Implementing data warehouse, business intelligence, and machine learning for an agricultural supply cooperative

Implementing data warehouse, business intelligence, and machine learning for an agricultural supply cooperative

Challenge

Our customer, a major agricultural cooperative wanted to gain clarity around what drives profit for their business. They ran four disparate lines of business: Hazelnut Production, Fuel, Retail, and Farm. Having no way to identify individual business unit performance, the customer sought a means to measure incremental contributions from each line of business. 

The problem, however, was that each line of business kept their data in a silo, and each leveraged different metrics and KPIs, making it a challenge to reconcile and understand what portion of their profit came from each business line. 

The customer also leveraged a Compass data warehouse solution to store transactional information originating from the organization’s point-of-sale (POS) system but faced challenges gaining meaningful insights from this information. As a result, they sought a way to use this information to streamline financial and sales tracking. 

 

Solution

Solution

Neal Analytics worked with the customer to modernize its data warehousing system. In doing this, Neal integrated their data warehouses across the four business units. After integrating the data warehouses, Neal leveraged Power BI to build dashboards that enabled them to visualize and gain more granular insights into their financial records from one place. 

As a part of the data warehouse modernization, the customer also wanted to leverage a Sage ERP solution to track financial transactions. Transactional data originating from their POS system was stored in a Compass data warehouse, requiring a connector to integrate data between the two systems. Neal Analytics assisted with rolling out the Sage ERP and developed a connector to enable the ERP to track POS transactions. Connecting the Sage ERP to the Compass data warehouse allowed them to achieve more timely reporting, helping drive rapid platform adoption.  

 

Result

Result

Thanks to the modern data warehousing environment created by Neal Analytics, the customer realized an increase in sales and business growth. They were also able to streamline product sales, optimize their inventory, and more easily identify and manage sales drivers, leading to increased profitability. 

Thanks to the new Sage ERP, they also gained greater visibility into their financial data, including more granular and timely insights into sales performance. This enabled them to achieve better reporting capabilities, identify which lines of business were performing better than others, and identify trends that might be impacting sales.