Title

AWS re:Invent 2023 - Plan for better results (BIZ111)

Summary

Vikram Balasubramanian, a Senior Solutions Architect for AWS Supply Chain, presented the demand planning capabilities of AWS Supply Chain.
The session covered setting up a demand plan, including defining the planning horizon, granularity, and product hierarchy with up to 10 levels.
Alternate hierarchies such as site, channel, and customer dimensions can be modeled for nuanced planning.
The application allows for data quality control, handling negative values, and setting initial forecast values for new products.
Demand planners can control the start and end timeline for product launches and set automated or manual modes for publishing demand plans.
The output of the demand plan is available in an S3 bucket for downstream system integration or sharing.
AWS Supply Chain uses machine learning capabilities, leveraging Amazon.com's experience, to generate accurate forecasts and identify influence factors.
Forecast accuracy metrics are provided for self-evaluation, and the application allows for real-time interaction and adjustments based on external inputs.
An audit trail is maintained for changes made to the forecast for accountability and future learning.
The session concluded with a demonstration of publishing the final demand plan to a downstream system.

AWS Supply Chain's demand planning tool is designed to be flexible and user-friendly, allowing demand planners to easily define and adjust their demand forecasts.
The tool's ability to model up to 10 levels of product hierarchy and incorporate alternate dimensions like site, channel, and customer provides a comprehensive approach to demand planning.
Data quality control features within the application ensure that planners can trust the integrity of the forecast by managing how input data is treated.
Machine learning algorithms are a core component of the AWS Supply Chain demand planning tool, indicating AWS's commitment to incorporating advanced technologies for better forecasting accuracy.
The integration of an audit trail for forecast adjustments highlights the importance of transparency and traceability in demand planning processes.
The ability to publish demand plans to an S3 bucket demonstrates AWS's focus on seamless integration with other systems and ease of sharing information across an organization.
The session's emphasis on real-time interaction with the forecast and the ability to respond to external events, such as promotions, shows the tool's agility in adapting to dynamic business environments.