Cash management disrupted
Technology driven cash management works well in predictable environments, but it can easily be tripped up by corporate events that reshape a company’s business model.
Businesses increasingly have to reinvent or transform themselves to survive, and treasurers have to manage change as a new normal.
For instance, back in February 2021, TechnipFMC spun-off Technip Energies, an engineering & technology company for the energy transition in liquefied natural gas and other energy sources. Even for a state-of-the-art cash management forecasting system powered by artificial intelligence, such an event would have thrown a spanner in the works.
Suddenly, TechnipFMC’s business changed. This required some very human intervention at the energy industry technology provider to keep the treasury aligned with the new reality.
“(Technip Energies) had different cash flow and balance sheet characteristics,” said Fred Schacknies, VP & Treasurer at TechnipFMC speaking at the 2021 International Treasury Management Virtual Week.
This change saw the TechnipFMC treasury team go back to the drawing board to rethink their approach to forecasting cash flows and managing cash.
Schacknies explained that Technip Energies maintains larger cash balances due to the nature of the projects it engages in. Following the spinoff, the remaining TechnipFMC is focused on deleveraging to enhance balance sheet efficiency. As a result, the goal of cash forecasting at TechnipFMC has shifted to better understanding the sources and uses of capital at a macro level.
The challenge of new business models
Microsoft is a very different type of business to TechnipFMC, not least in terms of its balance sheet. Microsoft reported holding $125 billion of cash and securities at the end of 2021, while Technip FMC owned $4.8 billion of cash and equivalents at the end of 2020.
Although Microsoft buys a new company almost every week – mostly recently Activision Blizzard for which it is paying $69 billion – most of those acquisitions barely register on Microsoft’s prodigious cash flows. But the treasury still has to integrate their impact on the company’s cash position.
Microsoft has demonstrated the value of ‘smart’ treasury systems, no doubt helped by its predictable revenue streams. Yet even here Microsoft faced challenges as its business model evolved from software sales to software-as-a-service and cloud products.
Jim Scurlock was Head of Global Cash Management at Microsoft until January 2022, when he moved to fast-growing AI cloud company DataRobot as their Treasurer. As he explains, Microsoft’s new SaaS businesses simply didn’t have enough historic data to feed into machine learning models. Moreover, the effectiveness of ‘smart’ cash management systems can also be blunted by the human factor, according to Scurlock.
One issue is that different parts of the business might be incentivised to pursue certain strategies, such as boosting profit margins, which can be reflected in their reporting. Others may pad out their forecasts to cover themselves in case the future doesn’t pan out as anticipated. “It’s almost a washed out forecast, you really can’t rely on it. It could be 10% to 20% off,” Scurlock said.
For all the brilliance displayed by AI, such technologies can be poor at dealing with sudden unpredictable events. Many businesses simply don’t generate smooth linear earnings. Their fortunes may fluctuate with the ebbs and flows of the economy or involve unpredictable sales of one-off large items that can influence a company’s cash profile.
“A fundamental lesson I’ve learned is that whatever your forecasting approach, whether it is direct or indirect, you have to reflect the needs of the business. There is no one size fits all,” said Schacknies.
“One thing that I’ve learned over time is that, frankly, direct forecasting alone often doesn’t work,” observed Schacknies.
The treasury and departments reporting data often speak a different ‘business’ language. He added that it takes considerable effort to coordinate and gather inputs from across the organisation. Plugging those data gaps comes down to legwork. “You really have to go out and partner with finance leaders from across the business and get them invested in understanding it,” advised Schacknies. A necessary, but time consuming activity, particularly as treasury teams are often lean and small.
“The reason why we have been able to scale as efficiently as we have is because we did implement in-house banking, almost 20 years ago,” said Scurlock. The in-house bank has allowed the group’s treasury to efficiently centralise data and to manage activities such as inter-company loans.
He explained that the in-house bank enabled the treasury to centralise many of the firm’s exposures. This makes it much easier to identify cash flows and map them to particular activities. The in-house bank and Microsoft’s technology are a potent combination: “It takes us about 15 seconds to run something using machine learning,” said Scurlock. “And we’ve got an AR (accounts receivables) forecast by legal entity for the next 12 rolling months.” He explained that the process is incredibly accurate and he tries to use machine learning wherever possible. He said Microsoft has close to 98% visibility to all of its cash balances globally.
Schacknies acknowledges that in-house banks are fundamentally better than traditional banking tools for managing global liquidity. But it’s not an all round solution. “However, that efficiency comes by substituting movements of cash across banking networks for movements of data within treasury systems,” he said in response to questions from EuroFinance. He explained that for traditional accounting or consolidation systems or forecasting models built to observe changes in bank accounts, that shift can be confusing. “Ultimately, it shouldn’t be,” he remarked. “Treasurers have a choice: either forecast at the transaction level and treat in-house bank accounts as if they were external ones, or forecast at the external cash level only, and understand that intercompany transactions may seem invisible.”
How useful a ‘smart’ cash management system is, doesn’t just depend on the quality of the inputs, but also on the predictability of the underlying business.
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