Workforce Getting Obsolete? Use Multi-Dimensional Labor Market Data to Get Future-Ready

Enterprises are confronting a stark reality: their workforce planning is no longer keeping up with the rapid evolution of required skills, market dynamics, and increasing competition for talent. HR leaders admit their current workforce planning strategies are inadequate to meet future demands. 

With 58% of HR leaders struggling to address evolving skill requirements and 40% of businesses unable to fill critical roles, the misalignment between workforce capabilities and business goals is hindering growth. 

The key challenge here is the “Widening Skills Gap” 

A Data-Driven Solution: Leveraging Multi-Dimensional Labor Market Insights 

The solution to bridge the skills gap lies in using multi-dimensional labor market data to drive skills based workforce planning strategies.  

This data provides real-time insights into skill trends, job evolution, and talent dynamics, enabling teams to anticipate shortages, align strategies with business goals, and retain talent. Precise talent mapping significantly enhances skills based workforce planning assessment. 

Skills Based Workforce Planning Powered by Labor Market Data 

Keeping track of labor market data and having your finger on the pulse of how skills, roles, talent supply and demand and even location hotspots are evolving can give you an edge in building a skills based workforce planning framework.  

In 2025, focus on 3 aspects of how labor market data is powering skills based workforce planning –  

1. Deep Analysis of Emerging Skill and Role Trends:

   Understanding emerging skill dynamics is essential for skills based workforce planning, requiring organizations to track not only in-demand skills but also their evolution and integration into key business initiatives. This analysis enables proactive, skills based workforce planning.

Multi-layered Skills Data – The Edge 

 Niche, new-age skills are increasingly expensive to onboard, due to the supply demand mismatch. For example, an e-commerce company faced significant challenges in hiring a Natural Language Processing (NLP) expert to enhance its chatbot, as the demand for data science professionals has surged in the past five years, driving salary expectations up by as much as 40% due to the supply-demand gap.  

Organizations leveraging multi-layered global skills data can: 

• Anticipate emerging skill premiums before they impact hiring costs 
• Develop competitive compensation strategies that attract and retain key talent 
• Create targeted upskilling programs focused on high-value capabilities 
• Build talent pipelines for future critical roles before shortages become acute 

 

Through skills based workforce planning, these strategies enable organizations to meet evolving business needs effectively. 

Role Transformation Mapping 

The evolution of multi-tasking, hybrid roles represent a fundamental shift to skills based workforce planning requirements. New-age roles demand integration of technical expertise, business acumen, and interpersonal capabilities.  

This hybrid approach: 

• Creates more versatile and adaptable employees
• Reduces talent acquisition costs through internal development
• Improves organizational resilience against market changes
• Enables faster response to emerging business opportunities

2.Talent Demand and Supply Dynamics :

Understand and address talent surpluses, gaps, and region-specific trends to align skill-based workforce planning capabilities with business needs by:

• Optimizing Talent Sourcing and Deployment – Use real-time data to identify global talent hotspots, enabling cost-effective hiring from regions rich in skilled workers. Example, hire software developers from emerging tech hubs like India to meet the increasing demand for AI and machine learning expertise.
• Monitoring Sector-Specific Skills Trends – Track industry trends in real time to anticipate and meet rising sector demands. Focused talent acquisition bridges skill gaps and ensures access to top expertise. Like, if you are a technology provider, monitor and address the growing demand for DevOps engineers by hiring from emerging tech hubs like Eastern Europe.

3.Mitigate the Impact of Attrition :

Facilitate skills based workforce planning well in advance within your org – leveraging global labor market data and create a pool of talent that will insulate you from potential high attrition rates. Here’s how –

• Create a Sustainable Talent Framework – A data-driven skill based workforce planning strategy focuses on future-proofing your workforce while maintaining competitive advantage. The skills based workforce planning framework:
• Identifies at-risk roles through skills obsolescence analysis
• Creates structured knowledge transfer programs from senior experts to junior talent
• Implements targeted reskilling initiatives aligned with market demands
• Develops competitive compensation packages based on skills premiums
• Skills Adjacency Mapping – For easy sustainability and scalability of the workforce while also ensuring talent portability Workforce planning teams can leverage labour market data to explore natural progression paths between related skill sets. This enables strategic talent development and data-driven skills based workforce planning. This analysis:
• Maps current employee skills against emerging market demands
• Identifies high-potential candidates for role transitions
• Creates targeted upskilling pathways
• Reduces recruitment costs through internal talent development

Anticipate, Adapt, Achieve: The Future-Readiness Starts Now

Building a future-ready workforce requires proactive skills based workforce planning. The McKinsey Global Institute projects that by 2030, as many as 375 million workers globally (14% of the workforce) will need to transition to new roles or significantly enhance their skills due to automation. Companies leveraging multi-dimensional labor market insights can anticipate skill gaps, build talent pipelines, and implement upskilling programs before challenges arise.

A Deloitte report shows that 75% of enterprise businesses plan to reskill their workforce to meet evolving demands. Prioritizing skills based workforce planning approach fosters innovation, improves operational efficiency, and ensures long-term resilience.

The time to act is now. By aligning workforce strategies with business goals, organizations can secure sustainable success and maintain a competitive edge in a rapidly evolving economic landscape. 

Draup helps companies like Pepsico, Randstad, Vodafone, Paypal, Pfizer, Intuit and many more to understand such trends and plan early – factoring in the futuristic software engineering roles required to drive Gen AI led innovation and growth.  

Book a demo now!! 

 

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Navigating the Shifting Global Workforce Planning Landscape: Opportunities, Challenges, and the Role of AI

The year 2025 will see the most drastic evolution in global policies, leading to the workforce landscape undergoing unprecedented transformation. The U.S. adoption of a more inward-focused strategy has sent ripple effects across industries and regions, accompanied by a growing emphasis on regional talent hubs, significant leaps in AI implementation, and the reconfiguration of global supply chains. While the impact of these changes for businesses play out in real time, Draup has undertaken some research to understand the broader implications on the strategic workforce planning landscape. 

Global Policy Shifts and Their Impact on the Workforce 

Workforce planning teams are looking at a seismic shift in how their decisions will contribute to how businesses operate and where talent is sourced. Here are several key trends and their implications for organizations and regions worldwide: 

Talent Development: Policies promoting domestic talent are leading to the creation of regional hubs, with Europe, India, and Latin America specializing in green technology, AI, and integrated manufacturing-tech solutions, respectively. 

U.S. Policy Impacts: An “America First” approach prioritizes domestic issues, fostering growth in tier-2 and tier-3 cities through tax incentives. AI is democratizing skills, reducing reliance on traditional IT hubs. 

 Supply Chain and Automation: Proposed tariffs drive supply chain restructuring, emphasizing efficiency through automation and AI. This necessitates a workforce skilled in digital transformation. 

These shifts require workforce planners to realign their strategies, focusing on location-based talent development and new skill combinations that bridge traditional and emerging needs. 

Regional Workforce Planning Trends and Challenges  

Regions worldwide are presented with unique opportunities and challenges. Shifting policies, trade strategies, and emerging technologies are reshaping regional economic landscapes and creating new talent ecosystems. 

Europe’s AI Landscape Evolution:  

• Europe is developing distinct AI specialization hubs – with established centers like London (51,800 AI professionals) and Paris (42,000) leading, while emerging micro-hotspots like Porto and Sofia show rapid growth in AI talent. This indicates how regions are building specialized AI workforces aligned with their economic strengths.  
• Europe is poised to lead in Net Zero initiatives and sustainable technology, with investments focused on achieving climate neutrality by 2050. However, stringent AI regulations may limit Europe’s competitiveness compared to the U.S. and China. 

India’s Tech Ecosystem Evolution 

• AI talent is expanding beyond traditional tech hubs, with tier 2 and 3 cities like Pune, Ahmedabad, and Coimbatore emerging as R&D centers 
• The country’s software export capabilities are strengthening through focused development of specialized AI talent 
• Growth is particularly strong in contract development services and pharmaceutical manufacturing outsourcing 
• Key challenge: Bridging the skills gap between current workforce capabilities and advanced AI requirements 

Latin America’s Digital Transformation 

• Brazil has made significant strides in cybersecurity development 
• Secondary cities are emerging as tech hubs, with new VC-backed startups growing in these areas 
• Regional focus areas include:  
• Skills development programs to enhance workforce competitiveness 
• Development of smaller technology and innovation centers 
• Digital transformation across traditional industries 
• Infrastructure development and political stability remain critical factors for sustained growth 

Southeast Asia’s Strategic Position 

• Countries like Vietnam, Malaysia, and Indonesia are becoming alternative manufacturing hubs 
• The region offers significant operational cost advantages compared to other markets 
• Focus areas include:  
• Manufacturing automation and smart factory development 
• Supply chain optimization through AI 
• Integration of local workforce with advanced technologies 
• Growing investment from Chinese tech giants is accelerating AI adoption and talent development 

Skills for the Future Workforce 

The evolving global workforce requires a strategic focus on skills development to navigate the challenges and leverage opportunities presented by technological advancements and policy shifts. Draup’s latest workforce planning report underscores the importance of reskilling and upskilling to prepare for an AI and automation-driven future. 

Key Skills Likely to Gain Prominence: 

• AI and Intelligent Automation: Skills in developing, deploying, and managing AI tools that enhance operational efficiency. 
• Agentic AI: Expertise in autonomous AI systems for independent decision-making within set boundaries. 
• Robotic Process Automation (RPA): Designing, developing, and managing software bots to automate repetitive tasks, with knowledge in workflow optimization, RPA tools, and system integration. 
• New Age Cybersecurity: Securing digital assets with advanced techniques like zero-trust architecture and AI-driven threat detection. 
• AI Ethics Analyst: Ensuring ethical AI practices. 

And more. 

These shifts will not only transform IT roles but also impact various sectors, including supply chain management, procurement, and HR, requiring professionals to adapt to new tools and methodologies driven by AI and automation. 

Practical Solutions for Workforce Planning 

To navigate the complexities of global policy shifts and emerging workforce trends, organizations must adopt data-driven strategies and leverage advanced tools to stay ahead. The Draup report outlines actionable solutions for workforce planners and HR leaders to prepare for these transformative changes. 

• Leveraging Data-Driven Insights: Comprehensive talent ecosystems, geopolitical risk assessment, and strategic workforce planning leveraging multi-dimensional labor market data will be critical for making informed decisions about workforce deployment. 
• Empowering HR and Talent Acquisition: Streamlining recruitment, transforming L&D programs, and promoting cross-functional expertise are essential for building a future-ready workforce. Data-driven talent intelligence platforms are seeing increasing adoption among forward-looking enterprises to meet these requirements. 

By adopting these solutions, companies can future-proof their workforce strategies, enabling them to navigate policy-driven disruptions, embrace innovation, and maintain a competitive edge in a rapidly evolving global economy. 

2025 Workforce Analytics Forecast: Critical Trends Reshaping Talent Strategy

Drawing from extensive observation of talent market movements and emerging workforce patterns across global enterprises, Draup has identified key trends that will likely shape workforce planning and talent acquisition in 2025. 

These predictions stem from careful analysis of industry developments, shifting talent priorities, and emerging analytical needs across global enterprises. 

Geographic Intelligence Takes Center Stage 

Analyzing local and nearby talent pools within existing locations has become a top priority. 

The traditional “follow the headquarters” approach is becoming obsolete. Organizations leveraging granular geographic analysis have reported up to 30% cost savings and faster hiring cycles due to low competition. For instance, companies identifying micro-talent hotspots in emerging tech hubs like Guadalajara and Pune can secure critical AI talent at significantly lower costs while still maintaining quality. This hyperlocal approach has become essential as remote work normalizes, with 67% of organizations now prioritizing location-specific talent analytics. 

Emerging Workforce Planning Analysis Domains 

New analytical approaches, driven by talent intelligence platforms, are reshaping how organizations approach workforce planning and talent strategy. Through Enterprise AI Team Composition analysis, HR teams are discovering optimal structures for the company’s AI initiatives, moving beyond traditional IT team models to create dynamic, cross-functional units that blend technical expertise with domain knowledge. 

The Convergence of roles has emerged as a critical focus area, as traditional job boundaries blur in the AI era. We’re seeing the rise of hybrid positions where, for example, business analysts are becoming data-savvy, and software developers are developing product management skills. This convergence is forcing organizations to rethink job classifications and career development paths. 

In analyzing Human vs. AI Workloads, companies are making data-driven decisions about task allocation between human workers and AI systems. This goes beyond simple automation decisions to understanding complex workflows where humans and AI complement each other’s strengths.  

Peer organization ratios have become a crucial benchmark for companies building their AI capabilities. By understanding staffing patterns across successful implementations, organizations are developing more effective frameworks for team structures and resource allocation. 

These emerging analytical domains are providing unprecedented insights into workforce planning for an AI-driven future, helping leaders make informed decisions about talent acquisition, skill development, and organizational design. 

Skills at the Core of Enterprise Workforce Planning 

Skills inventory management has shifted from a secondary concern to a strategic imperative. Advanced talent intelligence systems now offer real-time insights into workforce capabilities, moving beyond static resumes to capture practical competencies, project experience, and adjacent skills. Organizations with standardized skills frameworks achieve superior internal mobility, reduced recruitment costs, and better execution of digital transformation. 

Unified skills taxonomies enable internal talent marketplaces, aligning verified capabilities with emerging opportunities and driving precise workforce planning. This approach allows companies to uncover hidden employee skills, create targeted upskilling programs, and respond to market changes more effectively. 

Innovative Approaches to Talent Discovery

Companies are exploring innovative approaches to identify and define emerging skills by leveraging academic research institutions and conference data. This trend represents a shift from traditional skill taxonomy development to a more forward-looking approach that captures specialized capabilities, particularly in rapidly evolving fields like design and AI. 

Key aspects that are driving this approach: 

• Mining academic conference proceedings and research papers to identify cutting-edge skills before they become mainstream 
• Creating specialized skill tags based on emerging research topics and methodologies 
• Mapping these academic-sourced skills to practical job requirements 
• Enabling recruiters to identify candidates with specialized capabilities that may not yet be common in industry 

This approach helps organizations stay ahead in identifying and acquiring talent with specialized capabilities, particularly in fast-evolving fields where traditional skill definitions may lag behind actual market needs. 

Preparing for the Agentic AI Revolution 

Enterprises are increasingly seeking guidance on how autonomous AI systems are reshaping workforce planning and role definitions. This emerging trend reflects growing recognition that AI capable of independent action and decision-making will significantly impact job architectures. The key inquiries center around how to modify existing job descriptions and create new ones that account for human-AI collaboration patterns. 

The immediate focus areas include: 

• Redefining responsibility boundaries between human workers and autonomous AI systems 
• Identifying new skill requirements for roles that will oversee or collaborate with autonomous AI 
• Creating job descriptions that emphasize uniquely human capabilities while acknowledging AI augmentation 
• Planning for emerging hybrid roles that combine domain expertise with AI orchestration abilities 

This trend is expected to gain greater prominence as organizations prepare their workforce for increased deployment of autonomous AI systems. The implications extend beyond technical roles, affecting positions across all organizational levels and functions. Companies are particularly interested in understanding how to evolve their talent frameworks to reflect this new paradigm of human-AI collaboration. 

Redefining Talent Acquisition Metrics in a Skills-Defined World 

Organizations are prioritizing metrics that directly link hiring to capability building. Two key indicators are emerging: 

• Skill Adjacency Index: Measures the percentage of candidates with related skills aligning with future role demands. Leverages AI to dynamically map skill adjacencies, identifying candidates with growth potential. 
• Skill Evolution Readiness Score: Evaluates a candidate’s adaptability to new technologies based on learning agility and past upskilling. Enabled by recent integration of real-time learning data into talent systems, crucial for rapidly changing industries. 
• Workforce Diversity by Emerging Skillsets: Tracks diversity across in-demand skillsets (e.g., AI/ML) within candidate pools and hires. Recent data advancements allow targeted diversity tracking, ensuring equitable representation in key roles. 
• Reskilling ROI: Measures the impact of internal reskilling programs on reducing time-to-fill and cost-per-hire. AI-driven learning platforms enable accurate ROI calculation, justifying investment in employee development. 
• Skill Density per Role: Captures the average number of critical skills per role among new hires, reflecting alignment with multi-disciplinary job demands. AI-powered tools now provide precise skill density measurement, ensuring hiring addresses role complexity. 

These metrics shift the focus from traditional hiring volumes to precise measurements of hiring effectiveness, ensuring alignment with organizational goals. 

As we progress through 2025, enterprise HR teams must recognize that these aren’t merely trends but fundamental shifts in how businesses approach talent strategy. Companies that fail to adapt risk falling behind in the increasingly competitive talent marketplace, while those embracing these changes are positioning themselves for sustained competitive advantage

Why Real-Time Labor Market Intelligence is the Key to Bridge the Skills Gap in Tech

 The rapid evolution of technology is disrupting industries and the global economy at an unprecedented pace, bringing both transformative opportunities and significant challenges along the way. 

One of the most significant challenges faced by global enterprises in 2025 is the fast-widening skills gap—a disconnect between the skillset’s employers need and the ones employees currently have. 87% of companies worldwide are acknowledging current skills gap within their organizations or anticipating skill shortages in the short run. In the long run, this is set to slow down innovation, disrupt growth, and cost businesses billions in productivity losses and missed opportunities.  

Enterprise workforces still have a lot of legacy skillsets – while the digital workflows and economy evolves at breakneck pace. 

To close the skills gap, organizations must rethink their approach to workforce planning and talent acquisition – leading with real-time labor market intelligence. 

Real-time labor market intelligence empowers workforce planning teams with actionable, updated global insights into skill demands, emerging roles, available talent pool, talent distribution and cost analysis, peer talent acquisition analysis, JD analysis, and more. Such granular data empowers talent acquisition teams to make correct, skills-gap analysis and data-driven talent decisions.

Real-Time Labor Market Intelligence: Use Cases 

By identifying emerging skill demands, talent strategy and acquisition teams can gain a decisive edge in innovation, cost efficiency, and market competitiveness while building a future-ready workforce with no skills-gap.  

Deloitte’s research indicates that organizations adopting skills-based approaches are 63%  more likely to achieve business and workforce outcomes compared to ones that don’t. 

Example 1: Consider the case of a workforce planning team within an IT company detecting early blockchain adoption trends and developing internal capabilities six months ahead of competitors. This would help them win more outsourcing deals as they can showcase their delivery capabilities to their prospects. This also helps them deliver seamlessly and achieve optimal customer success and retention.   

Example 2: Walmart identified a digital skills gap as e-commerce surged and launched the “Walmart Academy” to upskill employees in digital technologies and data analysis. This proactive strategy (powered by access to skills gap data) not only filled critical gaps but also drove a $2 billion annual revenue increase, a 10% drop in employee turnover, and improved job satisfaction, showcasing how early action in workforce planning drives efficiency and market leadership.  

Example 3: In MedTech, augmented reality (AR) is revolutionizing surgical planning and training, but it requires niche skills in 3D modeling and AR development. To address this gap, medical firms can tap into locations with a growing talent pool of software development engineers, gaming engineers etc., compare regional costs and reskill them for delivering/supporting healthcare applications. This strategic move can enable them to build a strong AR team and lead in AR-driven medical innovation while closing the skills-gap. 

Example 4: A cloud services provider can leverage real-time skills demand data to identify a surge in demand for quantum computing expertise—a field where job postings has increased by over 260% since 2019. By initiating reskilling programs well in advance (achieve 83% of cost saving compared to external hiring) or upskilling early-career talent to meet this demand, the company can hire talent at a much lower cost compared to when the base pay would skyrocket as the demand for the talent increases.  

Closing the Skills Gap with Real-time Labor Market Intelligence 

The skills crisis in tech will continue to be a tough challenge. However, with proactive skills gap analysis powered by real-time labor market intelligence, talent acquisition teams can have a concrete plan to address it. 

Real-time labor market intelligence enables a clear, actionable strategy to address this skills gap issue by transforming workforce planning from reactive to proactive. 

By using real-time insights, organizations can: 

• Identify the skills gaps proactively – well in advance.  
• Identify and target the high priority business-critical skillsets for current and future business objectives. 
• Reskill and upskill the current workforce, as per internal and customer requirements. 

The stakes are high: ignoring the skills gap risks stagnation and missed opportunities very soon. Conversely, investing in talent today ensures businesses are prepared to meet the demands of tomorrow. With such skilled, future-ready workforce, organizations can thrive in an ever-evolving global market—turning around the skills crisis into a competitive advantage. Real-time skills gap analysis and intelligence lay the foundation for the same.  

Draup helps companies like Pepsico, Randstad, Vodafone, Paypal, Pfizer, Intuit and many more to understand such trends and plan early – factoring in the futuristic software engineering roles required to drive Gen AI led innovation and growth.  

Book a demo now!! 

Sources – Deloitte India Talent Outlook 2023, The Global Startup Ecosystem Report 2022, Deloitte Campus Workforce Trends Synopsis, GlobalX Charting Disruption 2024, Deloitte India Talent Outlook 2024