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New Data From Mckinsey Supports The Insights From Hidden Talents

Leo Migdal
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new data from mckinsey supports the insights from hidden talents

Last month, McKinsey & Co. published an article on team effectiveness, based on its “Team Effectiveness Index,” a measure it developed and tested over the last two years with more than a hundred teams across the world. In the article, they described the commonalities among top-performing teams and addressed three commonly believed myths that are contradicted by the data. In a slight surprise to us, each of these three myths are directly addressed in our “Hidden Talents, Winning Teams” series on team success. We will mention these myths and how they relate to our previous newsletter posts, but first let’s briefly recount the other insights from the data. According to McKinsey’s research, the most important performance differences among teams relate to (a) the efficiency with which they meet their deadlines, (b) the quality of their results, and (c) the level of innovation...

We can note that these are each performance metrics, not measures of employee satisfaction—as we frequently emphasize, the common thinking that people and team investments are about “being nice to employees” is belied by... According to McKinsey’s data, four health drivers come up as the most important across all three performance areas: Trust, Communication, Innovative thinking, and decision-making. Feedback and role definition are also near the top of all four lists. As we step into 2024, professionals in recruitment and artificial intelligence (AI) find themselves navigating a transformative technological landscape. AI has evolved from a mere tool to a powerful catalyst that is reshaping industries and redefining talent acquisition. With groundbreaking advancements in generative AI, applied AI, and machine learning capturing global attention, it's imperative for recruitment experts to stay ahead of these trends to maintain a competitive edge.

But how are these technologies specifically influencing the recruitment arena? What insights do the latest investment figures, job market demands, and enterprise adoption rates provide? In this article, we delve into McKinsey’s Technology Trends Outlook 2024 to extract key statistics and trends that are most pertinent to recruitment and AI professionals. Whether you're seeking the next wave of AI engineers or leveraging AI to optimize your hiring processes, these insights offer a data-driven roadmap for the year ahead. Since 2022, generative AI (gen AI) has dominated technological discussions, and the data supporting its rise is nothing short of staggering. McKinsey's report highlights that investment in generative AI surged sevenfold in 2023, propelled by groundbreaking advancements in text, image, and video generation (McKinsey).

This isn't merely a temporary spike; it's indicative of a fundamental shift that's transforming sectors ranging from pharmaceuticals to finance. For recruitment professionals, this exponential growth signals an ongoing revolution. Gen AI tools are increasingly being integrated into HR systems, automating repetitive tasks such as candidate screening, interview scheduling, and initial outreach through AI-powered chatbots. This automation enhances operational efficiency, allowing recruiters to dedicate more time to high-value activities like nurturing relationships with top-tier talent. Notably, this technological shift has driven a 111% increase in job postings related to generative AI between 2022 and 2023 (McKinsey). The race to secure AI talent—particularly those skilled in large language models (LLMs) and multimodal data processing—has intensified.

For recruiters, the takeaway is clear: engaging with this talent pool is crucial to staying competitive. Arlington, Va. – A new study released today by the Aerospace Industries Association (AIA) and McKinsey reveals that, despite focused efforts to strengthen talent attraction and retention, the aerospace and defense (A&D) industry continues to face... Titled Accelerating Progress—Maximizing the Return on Talent in A&D, the report offers a comprehensive, data-driven analysis of the sector’s workforce dynamics. It highlights the urgent need for fresh approaches and sustained investment to strengthen the talent pipeline and ensure the long-term vitality and competitiveness of the U.S. A&D industry.

“The aerospace and defense industry continues to lead in innovation thanks to the power and ingenuity of our workforce – but the talent challenges we face continue to grow more complex,” said AIA President... “To remain a global leader, we must take bold, strategic action to attract, retain, and empower the next generation of talent. That means investing not only in people, but also in the technologies and partnerships that will secure our industry’s resilience and competitiveness for decades to come.” Drawing on insights from more than 30 A&D organizations representing over 600,000 U.S. employees—as well as perspectives from industry leaders, talent executives, national workforce data, and McKinsey analysis—the study paints a picture of an industry at a critical inflection point. In 2024, the U.S.

A&D sector generated $995 billion in revenue, a 5.7% year-over-year increase, even as companies grappled with persistent talent shortages, high attrition, and ongoing supply chain and production constraints. Recently, AIA and Accenture LLP released “Artificial Intelligence in Aerospace and Defense,” a report analyzing how AI and automation can help the A&D industry tackle key challenges, including workforce gaps. Read the full report here. Joanna Riley, CEO & cofounder of Censia. Striving for a more just and efficient global economy through better talent data and technology. In the age of data-driven decision-making, the significance of structured, multidimensional data cannot be overstated.

This data type forms the backbone of advanced AI systems, facilitating nuanced insights and predictive analytics essential for modern business strategies, including talent management. Companies that harness data in talent management have seen remarkable improvements in both efficiency and insights into workforce dynamics. For instance, incorporating data-driven strategies in recruiting has been shown to significantly enhance the quality of the workforce, increase productivity, and support unbiased hiring decisions. Workable's comprehensive guide on data-driven recruiting emphasizes the importance of choosing the right data and metrics, collecting data efficiently, and acting on this data to improve hiring processes. Multidimensional data isn't a new concept. Most business intelligence (finance, consumer behavior, etc.) relies on structured data across multiple dimensions to gain profound insight and determine future strategy.

HR has always been the big exception because HR has traditionally been one-dimensional (a linear resume of qualifications matched to a linear list of job requirements), often inaccurate or messy (outdated profiles, multiple job... By cleaning and structuring this talent data and introducing new layers of information (company size, revenue levels, company events, industry and more), the insight that AI can derive from this data grows immensely.

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