Financial Planning & Analysis (FP&A) upholds the financial wellbeing of enterprises by providing timely and accurate analysis on finances. However, generating accurate financial forecasts through traditional planning strategies means keeping FP&A teams busy collecting and validating data rather than spending time on high-value activities.
A conventional forecasting process that relies on outdated technology not only leads to inaccurate results but also delays the decision-making process. A 2019 survey from SAP shows that FP&A teams spend only 23% of their time on high-value activities.
In the advancing world of financial planning, predictive planning can help FP&A teams take accurate and appropriate decision-making steps quickly to meet the organization’s long-term financial goals.
Predictive planning is currently one of the most crucial FP&A trends to pay attention to. Over the past year, the unpredictability of world events showed all of us the glaring weaknesses in our FP&A processes and systems.
As a CFO, looking out for only a single scenario is not enough. You need predictive planning to understand these uncertainties better and prepare for risks and opportunities in the future.
What is Predictive Planning?
Predictive planning leverages predictive analytics to make predictions about future events and outcomes using advanced data analytics methods. It is a dynamic, comprehensive, and data-driven approach that supports overall planning and executive decisions.
Strategic planners and financial analysts surpass traditional planning methods by forecasting future outcomes using historical data cycles through machine learning algorithms. With this ability to “see into the future,” FP&A teams forecast mission-critical efforts that impact the business, such as:
- Sales trends
- Consumer behaviors
- Supply and demand
Predictive planning helps your FP&A teams avoid actions that may result in lost opportunities, and instead, stay focused on building better business outcomes. With predictive planning and its evaluative capabilities, you take proactive steps to survive, sustain, and scale in a demanding and quick-moving business context.
Why Do You Need Predictive Planning?
The predictive planning approach considers several internal and external data sources to carry out an educated prediction in real-time when forecasting. Predictive forecasting responds quickly to changes, allowing finance departments to generate, judge, and compare simulations and make precise financial decisions.
Forecasting has a critical position in planning and production in the modern corporate landscape. With predictive planning in place, your planners do not need to rely on external sources or use other complex formulas in Excel spreadsheets for data-driven planning.
Instead, the data-driven predictive analysis lets your FP&A teams confirm, enhance, and review financial decisions, leaving less space for error and more room for valuable and constructive decisions.
Speedy assimilation and flexibility in forecasting further give you the ability to change, react, and manage unexpected factors, increasing the analytical and objective capabilities of your enterprise.
Predictive Planning Benefits
A versatile and dynamic planning module such as predictive planning considers relevant variables to produce fact-based analysis, giving you and your finance teams an upper hand in the decision-making and administrative processes.
Reduce Time: Automated analysis and machine learning algorithms save precious time by analyzing, comparing, and converting data in real-time. Your FP&A teams carry out agile finance predictions by harnessing the true potential of real-time analysis.
Reduce Cost and Effort: The predictive planning approach accommodates cost-effective planning and sourcing while minimizing manual data collection and analysis efforts. This approach helps FP&A teams with financial budgeting, evaluating external suppliers, and deciding internal policies.
Accurate Forecasting: Through the systematic mathematical and statistical analysis, you get an accurate picture of financial data without any blind spots. With relevant historical variables, predictive analytics generates fact-based and reliable sales forecast models that complement judgment calls made by your financial experts.
Campaign Planning: Consumers have more choices today than ever before. If you analyze all the data you have—such as purchasing patterns, buying behaviors, web browsing, and social network interactions—you are able to identify the ideal time and channel to orchestrate a successful campaign. Accurate forecasting will help you avoid wasteful spending and elevate the efforts of your marketing teams as well.
How to Get Started with Predictive Planning
To make sure you generate relevant FP&A insights, you must do predictive analytics right. Here are some of the factors to consider when getting started with predictive planning.
1. Define the Need
Begin by defining the need for the forecast and required enterprise goals. Carefully setting financial objectives will help predictive analytics solutions produce meaningful and actionable insights.
2. Determine Data Volume
Determine the data volume necessary to perform the analysis. Too much granular data will require more processing time to generate insights. Begin with aggregated data that contains enough details to predict seasonality and trends.
3. Cleanse Your Data
Poor quality data will generate less reliable forecasts. Make sure to cleanse your data and remove duplicates for data consistency. Most business intelligence software solutions have data cleansing features.
4. Select a Forecast Horizon
When forecasting, it is essential to select an optimal forecast horizon for accurate predictions. Initiate with a forecast for one month, and gradually examine the accuracy of other months.
5. Choose a Reliable Model
The next important step is to choose a reliable predictive model for accurate analysis. You can also build your own model or choose different tools to automate this process.
6. Test and Validate
Once you have identified the correct model for your analysis, make sure to test and validate it to identify weaknesses. Perform required rectifications with methods like cross-validation to balance the bias and variance of your model.
At Collectiv, we hold expertise in forecasting, progressive and automated planning, budgeting, and reporting solutions. We offer practical and strategic guidance, equipping your FP&A teams with data strategies that lead everyone in the right direction.
We strongly recommend Collectiv’s FP&A visioning program if you need further guidance. This program will shed light on successful strategies and tactics with a tested and validated foundation so your FP&A teams no longer remain scorekeepers and become valued advisors.