Case Study | Retail & CPG
The client is an American multinational beauty company that develops, manufactures, markets, and distributes fragrances, cosmetics, skincare, nail care, and professional and retail hair care products.
With growth and innovation at the center, the client always stays invested in looking for ways to modernize its reporting platforms and help its businesses succeed by speeding up the decision-making process.
Being one of the leading retailers in the beauty industry, the client is looking forward to implementing a modern self-service BI platform with advanced analytics capabilities. Hence, the client aims to take its operations to the next level and decommission the existing traditional reporting systems on SAPBW/4HANA to encourage data democratization.
The client chose Brillio as the key partner to power real-time decision-making through plug-n-play visualization. Brillio enabled the client’s vision with expertly-designed advanced analytics capabilities and rendered traditional reporting systems obsolete. With best-in-class Engineering practices, technology, and skillsets, Brillio helped the client achieve its goal of self-service analytics and financial value predictions.
The entire Brillio transformation has enabled the client’s business to make faster decisions and predict financial values.
Here is the approach followed:
Experts at Brillio started with an as-is analysis of the current business situation and the creation of an implementation roadmap for the identified business use-cases like PBI scorecard, Gucci, and SKU rationalization.
Brillio took a sprint-based agile approach with mock-up, whiteboarding, and dashboard designs.
Experts at Brillio implemented a Cash Collection Estimation model for forecasting the future payments of due receivables, deployed in Databricks ML runtime.
As there were complex calculations of the PBI view, the Brillio team pushed it to the Azure SQL Database, resulting in much faster loading of the views.
Following Brillio’s implementation, the client was able to achieve the goal of powering real-time decision-making and financial value predictions.