The first step was to create a supply chain data lake, enabled by Genpact Cora, our AI-based digital business platform hosted on AWS. This data warehouse encompasses 32 different data sources on which to base demand forecasts. A decision support engine applies domain algorithms, artificial neural networks to detect demand, and text mining on promotion records to the data lake to identify regularities, relationships, and patterns between demand variables, including the impact of special events such as promotions.
The supply chain HUB then provides data visualization and alerts. Hierarchy and role-driven dashboards provide easy data drill-down for review and monitoring, and integrated insights provide each stakeholder with a real-time view across the supply chain. We helped Panasonic redefine its decision-making metrics and KPIs to ensure that supply chain decisions support overall company goals.
Finally, we designed a new agile operating model that supports agility rather than efficiency (Figure 2). A managed services desk for analytics, data management, and infrastructure now provides sophisticated analysis of the improved data and a quicker response to market fluctuations. The inventory forecasting model now operates on an intelligent planning platform that uses sell-through data – a more accurate measure of end-customer demand than sell-in data. This means more accurate demand modeling and improved trade promotions such as discounting and bundling.
We worked closely with the Panasonic team throughout. Regular meetings with stakeholders, including sales teams and product managers, were held during the transition period to discuss progress and the processes being developed.