Now more than ever before, finance and treasury departments are experiencing a period of intense change, characterized by the accessibility and availability of a myriad of new cloud-based tools and technologies, increasing expectations of service delivery and business partnership levels, and the need to continuously keep finance and treasury skills sharp in terms of both “soft” as well as analytical and technical skills. It will be interesting to observe what the future of finance and treasury will evolve to look like (people, process, and technology) as these core support areas within organizations work to transform digitally along with the rest of their associated enterprises to better serve and support internal and external customers.
One important evolutionary change for finance and treasury is the increasing adoption of emerging tools and technologies, such as robotic process automation (RPA) and cognitive computing/machine learning. Such tools offer tremendous potential both in terms of the ability to free up time to focus on more value-added activities, and also to analyze large volumes of data more efficiently and help provide insights for better and faster decision making.
APQC has observed the usage of these tools increasing in prevalence within finance and treasury. RPA is a prime example. RPA is a form of server-based process automation that combines process steps with decision models or business rules with little to no human oversight. According to APQC’s most recent Treasury Operations Open Standards Benchmarking survey (400 respondents), more than half of treasury survey respondents have engaged in RPA work in treasury to at least some extent, with the majority of the rest planning to adopt RPA in treasury sometime in the future. Only 16 percent of treasury survey respondents reported that they have no plans to adopt RPA (see Figure below).
For example, Mallinckrodt Pharma, who shared on a recent APQC financial management Webinar, leverages RPA in treasury to automate daily cash position reporting. Drawing data from banking portals, secure e-mails, and other sources in a variety of formats, a bot applies a series of business rules related to the opening day balances and daily transactions to generate a projected closing balance for the day. Based on these inputs, the program generates and distributes the cash position report to relevant stakeholders. The bot navigates bank portal logins and extracts data from six banks in a variety of formats that included Excel, PDF, screen shots, and secure e-mail attachments to produce a daily cash report for decision making. As a result of the use of RPA for daily cash position reporting, the organization has seen a big reduction in cycle times, from an hour or longer each day to around three minutes. In addition, according to the assistant treasurer, the use of RPA in treasury has helped the organization to expand the treasury team’s skills because they are no longer doing the repetitive tasks that are now handled by bots.
Similarly, emerging tools like cognitive computing and AI are increasing in prevalence for finance and treasury. Cognitive computing refers to self-learning computer systems that use data mining and machine learning to simulate human thought processes. APQC’s most recent Treasury Operations survey found that four out of five treasury survey respondents are implementing cognitive capabilities for purposes of working capital optimization to at least some extent, although only a quarter say they have fully implemented it (see figure below). APQC’s research has found that top ways that cognitive computing could deliver value to finance and treasury include improving decision making, reducing risk, and increasing performance insights.
Of course, layered onto all of these changes already underway in terms of the increasing pace of digital transformation is the current pandemic scenario, again bringing treasury departments within finance to the very forefront of importance to their enterprises, as the department that is responsible for payments, liquidity, and cash management and forecasting. As discussed above, treasury was already well underway in terms of evolution, and the interesting question becomes: What will treasury look like in terms of skills, processes and practices, automation, and success measures, in the “next” (not new) normal?
Continuing in its quest to find and disseminate best practices and metrics for key processes within finance, such as treasury, APQC has partnered with SME Ernie Humphrey, CEO of TreasuryWebinars.com, to engage in a new research project to understand what success will look like for treasury in the “next normal” (e.g., post-pandemic and beyond) and to identify the key drivers/best practices of treasury success. This study is comprised of both an online survey and practitioner interviews, exploring practices related to the environment/structure of treasury departments, cash management, managing bank accounts and bank relationships, managing debt and investments, monitoring and executing risk and hedging transactions, and department-level success metrics. APQC would like to invite you to participate in the short survey component of this study to help improve the treasury profession, and in return each participant will receive a blinded summary results report at the conclusion of the data collection. Click here to participate in the survey.
There is no doubt that the pace of change these days is accelerating, and there are many exciting new developments are happening in finance and treasury. Stay tuned to APQC over the next few months as we complete this research study and report out highlights from the latest research on finance and treasury success practices.