Cristian Manuel Andrés Porras Calderón — Multicountry Predictive Labor Adjustment System with Inverted Recruitment, Experiential Evaluation Based on Kolb’s Model, and Environmental Sustainability Approach: HR+ Innovative Idea Winner
What if recruitment didn’t start with a CV… but with people, context, and potential?
These are the key ideas behind Multicountry Predictive Labor Adjustment System with Inverted Recruitment, Experiential Evaluation Based on Kolb’s Model, and Environmental Sustainability Approach, one of the two winning projects of the HR+ Online Contest, awarded in the Innovative Idea category.
Developed by Cristian Manuel Andrés Porras Calderón, the proposal responds to a growing challenge across Europe and beyond: how to better match talent with opportunity in increasingly complex, dynamic, and diverse labour markets.
Recruitment today is often shaped by standardised processes that prioritise formal qualifications and CV-based screening. While efficient, these approaches can overlook important dimensions such as adaptability, learning capacity, and contextual performance—especially in a world of work undergoing rapid digital, green, and social transitions.
This is where the proposal introduces a different perspective.
At its core, the system rethinks recruitment through three interconnected elements.
First, inverted recruitment, where companies meet candidates in their chosen or familiar environments. This approach reduces stress, removes logistical barriers, and creates a more inclusive and accessible recruitment experience—particularly for candidates who may be disadvantaged by traditional selection settings.
Second, experiential evaluation based on Kolb’s learning model, which focuses on how individuals learn, adapt, and perform in real situations. Instead of relying solely on past experience or formal credentials, this method allows organisations to better understand candidates’ potential, problem-solving abilities, and capacity for growth.
Third, a strong emphasis on environmental sustainability, integrating practices that reduce unnecessary travel and promote greener approaches to recruitment and skills development. In doing so, the proposal aligns HR practices with broader sustainability goals and the green transition.
Together, these elements form part of a broader multicountry predictive system, designed to improve labour adjustment across different contexts. By considering both individual potential and labour market dynamics, the model aims to create more effective, responsive, and forward-looking recruitment strategies.
This approach also reflects a wider shift in how we think about talent. Moving beyond static profiles and standardised processes, it highlights the importance of flexibility, inclusion, and lifelong learning in shaping the workforce of the future.
You can read more about the winning project below:
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