As 2023 budget processes commence, global megatrends such as economic shifts, labor shortages, and digitalization driven by geopolitics, the environment and workforce dynamics continue to evolve. The ripple effect of these, coupled with record-high inflation and the likelihood of a recession, have required CFOs to become even more strategic and agile. Expanding the focus of planning activities beyond the P&L to cash and capital planning can help CFOs better understand cash flow drivers and ensure resiliency through uncertainty.

Navigating such volatility requires a collective effort across Treasury, FP&A and business partners to develop cash forecasts aligned with strategies and operational improvements.

• From a liquidity management perspective, Treasury functions should collaborate with banking partners to develop informed short- and long-term strategies to manage cash, investments, debt and foreign currency exposures.
• Treasury also should work closely with Finance to review debt parameters and covenant calculations, as well as to understand planned capital projects and strategic initiatives.
• Finance should partner with the business to develop financial plans that are aligned with business strategies that are flexible to adapt to market volatility.
• Data analytics teams may provide meaningful insights for inputs and assumptions, driving financial models by applying advanced analytics.

The outcomes of these integrated efforts should be incorporated into cash flow planning models, as well as key analytical elements. For example:

Working capital analytics can provide visibility into trends impacting receivables, payables and inventory to drive actionable insights to improve working capital and cash conversion by focusing on key drivers beyond traditional DSO, DPO and DIO analysis.  Finance teams may consider, for example:

• Calculating the Collection Effectiveness Index (CEI) for additional insight into the effectiveness of customer collections. Analyzing the percentage of high-risk accounts can also provide additional context into receivable performance drivers, as well as the composition of the customer base.
• Analyzing discounts taken versus offered may allow the business to take advantage of early-pay discounts or provide additional context related to missed opportunities.
• Leveraging external data to provide greater insights to help manage inventory levels impacted by supplier operational issues, securing raw materials and other supply chain challenges. This information can be used to support strategic decisions, such as increasing supplier diversity, transforming procurement practices or reducing costs in supply chain operations.

Scenario-based planning can be a valuable tool in navigating uncertainty, mitigating potential financial risks and optimizing cash management. Scenario models should not be overly complex – using only a few key variables related to the macroeconomic environment, such as interest rates, and company-specific drivers, including changes in demand. Successful scenario planning is always linked to defined outcomes, such as seeking or reducing external financing or cost reduction initiatives impacting fixed or variable costs. Analyzing and comparing different cash flow scenarios allows management to make more informed investment and strategic financial decisions.

Stress testing or “what-if” scenarios may also provide a view on best case/worst case scenarios, enabling organizations to adapt quickly to changing market conditions. This scenario-driven approach may be used to test the impact of various economic assumptions on the business or an investment portfolio. Beginning with a baseline forecast for the most likely outcome, stress testing involves running multiple simulations for alternative scenarios to develop a probability distribution of economic outcomes. Such analysis can be used to support capital planning, evaluating impacts on the cost of capital and which investments should be reduced based on a specified increase in interest rates.

Such analysis can enable a more agile planning process when coupled with dynamic financial models to support strategic funding and investment decisions, in addition to managing short-term credit and long-term debt. However, enhanced analysis requires technologies that can combine internal and external data sets. Companies should consider leveraging pre-built “plug-and-play" digital solutions to deliver meaningful insights through advanced analytics embedded into driver-based models. Artificial intelligence and machine learning tools can also identify patterns and trends to monitor and project cash flow.   Alongside technology, CFOs should also reassess organizational capabilities and skill sets, promoting innovation and bridging the gap between data science and traditional finance.

These elements can provide finance organizations with a solid foundation to deliver benefits far beyond budgeting, providing companies with the ability to remain agile amid ongoing change and volatility.