Introduction¶
Creating an accurate demand plan is a crucial task for demand planners. It requires them to analyze the sales history of prior models or similar products to forecast the demand accurately. With the latest update of AWS Supply Chain Demand Planning, demand planners can now establish links between products and their predecessor versions or alternate products, incorporating rules around the extent of history to be used for forecasting purposes. This feature, known as Product Lineage, allows AWS Supply Chain Demand Planning to generate a ‘surrogate history’ for the product, resulting in more precise demand predictions. This guide will delve into the details of AWS Supply Chain Demand Planning, focusing on the newly added support for Product Lineage.
The Importance of Product Lineage in Demand Planning¶
Including sales history of prior models or similar products in demand planning contributes to the accuracy of forecasting. However, without a formalized mechanism to establish connections between products and their precursor versions, demand planning might lack precision. Product Lineage in AWS Supply Chain Demand Planning offers a solution to this challenge. By linking products and their predecessor versions or alternate products, demand planners can ensure that the forecast generated through lineage history is inherently more precise, minimizing the need for manual adjustments. This saves time and effort and enhances the overall efficiency of the demand planning process.
Leveraging Product Lineage in AWS Supply Chain Demand Planning¶
AWS Supply Chain Demand Planning provides a user-friendly interface to leverage the Product Lineage feature effectively. This section will explore the steps and considerations involved in utilizing Product Lineage.
1. Defining Product Lineage Rules¶
To get started, demand planners need to establish rules around the extent of history to be used for forecasting purposes. These rules will determine the linkages between products and their predecessor versions or alternate products. By defining these rules, demand planners can ensure the accuracy and relevance of the lineage history used for generating forecasts.
2. Establishing Links between Products¶
Once the product lineage rules are defined, demand planners can establish links between products and their predecessor versions or alternate products. This step involves identifying the relationships between different products and recording them in the AWS Supply Chain Demand Planning system. These links will be utilized to create the surrogate history for forecasting.
3. Generating Surrogate History¶
With the defined product lineage rules and established links between products, AWS Supply Chain Demand Planning will automatically generate a surrogate history for each product. This surrogate history forms the basis for demand predictions. By incorporating the actual sales history of prior models or similar products, the generated forecast becomes more accurate and reliable.
4. Visual Indicator for Lineage Forecasts¶
To identify forecasts generated using lineage history, AWS Supply Chain Demand Planning provides a distinct indicator on the user interface. This indicator notifies demand planners when a forecast has been created using the lineage history. This feature enables demand planners to easily differentiate between forecasts derived from lineage and regular forecasting models.
Technical Considerations¶
AWS Supply Chain Demand Planning’s support for Product Lineage encompasses various technical considerations. This section will highlight some of the key technical points that demand planners should be aware of.
1. Data Integration and Lineage Updates¶
To ensure the accuracy of lineage forecasts, it is crucial to maintain up-to-date information about product relationships and their respective sales histories. Demand planners should establish a data integration process that keeps the lineage data synchronized with any changes in the product portfolio or sales history. This synchronization ensures that the surrogate history used for forecasting is always reflective of the latest information.
2. Algorithm Optimization¶
AWS Supply Chain Demand Planning employs sophisticated forecasting algorithms to generate demand predictions. With the inclusion of Product Lineage, additional optimization is required to enhance the accuracy of lineage forecasts. Demand planners should explore the various algorithm options available in AWS Supply Chain Demand Planning to select the most suitable algorithm for their specific use case.
3. Scalability and Performance¶
As demand planners increasingly rely on Product Lineage for accurate forecasting, the scalability and performance of AWS Supply Chain Demand Planning become crucial. Demand planners should ensure that the system can handle the increased computational demands and processing load associated with generating lineage forecasts. Regular monitoring, capacity planning, and optimization measures should be implemented to maintain a high-performing and scalable demand planning environment.
Benefits of Leveraging Product Lineage in Demand Planning¶
The integration of Product Lineage into AWS Supply Chain Demand Planning offers several notable benefits to demand planners. This section will discuss some of the key advantages that demand planners can expect when leveraging Product Lineage.
1. Increased Forecast Accuracy¶
By incorporating the sales history of prior models or similar products, Product Lineage improves the accuracy of demand predictions. The surrogate history generated using lineage ensures that the forecast aligns closely with past sales patterns, resulting in more precise forecasting outcomes.
2. Reduced Manual Adjustments¶
With the improved accuracy of lineage forecasts, demand planners can reduce the need for manual adjustments to the generated forecasts. This saves time and effort, enabling demand planners to focus on higher-value strategic activities rather than tedious manual adjustments.
3. Enhanced Decision-Making¶
Accurate demand predictions empower demand planners to make informed decisions regarding inventory management, production planning, and supply chain optimization. By leveraging Product Lineage, demand planners can enhance their decision-making processes and drive better business outcomes.
Conclusion¶
In conclusion, the support for Product Lineage in AWS Supply Chain Demand Planning provides demand planners with a powerful tool to enhance the accuracy of demand predictions. By establishing links between products and their predecessor versions or alternate products, demand planners can generate lineage forecasts that closely align with past sales patterns. This guide has explored the various aspects of AWS Supply Chain Demand Planning’s support for Product Lineage, focusing on the technical considerations and benefits for demand planners. By utilizing the Product Lineage feature effectively, demand planners can streamline their demand planning processes, save time and effort, and ultimately make more informed decisions to optimize their supply chain and achieve business success.