Finance discipline for optimized performance

A blog post by David Cutbill, principal, Deloitte & Touche LLP

Around the globe and in most industries, whether a company is going through aggressive growth or tightly managing margins against increased competition, the future, and its impact on business, is increasingly unpredictable. This significantly lessens the predictive value of historical financial reporting, highlights the weaknesses of inflexible forecasting processes, and often results in an inability to efficiently and agilely allocate capital and cash across businesses. Finance professionals may be wondering how organizations can effectively plan for the future when the present is rife with uncertainty. It’s a reasonable question.

Recent events have heightened this unpredictable environment and exposed the need for enhanced financial disciplines that enable flexible, agile management, incorporating multiple competing views of the future. When future economic performance rests on the finance function’s shoulders, supporting and continually evaluating current decision-making that optimizes performance in the long term is essential. Doing so when the present and future are unknown is only possible with new and enhanced financial disciplines that foreshadow the future of finance.

What is driving the need for new financial discipline?

Marketplace volatility | Inflexible forecasting | Data limitations

Marketplace volatility, whether from macroeconomic events like the pandemic, rapid innovation, or increased vectors of competition, has meant that historical financial information is decreasing in value, either for the markets to appraise companies or for management to make strategic or operational decisions. Unfortunately, the traditional design for the annual planning and forecasting process fails to pick up this slack. It typically has built-in rigidity, limited ability to reforecast, and a focus on a single view of the future with linear execution plans.

Another underlying constraint is the lack of organized and connected internal and external data that informs management on marketplace and business impacts across different time horizons. We have heard the terms “driver-based budgeting” and “single source of the truth,” but these have not migrated into a companywide, driver-based information hierarchy that can effectively synthesize and use increasingly large amounts of historical, current, and predictive trend data.

The effective management of different kinds of risk is also not ingrained in many management disciplines, which often treats risk management as a separate parallel or one-off exercise that does not adequately maximize the return on risk across a plethora of strategic and operational decisions.

Guiding principles for a new finance discipline

• Manages against multiple views of the future
• Leverages diverse external economic and ecosystem evolution data
• Incorporates a future-focused view across multiple time horizons
• Allows for agile and surgical management across the business
• Supports decision-making with flexible and responsive execution
• Lessens the impact of management biases on decisions and execution
• Maximizes combined long-term success across diverse businesses

When faced with these challenges, a new breed of financial disciplines will need to meet a different set of criteria to better position the business to thrive in the current and any future environment.

How to develop new finance disciplines to enhance performance

The elements of finance disciplines that we explore here develop from a foundation of robust scenario development and resilient scenario planning. From there, agile capital allocation and predictive forecasting enable more structured and flexible decision-making, incorporating better real-time insight from across the business ecosystem.

The financial discipline focus: Developing scenarios, allocating capital, and using predictive forecasts for decisions

Developing scenarios for better planning

In times of uncertainty, predicting the future is difficult. However, structured scenario planning can empower organizations with more confidence in decisions taken now, enabling actions against multiple potential scenarios that improve operational resilience and financial performance, mitigating many of the challenges with predictions amid uncertainty.

Scenario planning uses real-world data and possible outcomes against critical uncertainties to create hypotheses about what could happen. Each assumption examines the implications for each scenario within the company’s specific business environment. It is important to remember that these scenarios create stories about what the future may be like. They are not predictions about what will happen, but hypotheses about what could happen, designed to shed light on new opportunities or hidden risks. They also provide greater clarity on a fundamental question: What would need to be true for this future to materialize?

Creating capital resilience in any environment

Another key underdeveloped finance discipline is capital optimization, which enables a more agile business model and resilient organization. Using scenarios with their implications and impact can maintain adequate liquidity in the current environment to cover different negative outcomes while also identifying surplus capital as possible leverage for investment and business opportunities.

Organizations can start responding to the current climate by upgrading short-term working capital and liquidity management with more transparency across the enterprise. Future transformation introduces scenario planning and optionality into a more agile capital allocation process that can adapt in real time for changes in the business and operating environment.

Predictive forecasting for risk sensing and enhanced decision-making

The act of forecasting needs to be more agile and constantly updated, even while incorporating multiple potential scenarios. Businesses can hotwire traditional planning and forecasting processes by utilizing scenario planning along with predictive analytics and data technologies. These new technologies use automation and robotics tools with a capacity to produce more accurate and voluminous data in real time and that surpass the speed and volume limits of manual processes and historical forecast models. This velocity of data means better information, and better information informs better forecasting. Data- and scenario-driven statistical models, alongside agile planning and short-term capital allocation, constitute the new financial disciplines. Concentrating on these disciplines collectively fosters a more resilient business that can optimize performance now while setting up future success in an ever-changing environment.

Key takeaways to know right now about finance discipline

Here are some key insights to know right now about the need for these new integrated finance disciplines. Coming soon, we will be taking a deeper dive into each area of focus: scenario planning, capital allocation, and predictive forecasting. This will include more insights into developing effective scenarios, the theory and mechanics of capital allocation, and how to build predictive forecasting capabilities. It is essential to build and enhance these integrated finance disciplines to support effective decision-making and optimize performance in these increasingly uncertain times.

Five takeaways on finance discipline

• Historical financial reporting and inflexible budgeting and forecasting processes can no longer support effective decision-making in the current uncertain environment, where the speed of change is ever-increasing.
• Finance disciplines need to be more future-oriented and leverage robust scenario planning as a foundation to incorporate multiple possible views of the future and support better decision-making today.
• Initial focus should be on building transparent and responsive working capital management processes that can more efficiently provide liquidity across the business to manage downside risk or fund growth opportunities.
• Capital allocation capabilities need to be upgraded to introduce scenarios and optionality and incorporate real-time information loops to test underlying hypotheses, enabling more rapid reallocation of capital as marketplace conditions change.
• Predictive forecasting models that incorporate real-time data, automation, and predictive analytics can hotwire traditional planning with a more agile process of accessing potential scenarios, analyzing risks, and enhancing insights for more informed decision-making.