The world of work is in a period of flux. By 2030, Germany will be short of around 4 million skilled workers due to demographic changes. Advancements in technology are reshaping careers, with an estimated 75 million jobs predicted to disappear worldwide by 2030, while 133 million new ones are due to be created. Big Data Skills Analysis supports companies in preparing for these changes in the job market. This article explains how companies can use scientific data to strategically recruit, retain, and develop workers in order to counteract shortages of skilled labor.
Data scientists, robotics engineers, and sustainability managers – a few years ago these were niche professions in the labor market. Today, they are positions that remain unfilled in companies for months. Using Big Data Skills Analysis to detect employee skills, HR departments can proactively identify key expertise for (future) labor shortages in selected professions. The results provide a foundation for decision-making in the context of employee recruitment and development based on scientific research.
WifOR’s Big Data Skills Analysis addresses these questions:
- Which skills will be particularly important over the upcoming years?
- Which skills will lose significance over the upcoming years?
- How can employee development be targeted to enable employees to transition from surplus to in-demand professions?
What is a Big Data Skills Analysis?
A classic “skills analysis” systematically determines a person’s abilities and knowledge. A Big Data Skills Analysis goes a step further: it considers not only the internal situation but also the external labor market trends as well as shows which expertise are required for selected professions. This approach is commonly adopted in HR planning in the remit of recruitment, retention, and development of employees.
Definition: Employee Skills
In scientific literature, the term “skills” has various definitions and is often used synonymously with “abilities”. Authors who make a distinction describe “skills” as an umbrella term for the range of abilities that enable people to handle complex and uncertain situations.
WifOR uses the following categorization of skill types to define required skill profiles and transition pathways:
- Technical professional skills: the specific skills and abilities that a person has acquired in their professional field.
- Cross-professional skills: general abilities, characteristics, and attitudes which are broadly applicable to many professions.
- Certificates and qualifications: official evidence of formal training or education, such as an academic degree or nursing qualification.
Big Data Skills Analysis: what is the methodology?
WifOR’s Big Data Skills Analysis follows a mixed method approach, structured in three steps. This approach is a quantitative analysis to determine the current and targeted professions on the labor market. Furthermore, WifOR applies its own databases, containing with several million job postings, which are constantly updated through web scrapings to assess the most recent labor market trends and developments.
In the first step, WifOR determines the skill requirements according to the profiles for the selected professions. Using AI-supported analyses, the most important skills for each profession can be identified from ca. 50,000 relevant skills before being qualitatively classified.
In the second step, the job requirements are linked with a macroeconomic labor market model. Thereby, WifOR identifies the most important skills for the selected jobs in the future.
In the third step, WifOR determines similarities between job requirements in order to derive meaningful courses of action for companies. This enables the planning of recruiting and training measures based on the identified skill gaps.
What are the benefits of Big Data Skills Analysis?
A Big Data Skills Analysis offers a range of opportunities for companies navigating transformation amongst current labor market megatrends such as digitalization, demographic change and a growing skilled labor shortage. It enables existing and in-demand skill profiles to be identified so that effective employee training programs can be developed. Furthermore, these skill profiles can guide companies when recruiting and onboarding employees for future positions.
Personal development
An important part of employee development for a company is understanding which technical abilities and expertise are present in a company and which are predicted to be absent in the future. Based on this information, companies can provide targeted training and further education opportunities. This can offer employees an insight even if they are currently working in a profession that will no longer exist in the long term. At the same time, the results allow employees to adjust their profiles and advance their own careers.
Recruiting
With a Big Data Skills Analysis, companies can also enhance their recruitment process. It enables, for example, HR planning to identify early on skills which will be required in the future and accordingly recruit individuals who already possess many of these skills. This can simultaneously facilitate the process of integrating new employees into a company as well as increasing productivity. Additionally, a strategic HR plan based on Big Data Skills Analysis opens the door to recruiting individuals from professions with similar skill requirements for hard-to-fill positions and investing in employee development using targeted training to support adaptation.
Employee retention
Companies can use Big Data Skills Analysis can also help to strengthen employee retention for companies. Career perspectives and opportunities for professional development that enable individuals to stay in the company can promote their commitment and motivation over the long term. Alongside a higher employee satisfaction, companies can as a result achieve business success by avoiding labor shortages, reduce employee fluctuation, and improving security in HR planning.
Big Data Skills Analysis: Example Case Study
The benefits of a Big Data Skills Analysis can be seen using this example case study: a medium-sized financial institution in Stuttgart faces several challenges, including uncertain market trends, new legislation, and digital transformations of products and technologies. The company uses the results from the Big Data Skills Analysis to prepare strategically for the future challenges of the job market.
One of the findings from the analysis is that “IT Banking Specialists” will be particularly sought after in the finance sector in the future. This position requires a combination of IT competencies and an aptitude for numbers. At the same time, the analysis shows that “Controllers” will be increasingly present in the job market in the future. The evaluation of transition paths illustrates that Controllers are well disposed to retrain as IT Banking Specialists.
Using transition paths, the financial institution can target existing employees for further training and offer them a future in the company. Furthermore, the institution opens up advertised positions to Controllers who can be trained as IT Banking Specialists through employee development programs. This not only allows the institution to attract highly qualified talents but also to secure its skilled workforce in the long term, thereby strengthening its competitiveness.
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In a nutshell
Companies must prepare strategically for multiple megatrends, such as demographic change, digitalization, and socio-ecological transformation. A Big Data Skills Analysis provides actionable reference points for making scientifically based decisions in these dynamic circumstances. The analysis enables HR managers to develop employees sustainably, plan targeted recruiting measures, offer employees long-term prospects – and thereby counteract the shortage of skilled workers at an early stage.
