Workforce productivity skills diagnostic platform - research and experimental development.

忘掉生产率难题吧，英国正面临着一场生产率危机。几十年来，英国国家和公司层面的生产力一直令政策制定者和商界领袖感到担忧。但现在，增长停滞、2008年危机带来的债务负担以及英国脱欧后的不确定性可能会导致长期萧条。生产率带动的产出和工资增长是唯一的出路。技能是关键驱动因素。然而，培训预算正在被削减，对新型培训技术的投资长期以来一直三心二意。需求仍然是通过老式的培训需求分析来建立的，并通过人工策划的资源来满足。为了实现劳动力生产力的阶段性变化，我们必须利用技术来个性化培训和优化技能。我们提出了一个数据驱动的在线平台来诊断技能差距，提出培训建议，并沿着个性化的路径指导学习者。该项目将在以下方面进行研究和产品开发：-开发机器学习算法，为个人识别相关培训材料；-定义明显影响组织生产力的技能组合，量化这些技能的贡献。这些研究组成部分支持生产力价值链中的两个关键环节：技能与生产力之间；在工人概况和技能要求之间。

Forget the productivity ‘puzzle’… Britain faces a productivity crisis. National and firm-level productivity in the UK has worried policy makers and business leaders for decades. But now flat growth, a debt overhang from the 2008 crisis, and post-Brexit uncertainty threaten long-term depression. Productivity-led growth in output and wages is the only way out. Skills are a key driver. Yet training budgets are being cut and investment in novel training technologies has been half-hearted over the long-term. Requirements are still established with old-fashioned training needs analyses and met with manually curated resources. To achieve the required step-change in the productivity of our workforce we must harness technology to personalise training and optimise skills. We propose a data-driven online platform to diagnose skills gaps, make training recommendations and coach learners along personalised paths. The project would conduct research and product development in: - development of a machine learning algorithm to identify relevant training material for individuals; - definition of a portfolio of skills that demonstrably affect organisational productivity, quantifying how those skills contribute. These research components support two key links in the productivity value chain: between skills and productivity; and between worker profile and skills requirements.