Context

The company, in the business of manufacturing high-precision, critical medical components relied on manual and legacy process to analyze data on sales, inventory and quality. Data from multiple sources systems, including their enterprise systems had to be unified for meaningful analysis.

A transformative journey involving automated data analysis, better insights accuracy and real-time analysis was the way ahead. A blueprint was drawn by GainInsights to transition from excel-based reporting to platform-driven explorative insights accessible across teams.

Situation

A leading manufacturer of high-precision, mission-critical medical components faced challenges in analyzing their sales data due to a reliance on manual, Excel-based processes. Limited insights were available, discrepancies were difficult to accommodate, and there was a lack of a centralized system for sales analytics. GainInsights recognized this opportunity and provided a transformative solution that was unified for insights, automated data analysis, improved accuracy, and enabled real-time insights, empowering the manufacturer to make data-driven decisions efficiently.

Solution Overview

GainInsights was engaged from planning to implementing sales dashboards and advanced planning capabilities. The project was planned and run in two phases:

Unifying data from multiple systems with automated data warehousing

Designing for near real-time insights from primary sales and executive dashboards

Key Aspects

Configuring Synapse Analytics for the data warehouse foundation, creating robust data pipelines with Azure services. This includes setup of Azure services on client’s Azure tenant, connecting to source databases, designing data ingestion layers, creating ETL pipelines, and populating data in Synapse Analytics / SQL DW.

Setup to handle exceptions using gateway configurations for incremental data refresh, and providing SOPs for job maintenance and scheduling.

Delivering interactive dashboards on Sales with KPIs including tracking by day, week, month, year, historical trends, customer grouping, salesperson, sales territory, sales against forecast/target, budget vs. actuals and configuring the transactional data for periodic refresh with security rules.

Conclusion

A robust data-platform led approach for unified analytics was transformative for the manufacturer, enabling them to rely on single source of truth and modern analytics to drive predictions, improve procurement decisions and profitability across customers and products.