Policy Proposal for a Labor Market Common Language

Japan, grappling with a dwindling workforce, must harness digital technology to enhance productivity, lest it fall into economic stagnation due to labor supply constraints. According to MRI’s projections, the advancement of digital transformation (DX) could lead to a workforce reduction of around 9.7 million people by 2035. Specifically, the increasingly spotlighted generative AI, which extends its influence beyond routine tasks, is estimated to potentially impact employment to the tune of at least 4.6 million. Yet, when factoring in the human capital required for shifts in industry structures such as DX, GX, and semiconductor industry revival, there still remains a considerable shortfall of approximately 1.9 million workers. Additionally, on top of the overall supply-demand gap, there's an anticipated mismatch of around 4.8 million between industries and occupations.

Japan is facing a shortfall of talent critical for the necessary transformations in its industrial structure. This shortage is not limited to just so-called digital talents but extends to on-the-ground professionals supporting semiconductor and renewable energy sectors. Furthermore, generative AI possesses the potential to revolutionize the way tasks are conducted across a myriad of professions, leading to profound shifts in the requisite skills regardless of industry or job type. Given these circumstances, facilitating talent mobility across companies and sectors is no longer optional—it is imperative. Governments, corporations, and workers alike must anticipate and prepare for this elevated workforce fluidity, framing strategies to address the looming skill mismatches.

In anticipation of evolving skill requirements and greater labor mobility, corporations are moving towards 'Human Capital Management,' while the government is laying the groundwork for a 'Tripartite Labor Market Reform'. Central to this initiative is the information exchange between market participants (companies and job seekers/employees) regarding talent requirements. In particular, companies are encouraged to foreground 'shared corporate philosophies' and 'assessment of desired skills' as twin pillars of disclosure. Leaders, by communicating their company's vision, purpose, and strategy, can garner empathy from both employees and job seekers while delineating the skills they seek. This guidance empowers workers to reskill, migrate to growth areas, and acquire just compensation and direction for their endeavors.

So, how should skill data visualization in the labor market progress in practical terms? Enter the taxonomy based on 'labor-market big data, which collates, archives, and categorizes online job postings. The US company Lightcast consistently updates its skill system by collecting job information posted online across the US, UK, Canada, Australia, and Singapore. Utilizing this taxonomy, various metrics, like skill similarities between occupations, skill disruptions due to digital technology adoption, wage premiums, and career paths, have been established. By integrating this skill information with a company's HR data, organizations can craft hiring strategies and assess their talent portfolios in tandem with the external labor market.

Advancements in DX, the growth of renewable energy, and the revival of the semiconductor industry have been driving new talent needs, propelling a fluidity in the labor market. However, without a shared lexicon comprehensible to all market participants, the optimal allocation of talent remains elusive, leaving mismatches unresolved. This piece underscores the utilization of the job big data-driven skill system, advocating for a collaborative approach among talent service industries, industry/professional groups, educational sectors, regional economic entities, and individual companies to establish six key points for developing a skill-based common language.