Leading National Equipment Rental Company
600+ legacy Cognos reports rationalized into ~60 modern applications
600+
Reports Rationalized
~60
Apps Delivered
96%
Reduction
Overview
One of the largest equipment rental companies in North America needed to transform an inherited legacy analytics environment into a modern, self-service platform. Evil Genius led a comprehensive rationalization and rebuild — consolidating 600+ static Cognos reports into ~60 purpose-built analytics applications, enabling predictive capabilities for the first time, and fully decommissioning the legacy platform.
The Situation
The client operates a massive fleet of industrial and construction equipment across the US and Canada. Following a spin-off from a larger parent organization, they inherited a legacy IBM Cognos v11 environment originally implemented in 2012. Analytics consisted primarily of static operational reporting — over 600 Cognos reports fed daily by a Teradata enterprise data warehouse. In addition to Cognos, the organization relied on a patchwork of other SaaS and on-prem tools for various operational and financial reporting needs. The data was flowing, but nobody was turning it into insight. Leadership recognized that the company was doing business reporting, not business intelligence — and that had to change.
Our Approach
- 1
Cataloged all 600+ existing Cognos reports, identified redundancy and overlap, and worked directly with business stakeholders to determine what was actually needed versus what was legacy noise. This rationalization consolidated 600+ reports into approximately 60 purpose-built applications — each designed around a specific business function rather than replicating individual legacy reports.
- 2
Designed a modern analytics architecture integrating with the existing Teradata EDW and multiple additional data sources. Implemented proper data modeling, access control, and data security frameworks purpose-built for the organization's needs — not inherited from a parent company.
- 3
Built ~60 analytics applications covering executive dashboards, operational analytics, financial reporting, and fleet planning — including predictive analytics capabilities that didn't exist in the legacy environment.
- 4
Designed and developed a modern customer-facing reporting portal, transforming the client's external analytics experience from a dated legacy interface into a leading-edge interactive experience.
- 5
Delivered comprehensive training and implemented source control practices to ensure the internal team could maintain, extend, and govern the new environment independently. The goal was lasting self-sufficiency, not ongoing dependency.
Results
- 600+ legacy Cognos reports rationalized and consolidated — not migrated, transformed
- ~60 purpose-built analytics applications delivered across executive, operational, financial, and fleet functions
- 96% report reduction through intelligent consolidation, not just cleanup
- Cognos fully decommissioned — complete legacy platform sunset
- Self-service business intelligence enabled across the organization for the first time
- Predictive analytics and augmented intelligence capabilities deployed for fleet planning and operations
- Multiple disconnected reporting tools consolidated onto a single governed platform
- Customer-facing reporting portal modernized, turning analytics into a competitive differentiator
- Data governance, source control, and access security frameworks established for the organization's specific needs
- Internal team trained and fully self-sufficient — no ongoing consulting dependency
What This Made Possible
The client went from an inherited, legacy reporting environment to a modern, governed analytics platform purpose-built for their business. Self-service capability empowered business users for the first time. Predictive analytics opened entirely new operational possibilities in fleet planning and maintenance optimization. And by rationalizing 600+ reports down to ~60 focused applications, the organization eliminated years of accumulated sprawl — building exactly the kind of clean, well-governed analytics foundation that positions them for AI and machine learning when they're ready.
Facing a Similar Challenge?
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