Transforming workforce strategy for a $91.75B New York based soft-drink giant

Explore How Draup Helps a Top New York Beverage Brand Align Talent with Real-Time Skills Data

~319000

Employees

$91.75B

Revenue

FMCG

Industry

New York, U.S.

Headquarters

About the organization

A global leader in the beverage industry, the company manages a vast and diversified workforce across operations, R&D, marketing, and supply chain. Competing in an increasingly dynamic market, it sought to modernize its talent processes and ensure all roles reflected current, in-demand skills.

The Core Challenges

Skills Drift
To align job content with real-time labor market trends, ensuring each role reflects the latest in-demand skills.
Manual Refresh Cycles
To eliminate manual JD updates by automating skill refresh cycles through dynamic intelligence feeds.
Misaligned Planning
To enhance workforce planning and recruitment efficiency with consistent, market-aligned role definitions.

The Solution

Data Analyst
WORKLOADS TO SKILLS
JOB POSTING TIMELINE
TECH STACK
RESKILLING PROPENSITY INDEX
Reskilling Index
The image is for representational purpose only.
01
Skill Intelligence Feed
Identified real-time skill gaps and emerging market trends across roles and locations to ensure talent insights remained highly relevant and actionable.
02
JD Automation
Enabled fully automated quarterly job description updates using an API-powered skill intelligence feed, reducing manual effort and improving accuracy.
03
Taxonomy Alignment
Mapped the organization’s internal job taxonomy to Draup’s standardized skills ontology to create consistent, market-aligned role definitions across all teams.
04
Execution Speed
Integrated GenAI-driven job description updates directly into Workday, eliminating manual edits and accelerating overall workforce alignment and planning.

Outcome

Automated JD Updates

Eliminated manual refresh cycles, ensuring job descriptions remain current with market skill trends.

Enhanced Candidate Quality

Improved job-to-market fit, driving higher candidate relevance and stronger recruitment outcomes.

Operational Efficiency

Reduced recruiter workload through automation, freeing time for strategic hiring priorities.

Continuous Workforce Evolution

Enabled dynamic alignment between internal roles and the evolving external labor market.
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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