Accelerating ERP Reporting and Insights with a Data-Centric Approach

JMA Resources Staff
May 7
2 min read

For a major DoD command, getting timely, reliable insights from their SAP ERP system had become a challenge in itself. Data tables weren’t structured for flexibility, and even small updates to a single field often took weeks or longer. Reporting processes were slow, costly, and difficult to maintain, leaving mission-critical decisions waiting on outdated information. The command needed a better way to build and adapt reports, one that could evolve with the pace of their operations.

JMA Resources Clients in their office during an all hands meeting talking about new the data reporting system that JMA Resources installed

JMA’s Approach

We brought in a solution grounded in one of our core strengths: reimagining data environments through smart architecture and data-centric design.

Building a Flexible, Modern Foundation

To improve responsiveness and data integration, we implemented Business Analytics for SAP ERP Data. Leveraging IBM PureData (later transitioned to Yellowbrick), SAP Business Objects, and a suite of tools including Qlik Replicate and ELT Maestro, we created an enterprise data warehouse (EDW) that could replicate ERP data in near real-time.

But the real innovation came in the architecture. Instead of building rigid tables tied to front-end reporting layers, our team used a data-centric modeling approach. We organized backend data in a way that made it easier to update and scale. This meant reporting elements could be changed quickly and consistently across systems, slashing turnaround times.

Connecting the Dots Across Systems

We also designed the EDW to support integration with both SAP and non-SAP systems creating a unified view of logistics and operations. That comprehensive picture gave users faster access to the insights they needed, when they needed them.

Results and Impact

Faster, Smarter Reporting

Where report changes once took months, they now take weeks and even days. The improved agility means users can respond to operational needs faster and make data-informed decisions in real time.

A Unified Data Ecosystem

By consolidating data marts into centralized EDWs, we reduced maintenance burdens and licensing costs while giving our client a more complete and connected view of their logistics data.

Clear Lineage, Trusted Data

Standardizing data elements and ensuring clear lineage has strengthened data governance, giving users confidence in their reporting tools and the insights they provide.

Future-Ready Flexibility

The architecture was designed to grow with the mission. As new platforms, tools, and needs arise, the EDW can evolve alongside them without needing to start from scratch.