Introduction

This content is currently WIP. Diagrams, content, and structure are subject to change.

Introduction

The C3 AI Demand Forecasting application helps organizations predict future demand for products and services. By leveraging time series analysis and basic machine learning algorithms, the application enables businesses to optimize inventory, reduce costs, and improve planning processes.

Key Features in Version 8.6

• Basic Forecasting Algorithms: Standard statistical and ML models for predictions
• Product-level Forecasting: Predictions at individual product level
• Simple External Factors: Basic incorporation of external variables
• Manual Adjustments: Tools for manually adjusting forecasts
• Basic Model Selection: Simple tools for selecting forecasting models
• Standard Reports: Basic reporting capabilities
• Simple Dashboards: Basic visualizations and reports

Key Demand Forecasting Terms

Term	Definition
Time Series	Sequential data points collected over time intervals
Seasonality	Regular and predictable patterns that repeat over time
Forecast Horizon	Future time period for which predictions are made
Forecast Accuracy	Measure of how close predictions are to actual values
External Factors	Variables outside the historical demand that influence future demand
Demand Drivers	Key factors that significantly impact demand patterns
Forecast Adjustment	Manual or automated modifications to statistical forecasts

Getting Started

To get started with the C3 AI Demand Forecasting application, see the following sections:

• Data Model Overview
• Setting Up a Test App
• Application Logic