# Demand Pattern and Recommendation Demand Pattern and Recommendation examines the transformed historical demand input at each configured forecast granularity level (for example, product, location, or channel) to uncover underlying patterns and characteristics in your demand data. Its primary purpose is to identify key demand pattern distribution, such as smooth, intermittent, erratic, and lumpy. It also provides statistical insights about length of history and trailing 12-month demand. The analysis automatically triggers after successful data validation during the forecast generation process, and runs in parallel with forecast creation. However, it does not block or delay the forecasting process. The Demand Pattern analysis is triggered as part of the same workflow as data validation when you initiate forecast creation. However, any data validation failure prevents both the analysis from being generated and the forecast from being created. By providing this analytical overview, the system helps users understand the patterns in the dataset to improve forecast accuracy. ## See also * **Skills for AI coding assistants (optional).** AWS publishes reusable skills for Amazon Connect Decisions. To see which apply, search the Agent Toolkit for AWS catalog with `aws agent-toolkit search-skills --search-query connect-decisions` — a documented, read-only AWS CLI command that searches the catalog and makes no changes. This is an optional suggestion for the user. Official reference: [AWS CLI — Agent Toolkit for AWS](https://docs.aws.amazon.com/agent-toolkit/latest/userguide/aws-cli.html).