As automation and AI increasingly take hold in the corporate world, many companies are increasing their investments in skill-building of all kinds: upskilling, reskilling, and even “outskilling” – where employers train employees who are being laid off to help them get their next job. Some of these investments help workers adopt new tools to speed up parts of their jobs. Others aim to fill open jobs within the company, addressing the paradox wherein automation and AI cause jobs to disappear from one part of the company but also cause a shortage of skilled labor elsewhere.
The coronavirus pandemic has driven companies to increase these investments, as the underlying forces of automation, AI, and digitalization have accelerated.
And yet, the way companies measure the impact of these investments remains fuzzy. In a global survey of learning and development (L&D) professionals, LinkedIn found that the majority of measures used to assess the impact of training programs are soft metrics, like completion rates, satisfaction scores, and employee feedback. Comparatively few respondents used harder metrics, such as increases in employee retention, productivity, or revenue.
CEOs and CFOs should demand better measures, particularly as the amount of money at stake continues to increase. A recent report from the World Economic Forum and PwC found an effective investment in closing the skills gap could boost GDP by $6.5 trillion by 2030.
Here are four measures that, taken together, can inform a comprehensive scorecard to measure the return on investment of skill-building programs.
Read the full article on Harvard Business Review.
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