Secrets of Success in Cash Forecasting: 2024 Alexander Hamilton Awards in Liquidity Management
Date: Wednesday, March 27, 2024
Time: 12pm ET | 9am PT
Approved for up to 1.2 CTP/CCM recertification credits by the Association for Financial Professionals
Editorial Webcast Sponsored by:
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 But through their award-winning projects, they transformed out-of-date, manual forecasting practices into highly automated processes that generate accurate and granular estimates of future cash flows.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. Join this Treasury & Risk webcast as we explore how this year's winners moved from manual and inefficient to automated and highly effective.
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.
Can't attend? Register here for an on-demand recording after the webcast.
Catherine Portman | VP & Corporate Treasurer |Palo Alto Networks Catherine joined Palo Alto Networks in 2019. In her role as vice president and corporate treasurer, she is responsible for leading the global treasury organization across critical functions, including cash and investments, capital markets, customer finance, global banking, and risk and insurance.
Brian Zarahn | Director of Treasury | Palo Alto Networks
Brian Zarahn is a director of treasury at Palo Alto Networks, managing the company's investment portfolio, capital markets, and foreign exchange (FX) hedging. Prior to joining Palo Alto Networks, he served as a Wall Street equity research analyst at Mizuho, Barclays, and Lehman Brothers. He holds a Bachelor's of Science degree from James Madison University and an MBA from the Wharton School at the University of Pennsylvania, and he is a CFA charterholder.
Abhishek Jhunjhunwala |Director, Capital Markets | Bristol Myers Squibb
Abhishek Jhunjhunwala is the director of capital markets at Bristol Myers Squibb. He has been with the company for about 11 years and has held various roles in the company's finance organizations (treasury, FP&A, controller, internal audit, business controls). Jhunjhunwala worked on the KPMG Risk Advisory team prior to joining BMS in 2013. He is a Chartered Accountant and graduated with a degree in finance and accounting in India.