A whopping 87% of organizations are experiencing skills gaps within their workforce or expect to be in the near future. 

This concerning skills gap is a consequence of role-oriented workforce architecture, where skills are not factored in talent identification. Such outdated workforce architectures hinder the ability to find, promote, or train people based on their skills. 

Forward-thinking businesses are adopting skills-based workforce planning, which provides flexibility and ensures that their workforce is future-ready. 

Why role-based workforce planning is not the best approach in the age of fast-evolving business objectives 

New-age business initiatives often require skills that are still emerging in the talent market. Traditional profiles might not explicitly list these skills. 

Sticking to traditional role-based hiring overlooks qualified candidates with different job titles but possessing the necessary skillsets. This approach might fill roles but may lead to skill gaps, hindering organizational agility, impacting project timelines and overall success. 

For example, a new-age job like AI Prompt Engineer requires a unique combination of skills. 

Traditional role-based hiring might look for candidates with the exact title ‘AI Prompt Engineer.’ However, it potentially misses individuals with strong natural language processing, coding, and creative writing skills gained in roles like ‘Technical Writer,’ ‘Data Scientist,’ or ‘Content Developer.’ 

This approach limits the pool of potential qualified candidates. 

Instead, using skills-based workforce planning identifies core skills like ‘natural language processing,’ ‘prompt engineering frameworks,’ ‘machine learning model understanding,’ and ‘creative content generation.’ 

This approach allows recruiters to target individuals with relevant experience and aptitude, regardless of their previous job title. 

By focusing on skills, companies can access a broader talent pool, including those with transferable skills, and accelerate the hiring process for critical roles. 

This also opens opportunities for internal mobility, allowing existing employees with relevant skills to transition into these new roles, fostering career growth and maximizing internal talent. 

How skills-first hiring helps 

Organizations that focus on skills, rather than just job titles, are 63% more likely to succeed in important areas like meeting or beating their financial goals, compared to those that haven’t adopted this approach. 

Skills-based workforce planning focuses on identifying the exact skills needed for high-priority business initiatives. It involves: 

• Categorizing initiatives by workload priorities (e.g., launching new products or expanding services). 
• Determining the skills needed by breaking down tasks. 
• Mapping technical and interpersonal skills for each initiative. 
• Aligning talent acquisition or training programs with business needs. 

A skills-first workforce approach requires a robust skills architecture, which includes: 

• Skills taxonomy: This serves as a comprehensive glossary of hard and soft skills required to set a skills-first strategy in motion. It involves organizing skills into technical, leadership, and interpersonal abilities to help stakeholders understand the skills required across business initiatives and its workloads. 
• Skills inventory: A skills inventory to track the current skills within their workforce and identify any gaps that need to be addressed. This real-time visibility is key to making informed decisions about hiring, training, and deployment. 
• Skills development pathways: An end-to-end upskilling/reskilling solution can be the answer to skills gaps. Workforce planning teams can start hiring and training to address skill gaps before your organization reaches a critical point. 

Leveraging AI built on multi-dimensional data for skills-first models 

AI has revolutionized the way organizations approach skills-based workforce models. It analyzes vast amounts of data to provide deeper insights into the specific mission-critical skills. 

The insights have enabled workforce planning teams to identify gaps within the current skills pool and make precise workforce planning decisions that includes targeted training programs. 

Talent intelligence platforms such as Draup leverage AI to analyze data across several key dimensions, enabling a comprehensive understanding of the workforce and talent landscape. 

These dimensions include: 

• Skills: This is the foundational dimension, encompassing both technical skills (e.g., programming languages, software proficiency) and soft skills (e.g., communication, collaboration, problem-solving) from various public profiles. 
• Workloads: This dimension captures the actual work being performed within an organization, broken down into specific tasks and projects. 

Draup enables workforce planning teams identify the skills required for different workloads and anticipate future skill needs based on evolving business priorities. 

• Compensation: This dimension provides insights into salary trends and market rates for different skills and roles. This data is crucial for competitive compensation planning and ensuring fair and equitable pay practices. 
• Peer Analysis/Competitive Benchmarking: This dimension enables organizations to compare their workforce skills and capabilities against those of their competitors. 

Draup provides insights into industry best practices and helps identify areas where a company may need to strengthen its talent pool. 

• Location/Geographic Data: This dimension considers the geographic distribution of talent and allows organizations to identify talent hotspots and plan for remote work strategies. 
• Diversity and Inclusion Metrics: Draup also incorporates diversity and inclusion insights to enable workforce planning teams build a more representative workforce. 

With Draup’s Talent Intelligence platform, companies can adopt a skills-first approach, building a more flexible, adaptable, and competitive workforce.