It’s not unusual for CFOs to be engaged in their company’s digital transformation. What is remarkable are the major strategic initiatives led by finance chiefs like Chris Greiner that involve end-to-end systems automation and the use of artificial intelligence tools.
In June 2021, Greiner took Zeta Global, a cloud-based marketing technology company, public—again nothing unusual, other than a very challenging investment climate. What stands out is that he and the finance organization orchestrated the IPO on a virtual basis, without ever meeting face-to face-with investment bankers and research analysts, much less the members of his team and the CEO.
These meetings occurred, of course—exclusively on Zoom. “All the normal physical stuff in an IPO, such as the road show meetings with banks, attorneys and analysts, were done on a virtual basis through Zoom meetings,” Greiner said.
The bigger challenge, he added, was building the financial models needed to elucidate the company’s earnings prospects at the virtual meetings. In anticipation of this need, the finance team spent months automating its systems, gathering and integrating the data stored in these systems on an end-to-end enterprise basis, and using machine learning tools to provide credible forecasts of sales, productivity and other key performance indicators. “Necessity is the mother of invention,” Greiner said.
He’s right about that. Reimagining a process like an initial public offering that had been performed the same way for decades was close to an impossible dream; however, due to the virtual alternatives presented by automation and AI, not to mention a lot of hard work, tenacity and perseverance, the dream became reality.
Could this have happened 10 years ago, even five years ago? Not by a long shot. “AI has moved from the experimental to the operational in the finance function,” said Dan J. Diasio, Global Artificial Intelligence Leader at EY Consulting.
Seeing is Believing
Although many finance organizations have automated traditional financial and accounting processes, due to the time consumed in performing rote and repetitive manual tasks like accounts reconciliations, they’re just beginning to take the next step in becoming a digital-first enterprise—investing in AI-fueled predictive technologies.
“When we ask CFOs if they added 1,000 people to the function to add value to the business, what would they do with these people,” Diasio said, “their typical response, which they know is not feasible, is that they wish they could disperse them across the enterprise to serve as personal advisors to each team to propose actions that generate better financial performance. We then show them how they can do the same thing with automation and AI-driven analytics.”
Instead of investing time into assessing and measuring revenues and expenses to provide a forecast and drum up a budget, strategic CFOs are automating these processes on an end-to-end systems basis, then leveraging the data produced into predictive insights.
These sharp-eyed discernments include the true value of assets and opportunistic or concerning sales trends, customer payment patterns or logistical bottlenecks. By using AI to analyze the impact of supply chain constraints, for example, a company’s pricing dynamics can be improved. “AI combined with RPA (robotic process automation) has reimagined the finance function,” Diasio said.
Two years ago, a survey by Deloitte of finance professionals indicated that less than half (47 percent) of CFOs were becoming “skilled” in using AI tools like machine learning, natural language processing (NLP), deep learning, digital assistants and computer vision, among others, given their enablement of a competitive advantage. “Smart CFOs have to give serious thought to artificial intelligence,” the report stated, noting that AI expertise was evolving from “aspirational to mainstream.”
A 2022 report by the audit and advisory firm updated the urgency to obtain AI skills, stating that CFOs “no longer have the luxury of waiting.”
StrategicCFO360 reached out to a trio of CFOs to learn how they are leveraging automation and AI to illuminate uncertainties, drive processing efficiencies, seize opportunities for growth, and help the finance organization assist peers across the enterprise to make better business decisions.
Segmenting Customers to Drive Service Insights
Adam Ante, CFO at human capital management (HCM) software provider Paycor, is not waiting to confront uncertainty. The CFO is leading a major strategic initiative seeking to improve the understanding of its diverse customer base of small and medium-sized companies to better serve their respective needs. The publicly traded company tallies more than 2,000 employees and generated $352.8 million in FY 2021 revenue.
“Historically, the HCM industry has segmented customers based on the number of company employees, like one to 100 employees, or 100 to 500,” said Ante. “The problem is that a 20-person business does not think of itself as a 20-person business; they see themselves as a manufacturer, a doctor’s office or a restaurant.”
Paycor’s HCM software is an integrated suite composed of payroll, expense management, recruiting, onboarding, benefits, talent development and other solutions. The strategic initiative is predicated on finding ways to tailor these solutions and Paycor’s services model to “what our customers do and how they use our products,” Ante said. “We want to learn to segment them in more interesting ways to readjust our internal operations and work processes to their specific needs.”
He provided the example of different customers within the broader manufacturing industry, one of Paycor’s highest performing sectors based on revenue and retention.
“Right now, we segment them by the number of employees, which doesn’t tell us much,” Ante said. “To learn more, we need to identify and analyze their month-to-month interactions with us—the product usage trends, how many times they call with a question, who responded to the question here and in what timeframe, that sort of thing.”
To obtain this detailed customer profile, Paycor partnered with audit and advisory firm PwC and data and analytics solutions builder Nousot. The partners respectively designed a machine learning engine and a set of algorithms that could analyze the continuous flow of data coming from customers to its front-end quoting and pricing systems (provided primarily by Salesforce) through its back-end billing and payment systems (provided primarily by Quora). The systems are automated. In between them, however, is a range of home-grown middleware applications that Ante plans to automate and integrate with other systems to create the desired end-to-end systems architecture.
The strategic project is in the early stages of collecting data and developing models to begin to identify insights, he said, noting that a data and analytics team within the finance function is engaged in a regression analysis using machine learning algorithms “to sort through” a range of variables. “The next steps are to build in additional data sets to enable the model to learn.”
The project will run through the next three quarters before reaching an end state. “We’ll start with simplifying the buying experience, re-architecting the upfront quoting system in parallel with re-architecting the billing system, so customers know exactly what they’re getting and paying for,” Ante said, adding that the finance organization “will continually hone the model” during the nine-month period, seizing opportunities when they appear to tailor its solutions and services closer to customers’ needs.
“Once we have this customer-centricity analysis completed, we can enable more seamless and productive customer experiences, while also learning where we’re falling short,” he said.
Standardizing Global Forecasting and Budgeting
Picsart’s CFO Craig Foster also is leveraging automation and AI, albeit for an entirely different strategic initiative entrusted to his care. The challenge before him is to move the finance organization off Excel-based spreadsheets into “something more robust” to improve the company’s budgeting and forecasting.
Picsart is a digital creation platform with an app making it easy for all kinds of creators to use a variety of AI-powered tools to design, draw, edit and share content. The privately held company employs more than 1,000 people, whose numbers are spread across 10 R&D centers in Miami, San Francisco, New York, Los Angeles, Tokyo, Berlin, London, Beijing and elsewhere.
This far-flung workforce created information logjams for Picsart’s fast-growing business, which produced more than $100 million in annual revenue and is valued at over $1 billion. “We’re a centralized organization with a compartmentalized operation, which makes it difficult to gather and analyze data in real time to do global forecasting and budgeting,” Foster explained.
Picsart’s financial planning and analysis (FP&A) team currently assembles the forecast through what the CFO said were “old school processes, running the analytics using nested Excel spreadsheets with some level of historical data.” To obtain real time data, the team had to “embark on a treasure hunt, synching up with other functions like HR, procurement and operations to find out what’s new in their areas, expense-wise,” Foster said.
As an example, he pointed out that as a digital company, it needs to continuously invest capital in new AI capabilities, which subsequently requires additional capital expenditures in new servers.
To provide a credible forecast required access to real-time sales and expense data; to provide a more detailed and realistic budget required access to information on available capital, estimated capital expenditures and projected revenues. “We had to put an end to the treasure hunt,” Foster said.
The finance organization is at the beginning of what the CFO projected will be a six-month process to develop world-class budgeting and forecasting processes. As the project takes shape, four technology solutions are being brought to bear.
“We’re using BlackLine to automate time-consuming manual processes like account reconciliations, spitting out only the exceptions that require human input,” said Foster. “We’re also deploying a full-blown cloud-based FP&A platform called Planful to streamline planning, analytics and budgeting.” The other tools include Procurify, a provider of purchasing and procurement software to track, control and analyze business spending, and Bill.com, a cloud-based payments platform automating the payment approval process, with built-in analytics. “Soon we’ll be able to see what’s happening in our procurement and payment processes to include these insights as we formulate the budget and forecast, the gray areas disappearing,” he said.
Virtual Road Show
The gray area for Zeta Global was finding a window of time in 2021 to launch its planned IPO, given the long queue of businesses hoping to do the same but stymied by the pandemic. “We needed to be ready at a moment’s notice as soon as a window opened up,” Greiner said.
In the meantime, the CFO and his finance team put together the building blocks beginning in early 2021, transforming the typical manual work involved in the process into its virtual doppelganger. “Instead of the typical `analyst day’ meeting with nine research analysts in a room, for example, we prepared to meet with each analyst in one-on-one virtual sessions,” Greiner said, explaining the financial models.
Before the virtual sessions could commence, systems like sales, HR and finance were automated on an end-to-end enterprise basis. Once completed, the data coming from across this network was integrated and a set of machine learning algorithms was developed to measure productivity, forecast sales and project deal closings. This data populated the financial models that were ultimately introduced virtually to the analysts.
“Other than Zoom, we had all the vendors we needed to automate the systems,” said Greiner. “What we didn’t have but quickly invested in were people to build all the connectors and do the analytics.”
These people were hired in the finance organization. “During the IPO process, instead of hiring more accountants and financial analysts, I hired systems-driven people with finance backgrounds,” he said.
The IPO came off without a hitch on June 10, 2021, with shares priced at $10. Revenues were $458 million in 2021, a 25 percent increase from reported revenues the previous year. Greiner attributed the successful public offering to his finance team’s blend of technology and traditional finance and accounting skills.
“It’s what you need these days to be considered a world-class finance organization,” he explained. “Frankly, I wouldn’t be surprised if one of the future CFOs of Zeta has more of an IT systems background than an accounting background.”