Strategic Workforce Intelligence Partnership with The Iconic Swoosh Sportswear Brand

Discover How Draup Enabled Global Talent Visibility and Scalable Workforce Planning for a Consumer Lifestyle Brand

677,000+

Employee Count

$46 Bn

Revenue

Athletic Footwear and Apparel

Industry

Beaverton, U.S.

Headquarters

About the Company

A multinational global sportswear industry leader, the company is recognized for its innovation and digital-first approach. The company emphasizes sustainability, design leadership, and a strong omnichannel customer experience as it expands its digital and retail operations. To evolve into a technology-empowered, data-driven enterprise, leadership is focusing on a global workforce strategy, optimizing efficiency, identifying cost-effective hubs, and securing high-quality talent in the Technology, Retail, and Supply Chain sectors.

The Core Challenges

To unify global workforce and talent data across mature and emerging markets.

To balance cost, capability, and proximity while structuring scalable global hubs.

To forecast skill shifts driven by AI, analytics, and automation across digital, retail, and supply chain roles.

To develop predictive, region-specific insights for workforce and location decisions.

The Solution

Supply Chain Analyst

PROFILE

LOCATION ANALYSIS

TALENT MARKET INSIGHTS

CAREER PATHS

DATA INTEGRATION

TECH STACK

The image is for representational purpose only.

Global Talent Intelligence

Benchmarked 13 global hubs to evaluate talent supply, hiring difficulty, costs, and diversity, establishing a three-tier model.

Supply Chain Assessment

Assessed EMEA logistics and procurement talent, confirming mature hubs and highlighting Poland and Hungary as nearshore options.

Retail Talent Insights

Mapped retail and omnichannel talent across South and Southeast Asia, identifying Bangalore and Jakarta as scalable centers.

Tech Operations Analysis

Evaluated tech operations across APAC and LATAM, spotlighting Japan, South Korea, and Mexico for strategic digital roles.

Predictive Workforce Intelligence

Built a unified predictive dashboard integrating hiring difficulty, wage inflation, attrition, and cost modeling for 2027 planning.

Outcome

Evidence-Based Global Workforce Strategy

Established a unified, data-backed workforce model integrating talent supply, cost, competitiveness, and skill depth across mature and emerging hubs.

Optimized Global Hub Structure

Implemented a three-tier framework balancing innovation hubs, operational centers, and nearshore markets to support scalable, cost-efficient global workforce growth.

Enhanced Workforce Agility & Scalability

Enabled dynamic workforce allocation through predictive analytics, reducing time-to-hire and improving deployment efficiency across global functions.

Sustainable Cost Optimization

Achieved significant operational efficiency by leveraging regional cost equivalence, enabling the organization to employ approximately 1.4 FTEs in Europe and 2.3 FTEs in India for every 1 FTE in the U.S.

Powered by unparalleled global labor & market data

23K+

Skills

1B+

Professionals

5700+

Locations

1.6M+

Peer Group Companies

1B+

Job Descriptions

4M+

Career Paths

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.

1

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.

2

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.

3

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. Learn more

4

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.

5

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.

6

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.