Driving Workforce Strategy & GenAI Insights for a $64.9B Dublin based IT services powerhouse

Learn How Draup Powers Peer Benchmarking, Skill Intelligence & Leadership Research

~801000

Employees

$64.9B

Revenue

Professional IT Services

Industry

Dublin, Ireland

Headquarters

About the organization

The company is a leading global consulting firm, supporting enterprises across multiple industries with strategic advisory, technology solutions, and workforce insights. To maintain its competitive edge, the firm continuously seeks better methods to benchmark talent, plan workforce strategies, and conduct thought leadership research, including emerging areas like GenAI adoption.

The Core Challenges

Fragmented Benchmarking
To benchmark peers globally with granularity across functions (Sales, HR, Supply Chain) and locations.
Disconnected Talent Data
To consolidate workforce intelligence into actionable insights for EVP and talent strategy comparisons.
Reactive Skills Research
To support high-impact leadership research on emerging skills and workforce transformation trends.

The Solution

Data Engineer in United States
SKILLS INTELLIGENCE
PEER INTELLIGENCE
GEN AI USE CASES
The image is for representational purpose only.
01
Peer Benchmarking
Provided detailed hiring distribution and EVP comparisons across global peers
02
Skill Intelligence
Delivered skill-level insights to support workforce planning and talent acquisition
03
Leadership Research
Enabled research on emerging trends such as GenAI adoption in IT, R&D, and marketing
04
Execution Speed
Facilitated on-demand, API-based data delivery integrated with internal dashboards for faster analysis

Outcome

Precision Benchmarking

Published high-accuracy peer comparison studies and internal leadership reports.

Enhanced EVP Insights

Developed battle cards and talent heatmaps for strategic decision-making.

Thought Leadership on GenAI

Analyzed AI-related skill demand trends to position the firm as a knowledge leader.

Efficient Workforce Research

Streamlined access to real-time and historical data, eliminating manual consolidation.
6,100+​
Locations
4M+​
Career Paths​
1.7M+​
Peer Group Companies​
28K+
Skills
3,500+​
Roles
1B+​
Professionals​
55K+​
Universities​
1B+​
Job Descriptions​
200K+​
Courses​
180K+​
Technology Solutions​
1.6M+​
Account Priorities​
Labor Market Data Contextualized with Business Intelligence for Every Decision

Analyzing 1B+ data points
daily from 100K+ sources

6,100+​
Locations
4M+​
Career Paths​
1.7M+​
Peer Group Companies​
28K+
Skills
3,500+​
Roles
1B+​
Professionals​
55K+​
Universities​
1B+​
Job Descriptions​
200K+​
Courses​
180K+​
Technology Solutions​
1.6M+​
Account Priorities​
AICPA SOC2 TYPE 2
SOC 2
GDPR Logo
GDPR
ISO 27001 Logo
ISO
EAIGG Logo
EAIGG

Ethical AI, Backed by Global Standards

Draup, an AI-first company, upholds global standards like SOC 2, GDPR, and ISO 27001. As an EAIGG member, we audit for bias and build trustworthy AI.

Data Trust &
Methodology
at Draup

Draup uses a structured methodology to reduce inaccuracies and prevent misleading information, with a focus on transparency and responsible data practices.

Data Transparency and Coverage

Draup sources data from diverse, vetted global inputs including public datasets, labor information, professional ecosystems, and industry research. Coverage varies by region and role, and we supplement limited areas with alternative sources and analyst-led modeling.

Profiles Behind the Numbers

All aggregate insights related to buyers, roles, skills, and locations are grounded in structured, anonymized human and organizational profiles rather than pure extrapolation. This ensures context, reliability, and protection of personal identities.

Data Hygiene and Integrity

We maintain a clean, accurate data environment by removing duplicates, outdated entities, and invalid records. Automated checks powered by ML models and analyst reviews work together to ensure clarity and accuracy for every entity, such as buyer, role, skill, technology, or company.

AI Governance and Bias Mitigation

Our governance framework combines automated evaluations with Human-in-the-Loop reviews. We use statistical checks, audits, and cross-source comparisons to reduce demographic and structural bias before insights reach the platform.

Compensation Guardrails

Compensation insights use blended, directional inputs such as aggregated ranges, benchmarks, modeled distributions, and market signals. We distinguish clearly between modeled and reported data and apply guardrails to prevent over-interpretation.

Hourly and Frontline Workforce Coverage

For hourly, frontline, and blue-collar roles where digital visibility is limited, we incorporate government datasets, localized labor information, and specialized partners to build a more complete and balanced view of workforce supply and demand.

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