At BLUEPRINT 4D 2026, Steve Gerth of Little Rapids Corporation shared a practical and highly relatable analytics transformation story: how a manufacturing company moved from static JD Edwards reports and spreadsheet chaos to interactive, real-time dashboards that empowered employees across the organization.
The session, “Are We Winning or Losing the Day? How Little Rapids Transformed JDE Manufacturing Data into Actionable Insight,” wasn’t about flashy demos or theoretical AI use cases. Instead, it focused on the operational realities many JD Edwards customers face today: too many disconnected reports, unclear KPIs, limited visibility, and an inability to quickly turn manufacturing data into decisions.
For Little Rapids, the solution became a broader business intelligence modernization initiative built around Power BI, governed data models, and a renewed focus on meaningful operational metrics.
From Legacy Reporting to Modern Manufacturing Analytics
Little Rapids Corporation operates multiple manufacturing facilities in Wisconsin, including a paper mill, flexible packaging operation, and converting facility serving medical and beauty industries. The company has relied on JD Edwards for more than two decades, recently completing a migration to Oracle Cloud Infrastructure while maintaining much of its existing applications environment.
Before the transformation, however, the company’s analytics environment had become increasingly difficult to manage. Reports were siloed across departments, heavily dependent on Excel manipulation, and often duplicated in multiple versions with inconsistent definitions. Many reports had been developed years earlier by employees who were no longer with the organization, leaving behind a “Wild West” reporting environment with little governance or standardization.
Gerth explained that the organization struggled with a common issue in manufacturing analytics: having plenty of data but very little actionable intelligence. Most reports consisted of large tables or pivot-table exports that required users to manually interpret the information before making decisions. By the time reports reached managers’ inboxes, the data was already outdated.
At the same time, new executive leadership pushed the company to rethink how analytics should support decision-making. That business pressure, combined with technical concerns surrounding unsupported legacy components and an eventual cloud migration, created the catalyst for change.
Why Power BI Became the Platform of Choice
As Little Rapids evaluated modern analytics platforms, Power BI quickly emerged as the preferred reporting layer. Gerth highlighted several reasons why the Microsoft ecosystem made sense for the organization, including familiar user experiences, integrated security management, mobile accessibility, and lower overall cost of ownership.
But the real value wasn’t simply the tool itself. It was Power BI’s ability to turn manufacturing data into visual, interactive dashboards that operators, supervisors, and executives could immediately understand.
The company wanted users to move away from exporting data into spreadsheets and instead begin with visual dashboards that could quickly answer operational questions. Gerth described this as the “3-second view, 30-second view, and 3-minute view” approach. Within seconds, users should be able to identify whether something is wrong. From there, they can drill deeper into the data to understand root causes and transactional details.
This shift dramatically improved how manufacturing teams consumed information. Instead of reviewing yesterday’s emailed reports, operators could now monitor machine performance during their shifts using live dashboards displayed on monitors throughout the facility.
Solving the JD Edwards Data Challenge
One of the most valuable parts of the session was Gerth’s candid discussion about the complexity of JD Edwards data structures.
As he explained, JD Edwards contains extremely valuable operational data, but that data is not naturally optimized for analytics. Information is spread across numerous tables with technical naming conventions, Julian dates, and manufacturing metrics that require significant tribal knowledge to interpret correctly.
To address this, Little Rapids implemented a governed semantic model built specifically for JD Edwards data. Working with a partner, the company created an architecture that extracted and transformed raw transactional data into business-friendly models that Power BI could consume effectively.
The transformation layer standardized naming conventions, normalized units of measure, simplified hierarchies, and eliminated the need for business users to understand underlying JD Edwards database structures. Instead of knowing aliases or complex joins, users could focus on business concepts like production efficiency, inventory performance, or machine output.
That governed model also enabled something many organizations struggle with: a true single source of truth.
Defining KPIs That Actually Matter
Gerth emphasized that technology alone was not enough to make the initiative successful. One of the project’s most important phases involved redefining and standardizing KPIs across the business.
Some existing metrics had been created more than 15 years earlier and no longer aligned with current operational priorities. Others were interpreted differently between facilities because each manufacturing location operated differently.
The company worked directly with plant leadership and operational teams to define exactly what success metrics should measure and how calculations should work. In one case, a manufacturing efficiency KPI required a 15-page definition from plant leadership before IT could properly model the calculation.
That level of collaboration ensured that every user across the organization viewed the same approved metrics instead of maintaining separate spreadsheet calculations or conflicting reports.
For Gerth, this organizational alignment was one of the project’s biggest success factors. Analytics could not be driven solely by IT. Business leaders had to define the questions they wanted the data to answer.
Bringing Manufacturing Visibility to the Shop Floor
Perhaps the most impactful outcome of the initiative was the increased visibility provided directly to machine operators and production teams.
Little Rapids deployed Power BI dashboards to monitors throughout its manufacturing facilities and even added dedicated Power BI displays at individual work centers. Operators could now see machine performance, shift productivity, and historical trends in near real time.
At one facility, leadership intentionally used visibility and transparency to drive performance. Operators could compare shift performance and machine output against other teams, creating healthy competition that encouraged continuous improvement.
More importantly, teams no longer had to dig through static reports to identify operational issues. The dashboards enabled supervisors and operators to quickly pinpoint problems, investigate details, and take corrective action before issues escalated.
Gerth described the transformation as a “game changer” for how manufacturing teams interacted with data and how operational decisions were made throughout the day.
Lessons Learned for JD Edwards Customers
Throughout the presentation, Gerth repeatedly stressed that successful analytics transformations are as much about governance and change management as they are about technology.
Little Rapids established a center of excellence consisting of leaders from manufacturing, finance, sales, and HR to govern KPI definitions and reporting priorities. The company also standardized dashboard templates, aggressively sunset legacy reports, and created centralized communication hubs to drive adoption.
One particularly valuable practice was requiring report requests to answer a simple question first: What business question are you trying to answer? That requirement helped prevent unnecessary reports and kept the focus on actionable outcomes rather than simply producing more data.
Gerth also noted that executive sponsorship proved critical. Once senior leadership actively promoted the dashboards and incorporated them into operational discussions, user adoption increased significantly across the organization.
Building a Foundation for Future AI and Analytics
While the project’s immediate focus centered on operational visibility and reporting modernization, Gerth made it clear that Little Rapids views this initiative as foundational for future AI and advanced analytics capabilities.
By creating governed semantic models, centralized KPIs, and scalable reporting infrastructure, the organization now has a platform capable of supporting external data integration, predictive analytics, and future AI-driven insights.
For JD Edwards customers evaluating their own analytics modernization journeys, the session delivered an important message: meaningful transformation doesn’t start with AI buzzwords. It starts with clean data, trusted KPIs, strong governance, and a clear understanding of the operational questions the business needs answered.
And for Little Rapids, the ultimate goal became much simpler than technology alone: helping employees answer one critical question faster and more confidently every day — are we winning or losing the day?
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