Predictive Planning
What is Predictive Planning exactly?
Predictive planning/modeling is not AI.
Predictive planning is a form of machine learning that generates budgets or forecasts by analyzing both internal and external data organized across a series of time periods.
Predictive planning serves as one key tool within a broader AI solution framework that organizations deploy to modernize their finance functions.
Effective predictive models should address:
- Driver selection and identification
- Outlier identification and removal
- What-if modeling
Different model types will employ varied approaches to handle both supervised and unsupervised predictions.
As with broader AI implementations, success hinges on clearly identifying the process and carefully curating the input data.
The above steps largely determine the quality of the outputs from any predictive model. A strong grasp of materiality and level of detail is essential, as excessive granularity introduces significant noise that degrades prediction quality.
When should predictive models be implemented?
Predictive models should be implemented once an organization has mastered and rationalized their driver-based budgeting and forecasting processes.
Predictive Planning is the next logical step once an organization is comfortable with:
- Statistical modeling
- Identifying causal drivers
- Advanced time-series and regression-based trending
It is important to note that a predictive planning engine is not AI, but instead is part of an overall solution architecture which AI agents will use to help iterate through processes.
AI agents can and should be used to pass parameters and execute a variety of statistical models and execute what-if analysis, but the models themselves should be established before AI agents are implemented.
The overall design of your predictive solution will need to incorporate feedback to/from AI agents, a proper design should incorporate a variety of control tables to allow for iterating through a variety of datasets based on parameter driven approaches.
Expect to update your predictive modeling solution once it is stable to incorporate AI agent driven modeling.
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