The World Economic Forum (WEF) Annual Meeting is a global gathering that gathers approximately 3,000 leaders from governments, businesses, civil society, and international organizations in Davos, Switzerland.  This year’s event, from January 20-24, 2025, is themed “Collaboration for the Intelligent Age” and aims to address critical global challenges through innovative and cooperative approaches.  The biggest priority for Recruitment, WFP, and Learning Leaders is centered around the quote given by Ignacio Sánchez Galán from Iberdrola (Global Utility Company).  Galán emphasized the importance of skills: “Without skilled workers, the transition will not be achieved, and the benefits will be non-existent.” 

The forum will focus on adapting society and the economy to emerging technological opportunities, with a particular emphasis on: 

1. Investing in People

• Skill development in the rapidly advancing technological landscape
• Workforce adaptation to new technological challenges
• Reskilling and upskilling strategies

2. Human-Centric Skills

• Emotional Intelligence: The importance of understanding and managing emotions in the workplace will be highlighted.
• Creativity and Innovation: As automation takes over routine tasks, creative problem-solving skills become more crucial.
• Adaptability and Resilience: The ability to navigate change and recover from setbacks will be key discussion points.
• Critical Thinking: Skills in analyzing information, questioning assumptions, and making sound decisions.
• Cross-cultural collaboration
• Ethical technology integration
• Geopolitical resilience skills

3. Technological Skills

• Artificial Intelligence capabilities
• Quantum computing expertise
• Biotechnology skills
• Cybersecurity and digital network competencies

At Draup, all our innovation and roadmap initiatives are meticulously centered around a set of well-defined priorities. We approach skills not as isolated or standalone components but as interconnected entities that form a dynamic ecosystem. This perspective enables us to understand and address the complex interdependencies within workforce capabilities and align them with emerging trends in the digital and AI-driven landscape.

To bring this vision to life, we are developing several comprehensive playbooks designed to empower organizations to navigate these interconnected skill ecosystems. These playbooks will serve as actionable guides, offering insights, frameworks, and tools to help businesses adapt, evolve, and thrive amidst the rapid technological advancements. By leveraging this holistic approach, we aim to foster innovation, enhance workforce agility, and drive meaningful impact for our partners and clients.

Finance Playbook Example  (You will see some IT skills emerging in Finance across the Roles) 

This table provides a comparison of skill requirements and workload contributions (High, Medium, Low) across five financial roles: Financial Planning & Analysis, Finance Controllership, Treasury, Tax & Compliance, and Financial Service Operations. It highlights specific skills such as cash flow forecasting, financial modeling, enterprise risk management, and compliance-related skills, with each role prioritizing a unique set of competencies. For instance, Financial Planning & Analysis emphasizes financial structure evaluation and revenue analytics, while Tax & Compliance focuses on tax treaty interpretation and statutory compliance. Treasury roles demand expertise in liquidity management and treasury systems. This matrix is a guide to understanding the specialization demands within financial roles.

AI Roles Playbook Example:

This table compares key skills and their workload contributions (High, Medium, Low) across five engineering roles: ML Engineer, Deep Learning Scientist, MLOps Engineer, NLP Engineer, and Computer Vision Engineer. It highlights specific skill areas such as programming languages (e.g., Python, C++), machine learning techniques (e.g., reinforcement learning, transfer learning), and tools (e.g., TensorFlow, Docker). Each role has a unique distribution of skill requirements, with varying emphasis on particular competencies. For instance, ML Engineers focus heavily on Python, feature engineering, and hyperparameter tuning, while NLP Engineers prioritize text pre-processing and language models. This matrix provides a clear view of the specialization demands within AI-related roles. 

Summary:  Draup playbooks are designed to help you gain a deep understanding of core skills and their intricate interconnections, enabling a more holistic approach to workforce planning and development.