Industry 4.0 is introducing rapid and epochal changes and challenges. Among these, the issue of skills and job profiles is assuming a critical role. In fact, the literature highlights not only the necessary integration of existing skills in professional profiles, but also the inevitable creation of new ones to properly manage the digitalisation trends. Although, the state of the art mostly focuses on building models to assess the digital maturity of companies, considering instead the impact on the labor market as a hazy issue. Moreover, the literature tends to offer qualitative approaches to the topic, making the results uncertain; on the other side, quantitative ones tend to be mainly applied on structured databases, while the supply and demand of competences (findable in CVs, vacancies or firm’s job profiles) are less treated. The goal of the present research is developing a measure for quantifying the readiness of employees belonging to a big firm with respect to the Industry 4.0 paradigm. To reach the goal, a data-driven approach based on text mining techniques is applied to a case study. In particular the present methodology makes use of a previously developed enriched dictionary of technologies and methods 4.0 (Chiarello et al., 2018). The source is used to analyze job profiles’ descriptions belonging to Whirlpool, a multinational company with a structured database of jobs and skills. The process allows the identification of technologies, techniques and related skills contained in job descriptions. Starting from these, the Industry 4.0 impact on each job profile is measured. Finally, the metadata of the job profiles are analyzed to evaluate to which extent the skills of profiles 4.0-ready and non-4.0-ready differ. In the end, the work provides a framework for estimating the Industry 4.0 readiness of enterprises’ human capital which demonstrates to be fast, adaptable and reusable.

工业4.0带来了快速而划时代的变化和挑战。其中，技能和职位简介的问题起着至关重要的作用。实际上，文献不仅强调了现有技能在专业档案中的必要整合，而且还强调了不可避免地创建新技能以正确管理数字化趋势。虽然，目前的技术水平主要集中在建立模型以评估公司的数字成熟度，但将对劳动力市场的影响视为一个模糊的问题。而且，文献倾向于对这一主题提供定性的方法，使得结果不确定。另一方面，定量方法往往主要应用于结构化数据库，而能力的供求关系（可在简历，职位空缺或公司的工作概况中找到）则较少受到重视。本研究的目标是开发一种度量方法，以量化属于工业4.0范式的大公司员工的准备程度。为了达到目标，将基于文本挖掘技术的数据驱动方法应用于案例研究。特别是，本方法学利用了先前开发的丰富的技术和方法4.0词典（Chiarello et al。，2018）。该来源用于分析属于Whirlpool的跨国公司的职位资料，该公司具有结构化的职位和技能数据库。该过程可以识别职务说明中包含的技术，技术和相关技能。从这些开始，测量了工业4.0对每个职位概况的影响。最后，分析工作档案的元数据，以评估4.0就绪和非4.0就绪的档案的技能差异。最后，该工作为估算企业人力资本的工业4.0准备水平提供了一个框架，该框架被证明是快速，可适应和可重用的。