Planning for uncertainty

In today’s fast-paced business environment, uncertainty is a constant challenge. Traditional planning methods are often inadequate. Predictive planning and forecasting (PPF) has become essential for businesses aiming to stay ahead in the current market. This dynamic approach enhances agility and adaptability in decision-making and provides a robust way to plan for and manage uncertainty.

What is predictive planning and forecasting?

PPF leverages data analytics and machine learning to forecast future outcomes, enabling businesses to make informed decisions and adapt to changing conditions.

PPF transforms data into actionable insights through scenario planning. By integrating data analytics, statistical methods, and machine learning, PPF predicts future outcomes and prepares businesses for various potential futures. It supports on-demand re-forecasting when key assumptions change, using dynamic models to identify the key business drivers. This helps companies adapt swiftly to both internal and external changes.

PPF can operate on different maturity levels, from basic Excel-based models to advanced systems with predictive analytics, AI, and sophisticated technology platforms. Even at the basic stages, PPF demonstrates significant improvements over static forecast methods like last year plus 10%.

By adopting PPF, organizations transition from a static planning approach to an agile, data-driven one, which enhances their ability to make strategic decisions, optimize resources, and mitigate risks effectively.

Why Is PPF important?

PPF is crucial for several reasons:

• Anticipating market trends: Predictive Analytics help businesses foresee market changes and adjust quickly to maintain a competitive edge. For example, predicting seasonal demand allows companies to maintain appropriate stock levels, while modern technology helps them understand shifts in customer behavior – an insight previously unattainable.
• Enhancing decision-making: PPF provides data-informed insights, which reduce the reliance on intuition and bias prevalent in traditional planning. This transformation leads to a more analytical culture, moving away from the “political games” of traditional budgeting.
• Optimizing resource allocation: By forecasting future needs, companies can allocate resources more effectively and reduce the associated waste and cost. For instance, raw material purchases can be optimized based on production forecasts.
• Mitigating risks: PPF helps companies prepare for potential risks, minimizing their impact on operations. For example, planning for supply chain disruptions.

Real-world applications

Members of the International FP&A Board have shared their insights on PPF in different industries at various global locations.

Retailers

PPF helps forecast sales trends, optimize inventory levels, and adjust purchasing patterns in real time. A CFO from the retail industry shared the following insight:

“By analyzing customer data, we can predict high-demand periods and adjust stock levels accordingly, preventing overstock and stockouts. This approach aligns inventory management with financial strategy, improving cash flow and reducing holding costs.“

Manufacturers

PPF predicts production bottlenecks and schedules maintenance to minimize downtime. A VP Finance in manufacturing noted:

“PPF allows us to forecast equipment failures and plan preventive maintenance, ensuring continuous production. This proactive approach reduces unexpected costs and improves asset utilization, directly impacting our bottom line.“

Fast-moving consumer goods (FMCG) companies

PPF helps understand market shifts and consumer preferences, guiding product development and marketing strategies. A Finance Executive from an FMCG company remarked:

“By analyzing consumer behavior data, we can anticipate new trends and launch products that meet emerging demands. This alignment of product strategy with financial objectives helps optimize marketing spend and improve return on investment.“

An integrated PPF model shows how changes in a strategic plan automatically impact operational and financial aspects. For example, a change in marketing strategy will filter updates immediately into production schedules and financial projections, ensuring all departments are aligned and financial targets are met. This holistic approach enhances Strategic Planning and financial performance.

Maturity of PPF

Our research shows that organizations typically progress through five stages of PPF maturity, each incorporating more sophisticated models and technologies. This simplified model helps you understand where you are and allows you to plan your organization’s transformation.

1. Basic: Manual Processes
   • Reliance on spreadsheets and intuition-based forecasts.
2. Developing: Driver-Based Models
   • The use of basic statistical methods and separate spreadsheets.
3. Defined: Data Integration and Initial AI/ML Usage
   • Centralized data with initial artificial intelligence (AI) and machine learning techniques.
4. Advanced: Data Warehouses and Sophisticated Models
   • Real-time scenario management with advanced analytics.
5. Leading: Real-time and Fully Automated Systems
   • Full integration with real-time data and automated analytics.

As organizations advance through these stages, the FP&A team evolves from a data consolidator to a strategic business partner, leveraging storytelling with data.

5 strategic considerations for implementing PPF

Each organization will be at a different stage of PPF maturity. Depending on where you are, you can start planning the transformative steps for your company. Implementing PPF involves five strategic considerations:

1. Data quality and key business drivers

• Ensure real-time, high-quality data. Start by integrating key data sources and improving accuracy. The 2024 FP&A Trends Survey indicates that 45% of FP&A time is spent on non-value-adding activities related to data quality, therefore highlighting the need for improvement.
• Identify critical business drivers. Focus on the 20% of drivers that explain 80% of outcomes, such as customer demographics and seasonal trends.

2. Dynamic forecasting models

• Integrate key drivers into dynamic models. Connect strategic, operational, and financial planning processes. Our survey shows that driver-based models have streamlined processes and reduced manual labor, as they have been adopted by 37% of organizations in 2024.
• Use advanced modeling techniques. Incorporate machine learning and statistical methods to perform adaptive, real-time forecasting. According to the 2024 FP&A Trends Survey, organizations using AI/ML technologies rated their forecast accuracy 25% higher than the average.

3. FP&A skills

• Build a skilled, multifunctional team. Include roles like FP&A Data Scientist and FP&A Architect to combine data science, finance, and IT.

4: Integrated processes

• Establish collaborative processes. Ensure seamless integration across departments to align all plans with the general ledger and relevant cost centers.
• Promote cross-functional teamwork. Conduct regular cross-functional meetings and business process mapping to improve alignment and eliminate inefficiencies between teams. Despite the improvements, the 2024 FP&A Trends Survey shows that 35% of FP&A teams still face high workloads due to manual tasks.

5. Technology and analytics

• Invest in advanced technology. Use cloud-based platforms to support predictive analytics and machine learning. The 2024 FP&A Trends Survey shows that 40% of organizations upgraded their FP&A systems in the past year, reflecting a trend toward modernizing FP&A tools.
• Leverage automation. Automate data loading, model updates, and scenario analysis for timely, accurate forecasts that inform strategic decisions.

Depending on your current stage of PPF maturity, consider taking some of these steps to guide your organization toward more advanced and integrated forecasting.

Conclusions and recommendations

The PPF framework is a strategic necessity for organizations aiming to thrive in a dynamic market. Follow these clear steps to implement PPF effectively:

• Adopt PPF: Shift from static planning to proactive, strategy-shaping planning methods by integrating key data sources and improving data accuracy.
• Leverage advanced analytics: Use real-time data, Predictive Analytics, and machine learning to make informed decisions.
• Invest in technology and skills: Implement cloud-based platforms to allow for collaboration and real-time data access. Build an FP&A team skilled in data science, finance, and IT.
• Foster collaboration: Promote a culture of cross-functional teamwork with regular meetings and continuous education. Our survey showed that only 13% of organizations have implemented fully integrated Business Partnering activities, leaving significant room for improvement.

By following these steps, FP&A departments can transform into dynamic strategic entities, enabling businesses to stay ahead in an unpredictable market. This transformation, from data consolidation to strategic partnering, can help companies navigate the complexities of the current business environment.