Business Challenge

A collection of coordinated supply chain planning tools that aim to improve service, inventory, and cost efficiency. These tools utilize existing global license agreements (BY or SAP) and proven in-house developed tools to reduce ongoing maintenance expenses and streamline support.

Standardizing business processes across the organization to align with a global template, as implemented by Blue Yonder (BY) in accordance with the ISCP guidelines. Facilitating the ability to utilize various historical data sources, such as shipments and sales orders, based on specific market needs.

Cloudseed Solution

Parameterization allows for customized solutions to be implemented, ensuring that data processing is tailored to the specific needs of each market. This includes adjusting input received based on market requirements and maintaining consistency in unit of measure through the use of parameterization.

The system will maintain multiple history streams and direct them to the main tables in BY, with the flow determined by the history stream selected for statistical generation. This allows the markets to have a comprehensive view of all available streams while generating statistics on the chosen history stream. Additionally, a custom solution has been implemented to create a SKU code (ZSKU) in BY using market-specific rulesets.

Benefits to Customer

Businesses can access data based on their preferred hierarchy, allowing for greater flexibility and convenience. Additionally, businesses can work with units of measure that are commonly used in their specific region. Users are also able to view their historical data across all streams, which aids in the process of cleaning historical data for statistical analysis.

The demand planners are now emphasizing on forecasting at the product level, disregarding any changes in the finished goods code that may occur as a result of price or grammage variations over time. This approach has led to an improvement in forecast accuracy, which currently stands at around the mid 60s. We are now working on implementing demand modeling techniques to further refine and optimize our forecasting model.