Real-time KPI monitoring through a Supply Chain Control Tower

Optimized logistics management by delivering real-time insights on delivery times, product availability, and order accuracy.

Business Scenario

The customer is an American multinational F500 food manufacturing company. They wanted to improve the supply chain reporting processes for essential KPIs such as delivery times, product availability, and order accuracy. Their legacy infrastructure had multiple sources of information scattered across the in-house technology architecture. A centralized repository had to be created to automate the freight cost reconciliation process, aiming to eliminate human errors and reduce processing times. There was a need for data standardization and a governance framework to ensure consistency in sales and logistics data.

Sigmoid Solution

Sigmoid guided the data discovery process and identified necessary datasets to ensure accurate reporting of sales and logistics metrics. We developed automated pipelines to bring data from staging to the business domain layer. The data processing workflow was executed by using a collection of Redshift Stored Procedures. These procedures were activated by calls from AWS Glue Jobs which were triggered on a cron (a time-based job scheduler). We scheduled the jobs using SQL scripts, stored procedures, Glue jobs, and Glue triggers. The reports/KPIs were generated as per pre-defined schedules using the data from the domain layer and the output was stored in Redshift’s datamart tier. This output was used by the visualization team to optimize dashboards for easy interpretation of the data.

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Business Impact

Sigmoid increased automation in the data pipelines to streamline the data processing workflow for the analytics platform, resulting in faster and error-free reporting. The solution identified data that previously eluded Finance analysts in the Freight Recon process, eliminating consistent discrepancies. Implementation of a usable, repeatable, and automated Single Source of Truth (SSOT) with data standardization and governance framework ensured consistency in sales and logistics scorecard data. Additionally, we established a strong foundation for data products that can effortlessly integrate new supply chain use cases.