Case Study

12,000 Employees. Siloed Data. One Intelligent Workforce Platform.

How we helped a global enterprise transform resource allocation from reactive firefighting to predictive optimization — achieving 30% cost reduction while improving employee satisfaction to 95%.

Before — The Challenge

Growing Workforce. Shrinking Visibility.

The situation: A global technology company with 12,000+ employees across 14 countries. Headcount had grown 40% in three years, but productivity per employee had flatlined. Project delays were increasing. Talent was being misallocated. And nobody had a complete picture of workforce capacity.

The operational reality:

Resource allocation was managed through 47 different spreadsheets
Managers hoarded talent to protect their teams from being reassigned
Skills data existed in HR systems that nobody used for planning
Contractors were hired to fill gaps that internal talent could have addressed
High performers were overloaded while others were underutilized

What they'd attempted:

Implemented a resource management tool that was abandoned within 6 months
Hired consultants to do a "workforce study" — 200 pages, no action
Created a "capacity planning team" that became a bottleneck

"Every project felt understaffed, yet we kept hiring. Either we had a talent problem or a visibility problem — we couldn't tell which."

The Shift — Our Approach

We Stopped Looking at Headcount. We Started Seeing Capacity.

Our engagement model: We didn't start with technology. We spent the first three weeks shadowing project managers, sitting in resource allocation meetings, and mapping the actual decision-making process. What we found wasn't a skills gap — it was an information gap.

The Key Insight

42% of workforce capacity was invisible to decision-makers. People weren't overworked — they were misallocated. The problem wasn't headcount; it was matchmaking between skills, availability, and demand.

What made this approach different:

Reinforcement learning models that predicted resource demand 8 weeks ahead
Skills inference from project history — not just what HR had on file
Real-time capacity visualization that managers actually trusted
Recommendation engine that suggested optimal team compositions
Fairness constraints to prevent burnout on high performers

The turning point: When we showed leadership that 23% of their contractor spend could be replaced with existing internal talent — properly allocated — the conversation shifted from skepticism to urgency.

Week 1-3

Discovery & process mapping

Month 2

Data integration & ML models

Month 3-4

Pilot with 3 departments

Month 5-8

Enterprise rollout

The Workforce Intelligence Platform

A unified view that replaced 47 spreadsheets and gave leaders real-time visibility.

📊 Resource Utilization Before vs After

📈 Efficiency Trend Over Time

🎯

89%

Skill Match Accuracy

⚡

4.2x

Faster Resource Allocation

💰

$8.4M

Annual Contractor Savings

After — The Results

From Firefighting to Forward Planning.

The business impact:

20% efficiency gain — same headcount, higher output
15% faster project delivery — right people assigned from day one
95% employee satisfaction — up from 68%, driven by better workload balance
30% cost reduction — $12M annually from optimized allocation
$8.4M contractor savings — internal talent utilized first

The operational transformation:

Resource allocation decisions reduced from 2 weeks to 2 days
Managers stopped hoarding talent — visibility created trust
Skills development became strategic, based on predicted demand
Executive dashboards replaced monthly PowerPoint marathons

The Multiplier Effect

When people work on projects that match their skills and interests, productivity rises without increasing hours. The ROI came from alignment, not acceleration.

"For years, we thought we had a hiring problem. FyreOps showed us we had a visibility problem. Now our workforce works smarter, not harder — and our people actually enjoy coming to work."

Jennifer Martinez — Chief People Officer, Global Technology Enterprise