Create a scalable solution that can be applied across brands and regions to study the efficacy and efficiency of trade promotion spends in conjunction with a simulated environment in order to determine an efficient TO-BE state.

1. The current process is highly complex and non-transparent owing to increased competition, fragmented consumer segments, different trade terms with every retailer, non-binding agreements, and varying agreement structures.

2. Solutions built are custom to a certain region or brand and are difficult to replicate.

3. Data access and security

4. Time for execution

1. Multiple data sources (internal and external) are ingested and analyzed to develop a strong foundation of the current state.

2. Combination of on-premise and cloud elements to ensure scalability and region-specific access control

3. Use ML as a web service for faster code deployment and future enhancements.

1. Accurate quantification of your organic sales to create a baseline

2. Advanced ML algorithms to simulate the incremental impact of your trade promotion management initiatives

3. Enterprise-grade TPM tool capable of handling millions of SKUs

4. Best-in-class baseline models with granularity of SKU/customer level

This implementation uses the following native Azure components:

ADF pipelines, ADLS Gen 2, Azure SQL Database, Azure ML, and Power BI