanced analytics. Accounts Payable intelligence enables finance professionals and CFOs to make more informed decisions, which could be a major game-changer in the coming years. From an AP automation standpoint, companies can use data analytics to gain insights into how customers, vendors, and suppliers interact with an invoice to deliver more personalized services.

Similarly, 42% highlighted AI and machine learning as a missed opportunity for investment. Machine learning in AP automation helps CFOs better understand vendor payment risks, forecast future spending increases or decreases, and detect the statistical probability of invoice anomalies and fraudulent expenses.

These responses highlight the gap between what CFOs recognize as beneficial to their company and what has actually been implemented in the past year or more. Financial leaders may now have the hindsight to recognize that favoring short-term cost-cutting over long-term strategy has resulted in their organizations falling behind in certain areas. But this retrospection may be arriving too late in the game, as bridging the gap will only become more difficult as early investors in these technologies continue to pull ahead.

Looking Forward: CFOs Remain Optimistic for the Year Ahead

Despite these discrepancies, 66% of CFOs remain optimistic about the future, expecting growth in 2021. The bulk of those optimists are likely the early adopters of AP automation and AI, who can now focus their attention on better leveraging those technologies, investing in AP intelligence and advanced analytics. Finance leaders can better lead their teams by embracing technology such as automation, advanced analytics, and machine learning to rapidly adapt to the volatile climate and help facilitate growth post-COVID-19.

Those who expect to experience negative growth in 2021–about 25% of respondents–are more focused on cost savings than a long-term investment. Existing disparities will only be exacerbated in the coming months as companies already investing wisely in digital transformation continue to leverage technology in a strategic way to extract the greatest possible value from the finance function.

*All data in this report was sourced from research performed by AppZen in late 2020. Full copies of the data can be found in the CFO Survey Report – Why Optimism Abounds.

Anant Kale

Founder & CEO at AppZen. Anant dreams up the next use of Artificial Intelligence for enterprise automation