Wednesday, March 27th: 12pm EST
Join this Treasury & Risk webcast as we explore how our 2024 Alexander Hamilton award winners moved from manual and inefficient to automated and highly effective cash forecasting.
Effective cash forecasting is foundational to treasury’s core responsibility of cash management. Yet many companies—even large, successful global businesses—still develop cash forecasts via Excel spreadsheets and manual processes. As a result, they lack accuracy and visibility into the organization’s future cash flows, which means treasury misses opportunities to reduce borrowing costs and/or increase investment earnings on excess funds.
All three of this year’s Alexander Hamilton Award winners in the category Liquidity Management started in that position. But through their award-winning projects, they transformed out-of-date, manual forecasting practices into highly automated processes that generate accurate and granular estimates of future cash flows.
Now, these organizations are reaping big rewards from their efforts. Â
Despite having $8.4 billion in cash and cash equivalents and $22.5 billion in revenue during the first half of 2023, Bristol Myers Squibb used to have a largely manual and Excel-based cash forecasting process that was not consistent globally. The company developed an entirely new forecasting process and deployed specialized software that introduced extensive automation. Now, cash forecasts are more accurate companywide, leading to better funding, investment, and hedging decisions.
Palo Alto Networks was missing out on investment earnings across a significant portion of its cash balances. As part of its Investable Cash Optimization Program, the treasury group revised the corporate investment policy to allow new cash allocations and automated formerly manual processes. Thus, Palo Alto was able to increase the proportion of cash balances that it invests, from 82% to 97%, and diversify cash holdings into higher-yielding bonds.
London-based Pearson experienced a decline in the accuracy of its cash forecasts following the Covid-19 pandemic. Its legacy forecasting process required a great deal of manual effort, making it error-prone and time-consuming. The company revamped cash forecasting to improve accuracy and granularity, as well as efficiency, at a global scale. The drastic process improvements enabled the company to reduce borrowing by more than US$100 million.