• Productivity
    101 real-world gen AI use cases from the world's leading organizations 在过去一年半的时间里，生成式人工智能（AI）在企业领域的应用迅速发展。Google Cloud的Next活动中展示了超过300家组织如何利用AI推动企业转型。这些企业已经从简单的问答助手，发展到能够进行预测和采取行动的AI代理，进一步扩展其业务功能和提升效率。 具体来说，AI代理在以下几个关键领域表现出显著的效益：首先是客户服务，AI能够帮助企业更好地理解和满足客户需求；其次是员工赋能，通过自动化日常任务和优化工作流程，AI提升了工作效率；在创意构思和生产领域，AI助力企业快速生成创新的解决方案；数据分析方面，AI通过高效处理和解析大数据，支持决策制定；在编码创建方面，AI简化了开发流程，提高了代码质量；最后在网络安全领域，AI加强了数据保护和风险管理。 这些应用不仅提高了生产力和操作效率，还极大地改善了客户体验和企业的创新能力。AI的多模态能力，即在文本、语音、视频等多种通信模式中的应用，使其能够更全面地满足不同行业的需求。通过这些先进的技术，企业正在开创一个智能、高效和互联的新时代。 我们一起来看看，是否有参考？ Since generative AI first captured the world’s attention a year and a half ago, there’s been a vigorous discussion about what, exactly, the new technology is best used for. While we all enjoyed those early funny chats and witty limericks, we’ve quickly discovered that many of the biggest AI opportunities are clearly in the enterprise. Our customers and partners at Google Cloud have found real potential for creating new processes, efficiencies, and innovations with generative AI. For proof, look no further than the 300-plus organizations who are featured at this week’s Next event in Las Vegas. In a matter of months, organizations like these have gone from AI helping answer questions, to AI making predictions, to generative AI agents. What makes AI agents unique is that they can take actions to achieve specific goals, whether that’s guiding a shopper to the perfect pair of shoes, helping an employee looking for the right health benefits, or supporting nursing staff with smoother patient hand-offs during shifts changes. In our work with customers, we keep hearing that their teams are increasingly focused on improving productivity, automating processes and modernizing the customer experience. These aims are now being achieved through the AI agents they’re developing in six key areas: customer service; employee empowerment; creative ideation and production; data analysis; code creation; and cybersecurity. These special capabilities are made possible in large part by the new multimodal capacity of generative AI and AI foundation models, which allow agents to handle tasks across a range of communications modes, including text, voice, video, audio, code, and more. With human support, agents can converse, reason, learn, and make decisions. The hundreds of customers who joined us at Next ‘24 to showcase and discuss early versions of their AI agents and gen-AI solutions have come to rely on Google Cloud technologies that include our AI infrastructure, Gemini models, Vertex AI platform, Google Workspace, and Google Distributed Cloud. We were also joined by more than 100 partners supporting the creation of AI agents and AI solutions, which you can read about in detail.Here’s a snapshot of how 101 of these industry leaders are putting AI into production today, creating real-world use cases that will transform tomorrow. Similar to great sales and service people, customer agents are able to listen carefully, understand your needs, and recommend the right products and services. They work seamlessly across channels including the web, mobile, and point of sale, and can be integrated into product experiences with voice and video. ADT is building a customer agent to help its millions of customers select, order, and set up their home security. Alaska Airlines is developing a personalized travel search experience using advanced AI techniques, creating hyper-personalized recommendations that engage customers early and foster loyalty through AI-generated content. Best Buy is using Gemini to launch a generative AI-powered virtual assistant this summer that can troubleshoot product issues, reschedule order deliveries, manage Geek Squad subscriptions, and more; in-store and digital customer-service associates are also gaining gen-AI tools to better serve customers anywhere they need help. The Central Texas Regional Mobility Authority is using Vertex AI to modernize transportation operations for a smoother, more efficient journey. Etsy uses Vertex AI training to optimize their search recommendations and ads models, delivering better listing suggestions to buyers and helping sellers grow their businesses. Golden State Warriors are using AI to improve the fan experience content in their Chase Center app. IHG Hotels & Resorts is building a generative AI-powered chatbot to help guests easily plan their next vacation directly in the IHG One Rewards mobile app. ING Bank aims to offer a superior customer experience and has developed a gen-AI chatbot for workers to enhance self-service capabilities and improve answer quality on customer queries. Magalu, one of Brazil’s largest retailers, has put customer service at the center of its AI strategy, including using Vertex AI to create “Lu’s Brain” to power an interactive conversational agent for Lu, Magalu's popular brand persona (the 3D bot has more than 14 million followers between TikTok and Instagram). Mercedes Benz will infuse e-commerce capabilities into its online storefront with a gen AI-powered smart sales assistant. Mercedes also plans to expand its use of Google Cloud AI in its call centers and is using Vertex AI and Gemini to personalize marketing campaigns. Oppo/OnePlus is incorporating Gemini models and Google Cloud AI into their phones to deliver innovative customer experiences, including news and audio recording summaries, AI toolbox, and more. Samsung is deploying Gemini Pro and Imagen 2 to their Galaxy S24 smartphones so users can take advantage of amazing features like text summarization, organization, and magical image editing. The Minnesota Division of Driver and Vehicle Services helps non-English speakers get licenses and other services with two-way real-time translation. Pepperdine University has students and faculty who speak many languages, and with Gemini in Google Meet, they can benefit from real-time translated captioning and notes. Sutherland, a leading digital transformation company, is focused on bringing together human expertise and AI, including boosting its client-facing teams by automatically surfacing suggested responses and automating insights in real time. Target uses Google Cloud to power AI solutions on the Target app and Target.com, including personalized Target Circle offers and Starbucks at Drive Up, their curbside pickup solution. Tokopedia, an Indonesian ecommerce leader, is using Vertex AI to improve data quality, increasing unique products being sold by 5%. US News saw a double-digit impact in key metrics like click-through rate, time spent on page, and traffic volume to its pages after implementing Vertex AI Search. IntesaSanpaolo, Macquarie Bank, and Scotiabank are exploring the potential of gen AI to transform the way we live, work, bank, and invest — particularly how the new technology can boost productivity and operational efficiency in banking. Watch the session to learn more. Employee agents help workers be more productive and collaborate better together. These agents can streamline processes, manage repetitive tasks, answer employee questions, as well as edit and translate critical communications. Avery Dennison empowered their employees with generative AI to enable secure, flexible, and borderless collaboration for enhanced productivity to drive growth. Bank of New York Mellon built a virtual assistant to help employees find relevant information and answers to their questions. Bayer is building a radiology platform that will assist radiologists with data analysis, intelligent search, and to create documents that meet healthcare requirements needed for regulatory approval. The bioscience company is also harnessing BigQuery and Vertex AI to develop additional digital medical solutions and drugs more efficiently. Bristol Myers Squibb is transforming its document processes for clinical trials using Vertex AI and Google Workspace. Now, documentation that took scientists weeks now gets to a first draft in minutes. BenchSci develops generative AI solutions empowering scientists to understand complex connections in biological research, saving them time and financial resources and ultimately bringing new medicine to patients faster. Cintas is using Vertex AI Search to develop an internal knowledge center for customer service and sales teams to easily find key information. Covered California, the state’s healthcare marketplace, is using Document AI to help improve the consumer and employee experience by automating parts of the documentation and verification process when residents apply for coverage. Dasa, the largest medical diagnostics company in Brazil, is helping physicians detect relevant findings in test results more quickly. DaVita leverages DocAI and Healthcare NLP to transform kidney care, including analyzing medical records, uncovering critical patient insights, and reducing errors. AI enables physicians to focus on personalized care, resulting in significant improvements in healthcare delivery. Discover Financial helps their 10,000 contact center representatives to search and synthesize information across detailed policies and procedures during calls. HCA Healthcare is testing Cati, a virtual AI caregiver assistant that helps to ensure continuity of care when one caregiver shift ends and another begins. They are also using gen AI to improve workflows on time-consuming tasks, such as clinical documentation, so physicians and nurses can focus more on patient care. The Home Depot has built an application called Sidekick, which helps store associates manage inventory and keep shelves stocked; notably, vision models help associates prioritize which actions to take. Los Angeles Rams are utilizing AI across the board from content analysis to player scouting. McDonald’s will leverage data, AI, and edge technologies across its thousands of restaurants to implement innovation faster and to enhance employee and customer experiences. Pennymac, a leading US-based national mortgage lender, is using Gemini across several teams including HR, where Gemini in Docs, Sheets, Slides and Gmail is helping them accelerate recruiting, hiring, and new employee onboarding. Robert Bosch, the world's largest automotive supplier, revolutionizes marketing through gen AI-powered solutions, streamlining processes, optimizing resource allocation, and maximizing efficiency across 100+ decentralized departments. Symphony, the communications platform for the financial services industry, uses Vertex AI to help finance and trading teams collaborate across multiple asset classes. Uber is using AI agents to help employees be more productive, save time, and be even more effective at work. For customer service representatives, they’ve launched new tools that summarize communications with users and can even surface context from previous interactions, so front-line staff can be more helpful and effective The U.S. Dept. of Veterans Affairs is using AI at the edge to improve cancer detection for service members and veterans. The Augmented Reality Microscope (ARM) is deployed at remote military treatment facilities around the world. The prototype device is helping pathologists find cancer faster and with better accuracy. The U.S. Patent and Trademark Office has improved the quality and efficiency of their patent and trademark examination process by implementing AI-driven technologies. Verizon is using generative AI to help teams in network operations and customer experience get the answers they need faster. Victoria’s Secret is testing AI-powered agents to help their in-store associates find information about product availability, inventory, and fitting and sizing tips, so they can better tailor recommendations to customers. Vodafone uses Vertex AI to search and understand specific commercial terms and conditions across more than 10,000 contracts with more than 800 communications operators. WellSky is integrating Google Cloud's healthcare and Vertex AI capabilities to reduce the time spent completing documentation outside work hours. Woolworths, the leading retailer in Australia, boosts employees’ confidence in communications with “Help me write” across Google Workspace products for more than 10,000 administrative employees. It’s also using Gemini to create next-generation promotions, as well as for quickly assisting customer service reps in summarizing all previous customer interactions in real time. Box, Typeface, Glean, CitiBank, and Securiti AI discuss developing AI-powered apps across the enterprise, with measurable returns on investment for marketing, financial services, and HR use cases. Highmark Health and Freenome join Bristol Myers Squibb to explore how AI can improve efficiency and innovation across care delivery, drug discovery, clinical trial planning, and bringing medicines to market. Creative agents can expand your organization with the best design and production skills, working across images, slides, and exploring concepts with workers. Many organizations are building agents for their marketing teams, audio and video production teams, and all the creative people that can use a hand. With creative agents, anyone can become a designer, artist, or producer. Belk ECommerce is using generative AI to craft better product descriptions, a necessary yet time-consuming task for digital retails that has often been done manually. Canva is using Vertex AI to power its Magic Design for Video, helping users skip tedious editing steps while creating shareable and engaging videos in a matter of seconds. Carrefour used Vertex AI to deploy Carrefour Marketing Studio in just five weeks — an innovative solution to streamline the creation of dynamic campaigns across various social networks. In just a few clicks, marketers can build ultra-personalized campaigns to deliver customers advertising that they care about. Major League Baseball continues to innovate its Statcast platform, so teams, broadcasters, and fans have access to live in-game insights. Paramount currently relies on manual processes to create the essential metadata and video summaries used across its Paramount+ platform for showcasing content and creating personalized experiences for viewers. VertexAI Text Bison is now helping to streamline this process. Procter & Gamble used Imagen to develop an internal gen AI platform to accelerate the creation of photo-realistic images and creative assets, giving marketing teams more time to focus on high-level planning and delivering superior experiences for its consumers. WPP will integrate Google Cloud’s gen AI capabilities into its intelligent marketing operating system, called WPP Open, which empowers its people and clients to deliver new levels of personalization, creativity, and efficiency. This includes the use of Gemini 1.5 Pro models to supercharge both the accuracy and speed of content performance predictions. Data agents are like having knowledgeable data analysts and researchers at your fingertips. They can help answer questions about internal and external sources, synthesize research, develop new models — and, best of all, help find the questions we haven’t even thought to ask yet, and then help get the answers. AI21 Labs offers a BigQuery integration called Contextual Answers that allows users to query data conversationally and get high-quality answers quickly Anthropic has partnered with Google Cloud to offer its family of Claude 3 models on Vertex AI — providing organizations with more model options for intelligence, speed, cost-efficiency, and vision for enterprise use cases. The Asteroid Institute is using AI to discover hidden asteroids in existing astronomical data. This is a major focus for astronomers researching the evolution of the Solar System, investors and businesses hoping to fly missions to asteroids, and for all of us who want to prevent future large asteroid impacts on Earth. Contextual is working with Google Cloud to offer enterprises fully customizable, trustworthy, privacy-aware AI grounded in internal knowledge bases. Cox 2M, the commercial IoT division of Cox Communications, is able to make smarter, faster business decisions using AI-powered analytics. Essential AI, a developer of enterprise AI solutions, is using Google Cloud’s AI-optimized TPU v5p accelerator chips to train its own AI models. Generali Italia, Italy's largest insurance provider, used Vertex AI to build a model evaluation pipeline that helps ML teams quickly evaluate performance and deploy models. Globo, one of Brazil’s largest media networks, is using Service Extensions and Media CDN to fight piracy during live events by blocking pirated streams in real time. Hugging Face is collaborating with Google across open science, open source, cloud, and hardware to enable companies to build their own AI with the latest open models from Hugging Face and Google Cloud hardware and software. Kakao Brain, part of Korean technology company Kakao Group, has built a large-scale AI language model that is the largest Korean language-specific LLM in the market, with 66 billion parameters. They’ve also developed a text-to-image generator called Karlo. Mayo Clinic has given thousands of its scientific researchers access to 50 petabytes worth of clinical data through Vertex AI search, accelerating information retrieval across multiple languages. McLaren Racing is using Google AI to get up-to-the-millisecond insights during races and training to gain a competitive edge. Mercado Libre is testing BigQuery and Looker to optimize capacity planning and reservations with delivery carriers and airlines to fulfill shipments faster. Mistral AI will use Google Cloud's AI-optimized infrastructure, to further test, build, and scale up its LLMs, all while benefiting from Google Cloud's security and privacy standards. MSCI uses machine learning with Vertex AI, BigQuery and Cloud Run to enrich its datasets to help our clients gain insight into around 1 million asset locations to help manage climate-related risks. NewsCorp is using Vertex AI to help search data across 30,000 sources and 2.5 billion news articles updated daily. Orange operates in 26 countries where local data must be kept in each country. They are using AI on Google Distributed Cloud to improve network performance and deliver super-responsive translation capabilities. Spotify leveraged Dataflow for large-scale generation of ML podcast previews, and they plan to keep pushing the boundaries of what’s possible with data engineering and data science to build better experiences for their customers and creators. UPS is building a digital twin of its entire distribution network, so both workers and customers can see where their packages are at any time. Workday is using natural language processing in Vertex Search and Conversation to make data insights more accessible for technical and non-technical users alike. Woven — Toyota's investment in the future of mobility — is partnering with Google to leverage vast amounts of data and AI to enable autonomous driving, supported by thousands of ML workloads on Google Cloud’s AI Hypercomputer. This has resulted in resulting in 50% total-cost-of-ownership savings to support automated driving. Broward County, Florida, and Southern California Edison are using geospatial capabilities and AI to improve infrastructure planning and monitoring, generate new insights, and create regional resilience for communities facing climate challenges today and tomorrow. Kinaxis and Dematic are building data-driven supply chains to address logistics use cases including scenario modeling, planning, operations management, and automation. NOAA and USAID are among the U.S. government agencies using Google Cloud AI to unlock critical data insights to streamline operations and improve mission outcomes — all with an emphasis on responsible AI. Watch the session to learn more. Code agents are helping developers and product teams to design, create, and operate applications faster and better, and to ramp up on new languages and code bases. Many organizations are already seeing double-digit gains in productivity, leading to faster deployment and cleaner, clearer code. Capgemini has been using Code Assist to improve software engineering productivity, quality, security, and developer experience, with early results showing workload gains for coding and more stable code quality. Commerzbank is enhancing developer efficiency through Code Assist's robust security and compliance features. Quantiphi saw developer productivity gains of more than 30% during their Code Assist pilot. Replit developers will get access to Google Cloud infrastructure, services, and foundation models via Ghostwriter, Replit's software development AI, while Google Cloud and Workspace developers will get access to Replit’s collaborative code editing platform. Seattle Children's hospital is using AI to boost data engineering productivity and accelerate development. Turing is customizing Gemini Code Assist on their private codebase, empowering their developers with highly personalized and contextually relevant coding suggestions that have increased productivity around 30 percent and made day-to-day coding more enjoyable. Wayfair piloted Code Assist, and those developers with the code agent were able to set up their environments 55 percent faster than before, there was a 48 percent increase in code performance during unit testing, and 60 percent of developers reported that they were able to focus on more satisfying work. Security agents assist security operations by radically increasing the speed of investigations, automating monitoring and response for greater vigilance and compliance controls. They can also help guard data and models from cyberattacks, such as malicious prompt injection. BBVA uses AI in Google SecOps to detect, investigate, and respond to security threats with more accuracy, speed, and scale. The platform now surfaces critical security data in seconds, when it previously took minutes or even hours, and delivers highly automated responses. Behavox is using Google Cloud technology and LLMs to provide industry leading regulatory compliance and front office solutions for financial institutions globally. Charles Schwab has integrated their own intelligence into the AI-powered Google SecOps, so analysts can better prioritize work and respond to threats. Fiserv’s security operations engineers create detections and playbooks with much less effort, while analysts get answers more quickly. Grupo Boticário, one of the largest beauty retail and cosmetics companies in Brazil, employs real-time security models to prevent fraud and to detect and respond to issues. Palo Alto Networks’ Cortex XSIAM, the AI-driven security operations platform, is built on more than a decade of expertise in machine-learning models and the most comprehensive, rich, and diverse data store in the industry. Backed by Google's advanced cloud infrastructure and advanced AI services, including BigQuery and Gemini models, the combination delivers global scale and near real-time protection across all cybersecurity offerings. Pfizer can now aggregate cybersecurity data sources, cutting analysis times from days to seconds. To find even more customers using our AI tools to build agents and solutions for their most important enterprise projects, visit the Google Cloud customer hub and watch the Next ‘24
    Productivity
    2024年04月12日
  • Productivity
    Will Chatbots Take Over HR Tech? Paradox Sets The Pace. 在快速发展的人力资源技术领域，Paradox.ai 已成为领跑者，其先进的对话式人工智能平台彻底改变了招聘流程。通过利用自然语言处理和人工智能，Paradox.ai 提供了一个全面的解决方案，涵盖了从最初的职位申请到入职的整个招聘过程。该平台不仅简化了筛选和面试安排等繁琐流程，还提升了应聘者的整体体验，显著改善了招聘时间和招聘质量指标。 Paradox.ai 由亚伦-马托斯（Aaron Matos）于 2016 年创立，目前为联合利华、CVS Health 和通用汽车等大客户提供服务，实现了 90% 以上的招聘流程自动化。 Paradox.ai 凭借其强大的集成能力和大幅缩短招聘时间、降低招聘成本的能力，在人力资源技术领域充分体现了对话式人工智能的变革力量。 Chatbots used to be tinker-toys. You type, try to get help, but usually result in “please call support.” Well all this has changed. Thanks to advanced NLP (natural language processing) and AI (retrieval-augmented generation) chatbots are entire applications. They can answer complex questions, search databases, and invoke transactions on your behalf. Pretty soon we’ll be able to ask our phones “please find me a flight to Los Angeles next Tuesday morning” and the system will check your location and calendar, look at flights, and book you a seat. Where is this going in HR? Well the leader in this space is Paradox.ai, a company that pioneered the application of conversational AI in recruiting. And their system “defines the category.” Let me explain. Recruiting Is The Perfect Market For Conversational AI Recruiting is a goldmine for automation. When you post a job, applicants want to ask many predictable things: “How much does it pay?” “What are the hours?” or “What uniform do I need” or “What are the benefits?” The recruiter, a person devoted to filling positions, has to answer all these questions and more. They have to screen candidates, schedule interviews, check for qualifications, and look at credentials, experience, and more. It’s time-consuming, error-prone, and filled with wasted time. (That’s why talent acquisition teams have many “scheduler” and admins.) The average “time to hire” is over 45 days and often the process goes on for months. And throughout the experience the job seeker is left wondering “when will they call back” or “what else do I need to know?” (CEOs cite hiring as the third most time-wasting process in companies, following emails and meetings, estimated at “40% wasted time.”) Paradox uses Conversational AI to solve this problem. And because this is a “narrow but deep” space, the system does many things we can learn from in all our AI efforts. Paradox was founded by Aaron Matos in 2016. Aaron’s vision was to transform the candidate experience, revolutionizing the way candidates apply to jobs. Today Paradox has become a complete Conversational AI Recruitment Platform (chat to apply, scheduling, candidate support, ATS, assessments, onboarding, career site, and more), serving clients like Unilever, CVS Health, Pfizer, L’Oreal, Nestle, McDonald’s FedEx, Compass Group, Disney, and General Motors. The platform automates tasks such as screening for requirements, interview scheduling, reminders, offers, and new hire onboarding. And because it’s so easy to use, it helps companies radically improves time-to-hire and quality of hire. Based on my conversations with clients, Paradox can automate more than 90% of the end-to-end hiring process, saving hiring managers hours every week and increasing candidate conversion by more than 10 times. But this innovation did not happen overnight. As you know, going to a candidate website and looking for a job is a frustrating process. There are often hundreds of jobs listed, a complex scrolling website and very hard to even determine what job to apply for. You might argue that the website paradigm for job applications was never really a good idea in the first place. People don’t want to browse for jobs: they want to apply for a job that’s best for them. So the first thing Paradox did was create an easy to use assistant (Olivia) so candidates could ask questions and schedule interviews. And this meant that Paradox had to build integrations with every ATS and personal email and calendar tools out there. Then, as companies started to use Paradox for scheduling, the company added more. Today Olivia, the chatbot, can integrate with background check vendors, schedule interviews, deliver assessments (Paradox acquired a conversational assessment Traitify designed for this), and function as an ATS … all from a mobile phone. In many ways Paradox can be “the integration platform” for candidates and recruiters, stitching together the messy systems behind the scenes. This turned into a massive opportunity. Just as the Google Assistant or Siri hopes to be our single contact with the internet, Paradox partners with systems of record like Workday, SAP, and Oracle to bring conversational AI to any company. The company’s revenues have grown 11 times in the last four years, and are now nearly doubling each year. For customers Paradox has been amazing. As the candidate pipeline speeds up (by an order of magnitude), clients get higher quality candidates with dramatically reduced staff. (Staffing administrators can almost go away.) Consider high-volume hiring companies. These businesses (McDonald’s, Compass Group, Neighborly, FedEx, Disney) hire service-related workers on a regular basis. Their revenue is dependent on having enough people. With Paradox they can set up a “continuous recruitment process,” one that even hires people the same day they apply. Paradox has become essential to these companies growth, often paying for itself in less than a year (through reduced hiring staff, reduced spend on job ads, and reduced turnover.) Today, as Paradox built out its ATS, customers can rely on the platform to integrate front end tool (job portals and candidate support) to back end tools scheduling, ATS, onboarding) most of which are legacy. One of our clients has 27 recruiting tools and they anticipate replacing more than half of them with a platform like Paradox. What about higher level white collar roles? Paradox works here too. General Motors uses Paradox along with Workday (ATS), (branded Evie) to redesign the process. Interview Scheduling: Evie automates scheduling of phone screens and interviews between recruiters, candidates, and internal teams. This has reduced the time taken for interview scheduling from an average of five days to 29 minutes. Candidate Experience: Evie interacts with candidates from the moment they land on GM’s career site until the completion of their interview. Candidates appreciate the immediate communication from Evie after they apply or complete an interview, and enjoy the autonomy to select and change interview times. Efficiency and Cost Savings: The automation of interview scheduling has led to a major reduction in the cost of external contractors for coordination. Career Site Interaction: Evie sits on GM’s career site, answering questions from potential candidates about jobs, benefits, and company culture. This interaction enhances the candidate’s experience and provides them with immediate responses to their queries. Where Is Paradox Going The company is perfectly positioned to continue its growth as companies look for AI solutions to improve the productivity and effectiveness of recruiting. And demand is high: the 2024 PwC CEO survey found that recruiting was considered the #3 “most bureaucratic process” by CEOs (following email and meetings). The impact on recruiters? All positive. Clients tell us they can redeploy hiring staff to help recruiters focus on the most important part of their job: talking with candidates. But there’s a much bigger story. When a job candidate is handled efficiently and effectively the process becomes a brand-builder for the candidate, improving quality of hire. Ambitious job seekers will not put up with (or wait for) a messy, confusing hiring process. So not only is the process faster and more efficient, the quality of hire goes up. Companies are desperately looking for AI solutions that work. As Paradox has proven, when you focus deeply on the problem, conversational AI can be transformational. Listen to my conversation with Adam Godson (CEO) and you’ll hear the details. This is where the HR Tech market is going.
    Productivity
    2024年04月04日
  • Productivity
    应对心理健康危机：42%的公司计划推出新的员工福利 根据The Conference Board的最新报告，尽管HR领导们对劳动力市场的乐观程度略有上升，但员工保留和参与度的预期与去年相比有所下降，显示出劳动力短缺的持续问题。报告揭示，随着员工心理健康问题的加剧，42%的公司计划今年提供新的福祉福利。企业承认对员工福祉负有责任，并在增加对健康项目的关注和支出方面取得了显著进展。报告强调，全面考虑员工福祉不仅可以提高员工参与度和生产力，还能保留人才。  Tackling the Mental Health Crisis: 42% of Companies Plan to Offer New Employee Well-Being Benefits NEW YORK, March 22, 2024 -- Corporate America's HR leaders continue to be more optimistic than pessimistic about the state of the workforce. The Conference Board CHRO Confidence Index ticked up to 54 in Q1, from 53 last quarter. (A reading of more than 50 points reflects more positive than negative responses.) While retention and engagement expectations improved from last quarter, the survey reveals they are down compared to this time last year, signaling ongoing concerns about labor shortages. Hiring expectations remained stable. The survey also reveals that businesses are stepping up as mental health concerns continue taking a toll on workers throughout the nation: 42% of surveyed companies plan to offer new well-being benefits this year. Indeed, 36% say businesses are responsible for the well-being of their employees, with another 62% saying they are somewhat responsible. As a result, they are ramping up their focus on employee wellness: In addition to those offering new well-being benefits, a quarter plan to increase spending on well-being initiatives. "Taking a holistic view of worker well-being can not only improve employee engagement and productivity but also retain your talent—a top focus of both CEOs and CHROs this year," said Diana Scott, Leader of The Conference Board US Human Capital Center. The Index, conducted quarterly, was launched in Q1 2023 and is comprised of three components—hiring, retention, and engagement—as well as special questions included in each survey. Nearly 150 CHROs participated in the Q1 survey, which included additional questions on employee well-being. Key findings include: Hiring The CHRO Confidence Index: Hiring component remained the same as both last quarter and YoY, at 55. CHROs' workforce expansion plans remained stable in Q1, with fewer CHROs expecting to increase or decrease hiring in the next six months: 36% of CHROs expect to increase their hiring over the next six months—down from 44% in Q4. 13% expect to decrease their hiring over the next six months—down from 19% in Q4. Retention The CHRO Confidence Index: Retention component rose to 53 in Q1 2024 from 51 in Q4 2023. But retention expectations are down YoY from 57 in Q1 2023. CHRO expectations regarding employee retention ticked up slightly in Q1: 29% of CHROs expect their employee retention levels to improve over the next six months—up slightly from 28% in Q4. 19% of CHROs expect employee retention to decrease over the next six months, down from 22% in Q4. Engagement The CHRO Confidence Index: Engagement component rose to 54 in Q1 2024 from 52 in Q4 2023. But engagement expectations are down YoY from 58 in Q1 2023. Fewer CHROs expect declines in employee engagement in Q1: 35% expect engagement levels to increase—down slightly from 37% in Q4. 20% expect engagement levels to decrease—down significantly from 31% in Q4. Special Questions for Q4: Employee Well-Being For Q1 2024, the Index also surveyed CHROs on employee well-being. CHROs overwhelmingly agree that organizations share responsibility for their employees' well-being. 62% said organizations are somewhat responsible. 36% said organizations are responsible. Only 2% said organizations are not responsible for employee well-being. A quarter of CHROs increased spending on employee well-being in 2024. 26% said their well-being budget increased for FY2024. 69% said it remained the same. Only 5% decreased spending on well-being. Nearly half of CHROs plan to offer new well-being benefits, despite most keeping spending the same. 42% plan to offer new benefits this year. 39% do not plan to offer new benefits. 19% are discussing offering new benefits. Mental and physical health are the top priorities for new well-being initiatives. Of those offering new benefits: 20% are offering mental health initiatives. 15% are offering physical health and fitness initiatives. 12% are offering financial well-being initiatives. 10% are offering work-life balance initiatives. About The Conference BoardThe Conference Board is the member-driven think tank that delivers trusted insights for what's ahead. Founded in 1916, we are a non-partisan, not-for-profit entity holding 501 (c) (3) tax-exempt status in the United States. www.conference-board.org SOURCE The Conference Board
    Productivity
    2024年03月24日
  • Productivity
    Valoir 报告显示 HR 尚未准备好迎接 AI，你呢？ 研究显示，人力资源管理领导者面临的主要问题包括缺少 AI 相关的专业知识以及面临的风险和合规性问题。 弗吉尼亚州阿灵顿--Valoir 发布的一项全球新报告显示，尽管 AI 驱动的自动化似乎无法避免，但人力资源部门似乎并未做好准备。这项涵盖超过150位人力资源执行官的调查揭示了利用 AI 的巨大机会，但同时也显示出在制定政策、实施实践和进行培训方面普遍存在不足，以便安全有效地将 AI 技术应用于人力资源管理。 “虽然许多机构开始采用生成式 AI，但很少有组织建立必要的政策、准则和保障措施。作为员工数据的保护者和公司政策的制定者，人力资源领导者需要在 AI 的政策和培训方面走在前列，不仅为自己的团队，也为广大员工群体做好准备。” 以下内容需要特别注意： “AI 正在快速融入人力资源管理领域，特别是在招聘、人才发展和劳动力管理等方面。然而，引入 AI 也伴随着诸如数据泄露、误解、偏见和不当内容等风险，”Valoir 的首席执行官 Rebecca Wettemann 表示。“面对这些挑战并采取措施减少风险的人力资源部门，可以显著提升其从 AI 中获得的益处。” 人力资源的自动化与战略转型潜力 报告指出，有35%的人力资源部门员工的日常工作非常适合自动化处理。在所有人力资源管理活动中，招聘环节最有潜力应用 AI 技术，并且已成为采纳率最高的领域，近四分之一的组织已经开始利用 AI 支持的招聘流程。人才发展、劳动力管理以及培训和发展同样被视为 AI 自动化的关键领域。 生成式 AI 正在加速人力资源部门的生产力提升及风险增加 尽管到2023年中旬，超过三分之四的人力资源领域工作者已经尝试使用过某种形式的生成式 AI，但仅有16%的组织制定了关于使用生成式 AI 的具体政策。而且，真正关于其伦理使用的政策数量更是寥寥无几。人力资源领导者认为，缺乏 AI 相关技能和专业知识是采纳 AI 的最大障碍，但只有14%的组织制定了有效的 AI 使用培训政策。这些政策对于确保所有员工都能充分利用 AI 带来的好处并最小化风险是至关重要的。 “尽管生成式 AI 正被广泛采纳，但几乎没有哪些组织建立了必要的政策、准则和保护措施。作为员工数据的守护者和公司政策的制定者，人力资源领导者必须在 AI 政策和培训方面先行一步，这不仅是为了他们自己的团队，也是为了整个员工群体的利益，”Wettemann 表示。 报告的关键知识点： Integration Challenges: HR faces challenges in managing AI use due to lack of policies, practices, and training. Early Adoption vs. Preparedness: While HR has been an early adopter of AI, most organizations still lack the proper frameworks for safe and effective AI adoption. Rapid Product Release: Post-Chat GPT announcement, HR software vendors have rapidly released generative AI products with varying capabilities. AI’s Double-Edged Sword: AI offers great benefits but also poses risks of "accidents" due to immature technology, inadequate policies, and lack of training. AI Experimentation and Automation Opportunity: Over three-quarters of HR workers have experimented with generative AI. 35% of HR tasks could potentially be automated by AI. Current AI Utilization: The main opportunities for HR benefits from AI are in recruiting, learning and development, and talent management, with recruiting leading in AI adoption. Adoption Barriers: Main hurdles include lack of AI expertise (28%), fear of compliance and risk (23%), and lack of resources (21%). Policy and Training Deficiencies: Only 16% of organizations have policies on generative AI use, and less than 16% have training policies for AI usage. Risk Areas in AI: Data compromises, AI hallucinations, bias and toxicity, and recommendation bias are identified as primary risks. Future Plans for AI: Over 50% of organizations plan to apply AI in recruiting, talent management, and training within the next 24 months. Least Likely AI Adoption: Benefits management has the lowest likelihood of current or future AI adoption due to data sensitivity concerns. AI Skills and Expertise: The significant gap in AI skills and expertise impacts the adoption and effective use of AI in HR. HR’s Role in AI Adoption: HR needs to develop policies, provide training, and ensure ethical AI use aligning with organizational principles. Recommendations for HR: Suggestions include experimenting with generative AI, developing ethical AI usage policies, creating role-specific AI training, and identifying employee groups at risk from AI automation.
    Productivity
    2024年03月12日
  • Productivity
    根据美世 2024 年全球人才趋势研究，高管认为人工智能是提高生产力的关键，但大多数员工尚未做好转型的准备 Mercer's 2024 Global Talent Trends Study unveils critical insights from over 12,000 global leaders and employees, highlighting the increasing importance of AI in productivity, discrepancies between executive and HR perceptions, the necessity of human-centric work design, and the growing challenges in trust, diversity, and resilience within the workforce. The study emphasizes the urgency of adapting talent strategies to foster greater agility and employee well-being amidst technological advances and shifting workforce dynamics. 美世今天发布了2024年全球人才趋势研究。该研究借鉴了全球 12,000 多名高管、人力资源主管、员工和投资者的见解，揭示了雇主为在这个新时代蓬勃发展而采取的行动。 “今年的调查结果突显了工作中的惊人转变，”美世总裁帕特·汤姆林森 (Pat Tomlinson) 表示。“他们指出，高管层和人力资源部门对于 2024 年业务发展的看法存在显着分歧，而且员工对于技术影响的看法也存在滞后。随着我们迎来人机团队的时代，组织需要将人置于转型的核心。” 生成式人工智能 (AI) 被视为提高生产力的关键 生成式人工智能能力的快速增长引发了人们对劳动力生产力提升的希望，40% 的高管预测人工智能将带来超过 30% 的收益。然而，五分之三 (58%) 的人认为科技进步的速度超过了公司对员工进行再培训的速度，不到一半 (47%) 的人认为他们可以通过当前的人才模式满足今年的需求。 “通过人工智能提高生产力是高管们最关心的问题，但答案不仅仅在于技术。提高员工生产力需要有意识的、以人为本的工作设计。”美世全球人才咨询主管兼该研究的作者 Kate Bravery 说道。“领先的公司认识到人工智能只是其中的一部分。他们正在从整体的角度来解决生产力下降的问题，并通过新的人机协作模式提供更大的敏捷性。” 寻找通向未来工作的可持续道路面临着挑战。四分之三 (74%) 的高管担心他们的人才的转变能力，不到三分之一 (28%) 的人力资源领导者非常有信心他们能够使人机团队取得成功。提高敏捷性的关键是采用技能驱动的人才模型，这是高增长公司已经掌握的。 员工信任度全面下降 2023 年，对雇主的信任度从 2022 年的历史最高水平下降，这是一个危险信号，因为研究表明信任对员工的精力、蓬勃发展感和留下来的意愿产生重大影响。那些相信雇主会为他们和社会做正确事情的人，表示自己正在蓬勃发展、具有强烈的使命感、归属感和被重视感的可能性是其他人的两倍。 近一半的员工表示，他们希望为一个令他们感到自豪的组织工作，一些公司的回应是优先考虑可持续发展工作和“良好工作”原则。鉴于公平薪酬（34%）和发展机会（28%）是员工今年留下来的主要驱动力，雇主有动力在未来一年在薪酬公平、透明度和公平获得职业机会方面取得更快进展。 在全球范围内，员工都清楚，归属感有助于他们成长，但只有 39% 的人力资源领导者表示，女性和少数族裔在其组织的领导团队中拥有良好的代表，只有 18% 的人表示，最近的多元化、公平性和包容性努力提高了员工保留率关键多元化群体。四分之三的员工 (76%) 目睹过年龄歧视。由于这些挑战加上持续的技能短缺，更多地关注包容性和满足员工的需求将有助于所有员工蓬勃发展。 未来几年，韧性将至关重要 最近在风险缓解方面的投资已获得回报，64% 的高管表示他们的业务能够承受不可预见的挑战，而两年前这一比例为 40%。通货膨胀等近期担忧严重影响高管的三年计划，但网络和气候等长期风险可能没有得到应有的必要关注。 建立个人韧性与企业韧性同样重要，五分之四 (82%) 的员工担心自己今年会精疲力竭。为员工福祉重新设计工作对于缓解这一风险至关重要，51% 的高增长公司（2023 年收入增长 10% 或以上）已经这样做了，而低增长同行中只有 39% 这样做了。 员工体验是重中之重 超过一半的高管 (58%) 担心他们的公司在激励员工采用新技术方面做得不够，三分之二 (67%) 的人力资源领导者也担心他们在没有改变工作方式的情况下实施了新技术解决方案。员工体验是今年HR的首要任务；这是一个值得关注的问题，因为蓬勃发展的员工表示雇主设计的工作体验能够发挥他们的最佳水平的可能性是普通员工的 2.6 倍。 人力资源部门在改善所有人的工作方面发挥着关键作用，但人力资源部门越来越有必要与风险和数字化领导者合作，以按要求的速度引入必要的变革。为了满足组织和员工的期望，96% 的公司计划今年对人力资源职能进行一些重新设计，重点是跨部门交付和领先的数字化工作方式。 投资者重视敬业的员工队伍 今年，美世首次收集资产管理公司关于组织的人才战略如何影响其投资决策的意见。近十分之九 (89%) 的人将员工敬业度视为公司绩效的关键驱动力，84% 的人认为“流失和燃烧”方法会损害商业价值。投资者还表示，营造信任和公平的氛围是未来五年建立真正、可持续价值的最重要因素。 单击此处了解更多信息并下载今年的研究。 关于美世 2024 年全球人才趋势研究 美世全球人才趋势目前已进入第九个年头，汇集了来自 17 个地区和 16 个行业的 12,200 多名高管、人力资源领导者、员工和投资者的见解，该研究重点介绍了当今领先组织为确保人员长期可持续发展所采取的措施。在此过程中走得更远的组织在四个领域取得了长足的进步。(1) 他们认识到，以人为本的生产力需要关注工作的演变以及工作人员的技能和动机。(2) 他们认识到信任是真正的工作对话，通过透明度和公平的工作实践得到加强。(3) 随着风险变得更加关联且难以预测，他们认识到，提高风险意识和缓解水平对于建立一支准备就绪、有复原力的员工队伍至关重要。(4) 他们承认，随着工作变得越来越复杂，简化、吸引和激励员工走向数字化的未来至关重要。 关于美世 美世坚信，可以通过重新定义工作世界、重塑退休和投资成果以及释放真正的健康和福祉来建设更光明的未来。美世在 43 个国家/地区拥有约 25,000 名员工，公司业务遍及 130 多个国家/地区。美世是Marsh McLennan （纽约证券交易所股票代码：MMC）旗下的企业，Marsh McLennan 是风险、战略和人才领域全球领先的专业服务公司，拥有超过 85,000 名同事，年收入达 230 亿美元。通过其市场领先的业务（包括达信、Guy Carpenter和奥纬咨询），达信帮助客户应对日益动态和复杂的环境。
    Productivity
    2024年03月07日
  • Productivity
    The best HR & People Analytics articles of January 2024 2024年对HR专业人士来说是充满挑战和机遇的一年。经济不确定性、地缘政治紧张和技术进步是主要的挑战。文章强调了生产力的重要性，以及来自PwC、麦肯锡和埃森哲的洞察。利物浦经理朱尔根·克洛普的离职案例展示了领导力和文化的重要性。文章还强调了人力资源分析的重要性，提供了来自领先公司的见解。 2024年的HR趋势和预测涵盖了人工智能的影响和向基于技能的组织的转变。工作场所的心理安全、多样性、平等、包容和归属感仍然是重要议题。这篇文章为HR专业人士提供了全面的指导，帮助他们在未来一年中导航复杂性。 2024 is set to be a momentous year. With economic uncertainty, rising geopolitical conflict, and rapid advances in technology, it is also set to be a stormy 12 months for the world, for organisations, and for HR professionals too. Perhaps this explains the slew of insightful resources in January, which has made compiling this month’s collection as challenging as it has been enjoyable. One of the key focuses has been on ‘productivity’, and I’ve brought together a number of resources on this topic. There are also new studies from the likes of PwC, McKinsey, Glassdoor, Accenture, and Deloitte as well as articles featuring practitioners from companies including Spotify, Microsoft, Ericsson, Lloyds Banking Group, and Standard Chartered. There’s lots to enjoy and learn from. Join me for a webinar on February 21 to discover how Leading Companies shift People Analytics from insight to impact Are you an HR or People Analytics Leader seeking to transform your organisation’s People Analytics from mere insights to impactful business outcomes? If so, I invite you to join me for a webinar that Insight222 is hosting on February 21. Naomi Verghese and I will walk through the findings from the Insight222 People Analytics Trends research, unveiling the distinctive characteristics of ABCD Teams that propel organisations to new heights. Naomi and I will be joined by Alan Susi, VP and Global Head of Organisational Analytics and People Insights at S&P Global. Alan will share insights into how S&P Global successfully elevated their approach to people analytics, turning data into tangible business outcomes. You can register for the webinar here – or by clicking the image below. Jürgen Klopp – a study in leadership, culture, and analytics As a fervent supporter, I’m still processing the totally unexpected news that Jürgen Klopp will be leaving his post as the manager of Liverpool at the end of the current football season. In his press conference on taking the reins at Anfield in October 2015, Klopp stated his goal was to turn Liverpool from “doubters to believers.” He has done this with some aplomb amassing a haul of seven trophies (to date) including the Champions League in 2019 and then, the following year, the Holy Grail of Liverpool’s first league title in 30 years. But Klopp is more than a brilliant football manager. He is the epitome of an empathetic leader. His emotional intelligence and natural humility not only endears Klopp to his players, but to supporters too for whom he is adored. The reaction to the news reduced many Liverpool supporters to tears. I’m still hoping – probably forlornly - that like Alex Ferguson in 2002, Klopp will change his mind and stay. In the likely event that he does depart, I’m sure that multiple studies will be made on Klopp’s time at Anfield, and that his leadership skills, use of data and analytics, and ability to build an inclusive winning culture will be deservedly celebrated. YNWA. Looking for a new role in people analytics or HR tech? Before we get to this month’s collection of resources, I’d like to highlight once again the wonderful resource created by Richard Rosenow and the One Model team of open roles in people analytics and HR technology, which now numbers over 500 roles. Looking for a people analytics event to attend in 2024? Richard Rosenow has also been busy compiling a study of People Analytics Conferences to attend in 2024 with the data collected from practitioners themselves. Society for Industrial and Organizational Psychology (SIOP), People Analytics World and the Wharton People Analytics Conference all come out well as does the Insight222 Global Executive Retreat. Thanks to Richard for putting this together. Share the love! Enjoy reading the collection of resources for January and, if you do, please share some data driven HR love with your colleagues and networks. Thanks to the many of you who liked, shared and/or commented on December’s compendium (including those in the Comments below). If you enjoy a weekly dose of curated learning (and the Digital HR Leaders podcast), the Insight222 newsletter: Digital HR Leaders newsletter is published every Tuesday – subscribe here. THE QUEST FOR PRODUCTIVITY MCKINSEY - 2024 and beyond: Will it be economic stagnation or the advent of productivity-driven abundance? | PwC - 27th Annual Global CEO Survey: Thriving in an age of continuous reinvention | JOSH BERSIN - HR Predictions for 2024: The Global Search For Productivity | ERIK BRYNJOLFSSON - How AI Will Transform Productivity | BEN WABER AND NATHANAEL J. FAST - Is GenAI’s Impact on Productivity Overblown? When I talk with CHROs and People Analytics Leaders at the companies we work with at Insight222, one of the words I’m hearing most at the moment is ‘productivity’. Continuing economic and geopolitical uncertainty, the promise of AI, and challenging talent demographics are all fuelling the demand for productivity from CEOs. Here are five resources that can be filed under the ‘productivity’ umbrella: (1) McKinsey’s Ezra Greenberg, Asutosh Padhi, and Sven Smit present a model for businesses to capture the three-sided productivity opportunity (see FIG 1). (2) Amongst a ton of takeaways, the standout theme from the annual PwC CEO survey is that the vast majority of participating companies are already taking some steps towards reinvention, while CEOs believe that 40% of their work is wasted productivity (see FIG 2). (3) Josh Bersin draws from the PwC survey in his 2024 predictions, where he outlines The Productivity Advantage where “If you can help your company move faster (productivity implies speed, not only profit), you can reinvent faster than your competition.” (4) Stanford professor Erik Brynjolfsson offers leaders an overview of how AI will transform productivity. (5) Finally, Ben Waber and Nathanael Fast’s absorbing essay in Harvard Business Review cautions leaders on leaning into the hype on GAI’s supposed positive impact on productivity too heavily. The authors break down two of the key challenges with LLMs: a) their persistent ability to produce convincing falsities and b) the likely long-term negative effects of using LLMs on employees and internal processes. FIG 1: The three-side productivity opportunity (Source: McKinsey) FIG 2: CEOs estimate administrative inefficiency at 40% (Source: PwC) GERGELY OROSZ AND ABI NODA - Measuring Developer Productivity: Real-World Examples Continuing the productivity theme, this is an invaluable resource by Gergely Orosz and Abi Noda in The Pragmatic Engineer newsletter. It provides detail on developer productivity metrics at 17 tech companies including Google, Microsoft, Spotify, and Uber (see summary in FIG 3). FIG 3: Developer productivity metrics at 17 tech companies (Source: Pragmatic Engineer) 2024 HR TRENDS AND PREDICTIONS JASMINE PANAYIDES - Nine Ways to Put HR Trends and Predictions into Practice in 2024 There has been a flood of articles advising what the key HR trends, predictions, and opportunities for 2024 are, but how are HR professionals supposed to make sense of these? In her article for the myHRfuture blog, Jasmine Panayides provides actionable tips on how HR professionals can apply the trends, predictions and opportunities to their work, and their organisations so they can deliver value to the company and the workforce. Jasmine also helpfully summarises the trends/predictions from a variety of sources into one table (see FIG 4), including from: Visier Inc., Gartner, Bernard Marr, UNLEASH, Mercer, and Culture Amp as well as my own 12 Opportunities for HR in 2024 article. FIG 4: Analysis of HR Trends and Predictions for 2024 (Source: myHRfuture) KATARINA BERG - HR Trends for 2024 | GARTNER - 9 Future of Work Trends for 2024 | GLASSDOOR – 2024 Workforce Trends | HUNG LEE - Forecasting 2024 in Recruitment Part 1, Part 2, Part 3, and Part 4 | KEVIN WHEELER - What Does 2024 Hold in Store for Us? | STACIA GARR AND DANI JOHNSON – 2024 Mega Trends and how people leaders should respond (Webinar) The deluge of commentators offering their HR trends and opportunities continued in January. As such, it is a challenge to sort the wheat from the chaff but in addition to those I highlighted in this compendium in December, and in Jasmine’s article above, I recommend diving into the following: (1) Spotify’s chief people officer, Katarina Berg, highlights ten trends with the common theme being each trend is a bridge, connecting the past with the future, and HR professionals are the architects crafting these vital links – including “Staying Human in the Age of AI – The Humanity Bridge”. (2) Gartner’s Jordan Turner and Emily Rose McRae highlight nine future of work trends for the year ahead (see FIG 5). (3) Aaron Terrazas and Daniel Zhao identify eight workforce trends based on Glassdoor’s data on workplace satisfaction, culture, and conversations. (4) Hung Lee is at the cutting edge of recruiting and HR tech, so his four-part series on recruiting in 2024 is definitely worth checking out – two examples include: “Multi-generational replaces neurodiversity as DEIB hot topic” and “Capital Allocation Shifts from Sourcing & Engagement to Assessment & Verification Tech”. (5) Futurist Kevin Wheeler offers seven insights and predictions together with his self-assessed certainty rating including “Generative AI will dominate, and every product will attempt to incorporate AI. 90% certainty” and “More firms will embrace a four-day workweek 50% certainty”. (6) Finally, I strongly recommend viewing the 2024 Mega Trends webinar hosted by Stacia Sherman Garr and Dani Johnson for RedThread Research, which breaks down the key macro factors impacting the world of work and how HR can respond. FIG 5: 9 Future of Work Trends for 2024 (Source: Gartner) GREG NEWMAN - 10 important topics that HR will likely ignore in 2024 Greg Newman takes an alternative, wry and contrarian approach by focusing his list of “predictions” on ten things most HR teams will continue to ignore in 2024. My favourite three are: (1) speaking the language of the business, (2) focusing AI conversations on ethics before technology, and (3) learning that good data is required to realise the dreams of AI and analytics. By aligning HR language with business terminology, we can more effectively demonstrate the value of our initiatives in a way that resonates with business stakeholders. GENERATIVE AI AND THE FUTURE OF WORK ELLYN SHOOK AND PAUL DAUGHERTY - Work, workforce, workers: Reinvented in the age of generative AI A new study from Accenture, co-authored by Ellyn Shook and Paul Daugherty, on how generative AI is impacting work, provides guidance on how leaders can: “Set and guide a vision to reinvent work, reshape the workforce and prepare workers for a generative AI world, while building a resilient culture to navigate continuous waves of change.” The report reveals a trust gap between workers and leaders on key elements related to GAI’s impact on work, the workforce, and workers. The authors also highlight four accelerators for leaders to navigate the journey ahead: (1) Lead and learn in new ways, (2) Reinvent work, (3) Reshape the workforce (see example in FIG 6), and (4) Prepare workers. FIG 6: Illustrative example of how work and roles can be reallocated in a GAI future (Source: Accenture) ROGER W. HOERL AND THOMAS C. REDMAN - What Managers Should Ask About AI Models and Data Sets The decision on whether to deploy AI models within an organisation ultimately lies with business leaders who may not be qualified to identify risks and weaknesses related to AI models and data sets. In their article, Roger Hoerl and Tom Redman provide (1) A framework (see FIG 7) designed to equip leaders with context and based on their concept of the right data. (2) A set of six questions for leaders to ask their AI model developers before and during modelling work and deployment. (3) Guidance for leaders on how to assess AI model developers’ answers to those six questions. FIG 7: The Right Data Framework (Source: Roger W. Hoerl and Thomas C. Redman) PEOPLE ANALYTICS STEVE HATFIELD, SUE CANTRELL, AND BRAD KREIT - Beyond the quick fix: How workforce data can drive deeper organizational problem-solving The premise of this thoughtful article by Steve Hatfield, Susan Cantrell, and Brad Kreit is that without the right context, even simple measurements can undermine efforts to convert people data into value. They then explore several examples – in the workforce, in the workplace, and in the work – where organisations might be limiting their analysis to the surface level and how deeper analysis can reveal systemic issues that lead to opportunities for transformation. Guidance on three actions leaders can take to help ensure they are not missing important context in their data analysis are provided: (1) Bring data from different domains and sources together for analysis. (2) Make sure you’re measuring what you should—not just what you can. (3) Identify potential biases in data collection algorithms. If organizations want to move beyond quick fixes and use work and workforce data to drive deeper—and often more challenging—problem-solving, it is important that they look at the data in context. NAOMI VERGHESE - How to Measure the Value of People Analytics My Insight222 colleague Naomi Verghese digs how to measure the commercial value of people analytics, highlighting a powerful case study from Jaesun HA and LG Electronics. Naomi provides detail on four key areas where people analytics adds value (business performance, workforce experiences, driving an analytics culture and societal benefit) as well as providing data on the characteristics of companies that ARE creating commercial value from people analytics (see FIG 8). FIG 8: Characteristics of people analytics that disclosed and measured commercial value of people analytics solutions (Source: Insight222 People Analytics Trends, 2023) ANDRÉS GARCIA AYALA - 5 Change Drivers Impacting People Analytics & How To Thrive In Them | WILLIS JENSEN - Attrition versus Retention: Which Should I Use? | KEITH McNULTY – Regression Modeling in People Analytics: Survival Analysis | LYDIA WU - The Market Sucks and You are Looking for a Job, Now What? | SEBASTIAN SZACHNOWSKI - 16 HR Metrics for IT | ERIN FLEMING AND NICK JESTEADT - People Analytics Perspectives from the Fringe: Current Priorities and a View on Optimized Teams in 2024 January saw a slew of articles from current and recent people analytics leaders, which typically act as a spur and inspiration for the field. Six are highlighted here: (1) Andrés García Ayala highlights some of the key change drivers impacting people analytics and ways to incorporate them into our work. (2) Willis Jensen builds on the recent primer on attrition metrics by Ben Teusch that I highlighted in December’s edition. He explains why we should be using attrition and retention as separate terms that lead to distinct metrics with different objectives (see also FIG 9). (3) Keith McNulty provides another indispensable practical guide for people analysts with a step-by-step tutorial to conducting survival analysis in R. (4) The prolific Lydia Wu turns her attention to providing some handy guidance for those looking for their next people analytics / HR tech role. (5) Sebastian Szachnowski provides a useful breakdown of 16 HR metrics for technology companies. (6) Last but definitely not least, Erin Fleming and Nick Jesteadt provide insights from their survey of fellow people analytics practitioners. Insights include a) 41% of respondents (n=49) operate as a one-person people analytics team, and ii) the main current focus areas of work include employee turnover, cultural engagement, return to office, and restructuring. FIG 9: When to use Attrition and Retention (Source: Willis Jensen) MAX BLUMBERG - The Big List of GPTs to Revolutionize Your People Processes | JOHANNES SUNDLO - GenAI for People Analytics Two articles addressing the opportunity for generative AI in the people space. (1) Max Blumberg (JA) ?? sets out 93 potential ways to upgrade your People Processes with AI and GPTs across four categories – workforce planning and strategy, recruitment, learning and development, and employee wellbeing. (2) Johannes Sundlo provides examples of companies using GAI in their people analytics work to support analyses on engagement data, skills, and tailoring training recommendations. GPTs are an amazing tool for scenario planning, forecasting future workforce needs, identifying talent gaps, and developing integrated talent strategies. THE EVOLUTION OF HR AND DATA DRIVEN CULTURE DAVE ULRICH, NORM SMALLWOOD, AND JOE GROCHOWSKI - Why and How to Move HR to an Outside-In Approach When asked the question, “What is the biggest challenge in your job today?” HR professionals will typically provide answers such as: “Build a skills-based organisation” or “Help our employees have a better experience”. As Dave Ulrich, Norm Smallwood, and Joe Grochowski write, these answers would be far more powerful when a “so that” is applied e.g. “Help employees have a better experience so that customer experience improves.” The article demonstrates that greater value is created with an outside-in approach that starts with the needs of external stakeholders (customers, investors, community) and then figuring out the implications inside the company for meeting those needs. Dave, Norm, and Joe also present their Human Capability Framework and a tool that provides an assessment of an organisation’s outside-in performance (see FIG 10). FIG 10: Human capability from the outside-in - diagnostic questions (Source: Dave Ulrich et al) WORKFORCE PLANNING, ORG DESIGN, AND SKILLS-BASED ORGANISATIONS AMY WEBB - Bringing True Strategic Foresight Back to Business In her article for Harvard Business Review, Amy Webb defines strategic foresight as “a disciplined and systematic approach to identify where to play, how to win in the future, and how to ensure organizational resiliency in the face of unforeseen disruption.” Her article also advocates for the integration of strategic foresight as a core competency in every organisation, regardless of size. Moreover, Amy provides guidance on how to operationalise strategic foresight by unveiling a ten-step process. Read alongside another article authored by Amy for HBR: How to Do Strategic Planning Like a Futurist, which includes Amy’s Futurist’s Framework for Strategic Planning (see FIG 11). FIG 11: A Futurist’s Framework for Strategic Planning (Source: Amy Webb) WORLD ECONOMIC FORUM AND PwC - Putting Skills First: Opportunities for Building Efficient and Equitable Labour Markets As the introduction to this compelling collaboration between the World Economic Forum and PwC begins: “Skills and talent shortages are critical challenges facing societies and economies today. The absence of relevant skills impedes business growth, hinders economic prosperity, and inhibits individuals from realizing their full potential.” The report identifies five specific opportunities for intervention where the gains from skills-first solutions are most likely for employers and workers alike (see ‘Skills-first Framework’ in FIG 12). Additionally, the report also showcases 13 Skills First “Lighthouses”, including IBM, Siemens, Standard Chartered and Sanofi. It concludes by offering key takeaways regarding six success factors in implementing skills-first approaches including (1) Sponsorship from leadership, (2) Alignment with business needs, and (3) Data and evaluation for iteration. (Authors: Genesis Elhussein, Mark Rayner, Aarushi Singhania, Saadia Zahidi, Peter Brown MBE, Miral Mir, and Bhushan Sethi). A cultural shift to skills-first approaches needs both sponsorship from executives and governance from human-resources professionals FIG 12: Skills-first Framework (Source: World Economic Forum PETER SHEPPARD - Learning from our Skills Journey | BEN AUTY - What are the new skills people will need for the future of work? | TANUJ KAPILASHRAMI - How Standard Chartered is Unlocking the Power of Skills in the Workplace Many of the organisations we work with at Insight222 have embarked on the road to becoming a skills-based organisation. It is not an easy journey, so it is helpful to learn from other companies who are treading this path. Three of these are Ericsson, Lloyds Banking Group, and Standard Chartered. (1) In his article, Peter Sheppard shares learnings from Ericsson’s skills journey including a) it’s not jobs or skills; it’s skills and jobs, b) it’s a whole organisation activity, c) Less is more with skills, and d) Data drives value. (2) Ben Auty shares insights as to why Lloyds Banking Group is developing a learning culture to build the workforce of the future at the bank, the main skills they are focusing on, and the central role the recently established Reskilling Team is playing. (3) Tanuj Kapilashrami shares how Standard Chartered catalysed their work on skills by identifying adjacencies between ‘sunset’ and ‘sunrise’ roles. We looked at skills adjacencies between ‘sunset’ jobs and ‘sunrise’ jobs: so, what are the jobs that are going to go away? What are the skills that help employees get reskilled into some of these sunrise jobs? We ran five proofs of concept, we showed some real redeployment opportunities and started making the skills narrative real. EMPLOYEE LISTENING, EMPLOYEE EXPERIENCE, AND EMPLOYEE WELLBEING JENNIFER E. SIGLER WITH STEPHANIE DENINO - So Many Stakeholders, So Little Time: State of EX 2023-2024 The fifth annual State of EX study authored by Jennifer E. Sigler, PhD on behalf of The EXchange, Inc, TI PEOPLE and FOUNT Global, Inc. is a treasure chest of insights on the fast-evolving practice of employee experience. It highlights the top four priorities for EX as: (1) Redesigning experiences, (2) Getting broader buy-in for EX work across the organisation, (3) Building an EX roadmap for the organisation, and (4) Getting more / better data. One other standout finding from the study suggests that senior leaders are increasingly focused on EX with a majority of respondents (63%) saying their organisation’s senior leaders view EX as equal to or even more important than other corporate priorities. This bodes well for the future of EX. Thanks to Stephanie Denino and Volker Jacobs for highlighting the study. FIG 13: EX Team Priorities YOY Change (Source: The EXchange, TI People and FOUNT Global, Inc) LEADERSHIP AND CULTURE NADJIA YOUSIF, ASHLEY DARTNELL, GRETCHEN MAY, AND ELIZABETH KNARR - Psychological Safety Levels the Playing Field for Employees | PETER CAPPELLI AND LIAT ELDOR - Can Workplaces Have Too Much Psychological Safety? Two perspectives on psychological safety in the workplace. In the first article, Nadjia Yousif, Ashley Dartnell, Gretchen May, and Elizabeth Knarr present the findings of Boston Consulting Group (BCG) research, which finds how psychological safety benefits inclusion, reduces attrition in diverse groups and effectively acts as an equaliser - enabling diverse and disadvantaged employee groups to achieve the same levels of workplace satisfaction as their more advantaged colleagues. The study also highlights the direct relationship between empathetic leadership and feelings of psychological safety in the workforce, giving leaders a clear directive to be empathetic and thereby engender psychological safety. The second article by Peter Cappelli and Liat Eldor presents research that found that when you move from average to high levels of psychological safety, performance in routine jobs actually declined. FIG 14: Psychological safety has an outsize impact on retention for diversity groups (Source: BCG) RASMUS HOUGAARD, JACQUELINE CARTER, AND ROB STEMBRIDGE - The Best Leaders Can’t Be Replaced by AI While there are some areas where AI is already surpassing or will surpass human capabilities, there are several it cannot replace. Based on their research into employees’ comfort with AI in management, as well as their decades of research on the qualities of effective leadership, Rasmus Hougaard, Jacqueline Carter, and Robert Stembridge identify the promise (and perils) of AI-enabled management (see FIG 15), as well as the three uniquely human capabilities leaders need to focus on honing, especially as AI begins to figure more in management: (1) awareness, (2) compassion, and (3) wisdom. For more from Rasmus, I recommend listening to his podcast discussion with me: How To Be a More Compassionate Leader. Leaders who deepen their ability to lead with humanity will win at attracting, retaining, developing, and motivating top talent. FIG 15: AI versus Human: A matric of leadership activities (Source: Potential Project) DIVERSITY, EQUITY, INCLUSION, AND BELONGING JULIE COFFMAN, ALEX NOETHER, BIANCA BAX, CASSY REICHERT, AND KRYSTLE JIANG - The Business of Belonging: Why making everyone feel included is smart strategy Revealing data from a Bain survey of 6,000+ employees across four countries, which finds employees who have seen their companies intentionally invest in inclusion since 2020 are three times more likely to feel fully included than employees who have not seen such investment from their employers. Other findings include (1) Combining diversity and inclusion maximises a company’s capacity (by 4x) to innovate, and (2) Employees with inclusive leadership are 9x more likely to feel fully included at work (see FIG 16). (Authors: Julie Coffman, Alex Noether, Bianca Bax, Cassy Reichert, and Krystle Jiang). FIG 16: Employees with inclusive leadership are 9x more likely to feel fully included at work (Source: Bain) SHUJAAT AHMAD - DEIB Is At A Crossroads—It’s Time for Bold Action and Clear Metrics Given recent developments it’s reasonable to say that Diversity, Equity, Inclusion, and Belonging (DEIB) is at an existential crossroads. As Shujaat Ahmad writes in his excellent article for Round: “Boards, leadership teams, and investors hold the power to set the tone, shape the policies, and allocate the resources to support DEIB initiatives: for DEIB to work effectively, they must shift from well-intentioned wordsmiths to committed drivers that hold the organization accountable for outcomes and positive change.” Shujaat then unveils his blueprint to help leaders assess progress and drive meaningful change, clarifying the ‘why’ before diving into the ‘how’ covering measuring what matters and interventions (see FIG 17). For more from Shujaat, I recommend visiting Belong and Lead. FIG 17: Source – Shujaat Ahmad HR TECH VOICES Much of the innovation in the field continues to be driven by the vendor community, and I’ve picked out a few resources from January that I recommend readers delve into: ERNEST NG - If the Pitch is Too Smooth, It Probably Is: Why AI in HR is Difficult – Part 2 of an insightful essay from Ernest Ng, PhD of HiredScore (see also Part 1 on disclosures here) where he cuts through the hype to assess how we should be implementing AI in HR. LOUJAINA ABDELWAHED - A Tale of Two Cultures - In One Company - Loujaina Abdelwahed, PhD from Revelio Labs highlights the growing disparity between junior and senior employees (see FIG 18) and identifies the factors causing this malaise. Thanks to Ben Zweig for highlighting. FIG 18: The growing disparity in sentiment between junior and senior employees (Source: Revelio Labs) JEREMIE BRECHEISEN - Where Employees Think Companies’ DEIB Efforts Are Failing – Jeremie K Brecheisen presents findings from Gallup that reveals a disconnect between how well employees and HR leaders believe their organisations are doing when it comes to diversity, equity, inclusion, and belonging: 84% of CHROs say their organisations are increasing investment in DEIB, while only 31% of employees say their organisation is committed to improving racial justice or equity in their workplace (see FIG 19). The article then outlines ten needs employees say are not being met and then offers strategies to help organisations address the disconnect. FIG 19: How employees and HR leaders differ on perceptions of DEIB progress (Source: Gallup) FRANCISCO MARIN - Navigating the ONA Landscape: Trends and Challenges for 2024 - Another good read from Cognitive Talent Solutions, as Francisco Marin explores the key trends and challenges shaping the ONA space in 2024. IAN WHITE - The three C’s of effective performance management – Ian White, CEO at ChartHop, presents the three C’s of performance management — continuous, contextual and cultural — designed to help companies understand their employees more holistically. CHRISTINA JANZER - The surprising connection between after-hours work and decreased productivity – Christina Janzer presents findings from Slack’s Workforce Index, which identifies findings on how to structure the workday to maximise employee productivity, well-being and satisfaction – including the connection between after hours work and decreased productivity. FIG 20: Source – Slack PODCASTS OF THE MONTH In another month of high-quality podcasts, I’ve selected five gems for your aural pleasure: (you can also check out the latest episodes of the Digital HR Leaders Podcast – see ‘From My Desk’ below): AMY EDMONDSON AND LAURIE RUETTIMANN – Right Kind of Failure – Amy Edmondson joins Laurie Ruettimann on the brilliantly named Punk Rock HR to explore the essential role of failure in our professional and personal growth. STACIA GARR, COLE NAPPER, AND SCOTT HINES - People Analytics & HR Tech Research by Industry Analysts – Stacia Sherman Garr, one of the industry’s top analysts, joins Cole Napper and Scott Hines, PhD on the Directionally Correct podcast to discuss the research Stacia and her team at RedThread Research do in the people analytics and HR technology space. RICHARD ROSENOW, MADDIE GRANT, AND SANJA LICINA - How to Build an Integrated Framework for Workforce Listening – In an episode of the Empowering Workplaces podcast, Richard Rosenow joins hosts Maddie Grant and Sanja Licina, Ph.D. to talk about The Three Channels of Workforce Information: conversations (“what people say”), surveys (“what people say they do”) and systems (“what people do”) as a way to build a comprehensive understanding of your workforce. McKINSEY - The shape of talent in 2023 and 2024 - In this episode of McKinsey Talks Talent, Bryan Hancock, Brooke Weddle and host Lucia Rahilly highlight the trends that shaped last year’s talent landscape—and those poised to ‘redefine its contours’ yet again in 2024. MATTHEW BIDWELL AND DAN LONEY – Forecasting 2024 Workplace Trends – Wharton Professor and convenor of the Wharton People Analytics Conference, Matthew Bidwell, joins host of the Wharton Business Daily Dan Loney to look at the year ahead in the workplace. VIDEO OF THE MONTH CHRIS LOUIE, TOMAS CHAMORRO-PREMUZIC, TERRI HORTON, AND LINDSEY SHINTANI - Power a dynamic workforce by embracing AI An enlightening panel discussion from the recent LinkedIn Talent Connect where Chris Louie, Dr Tomas Chamorro-Premuzic, Terri Horton, EdD, MBA, MA, SHRM-CP, PHR, and Lindsey Shintani discuss how AI is changing learning and career paths. They provide guidance on how to overcome AI anxiety and empower impactful futures. BOOK OF THE MONTH KEVIN WHEELER AND BAS VAN DE HATERD – Talent Acquisition Excellence An excellent new book published by Kogan Page and authored by Kevin Wheeler and Bas van de Haterd (He/His/Him). It provides an insightful and detailed analysis of how technologies such as artificial intelligence and machine learning in combination with analytics can improve talent acquisition and recruitment. RESEARCH REPORT OF THE MONTH YUYE DING AND MARK (SHUAI) MA - Return-to-Office Mandates A huge thank you to Nick Bloom for bringing my attention to this paper from Yuye Ding and Mark Ma, which studied the impact of 137 Return to Office mandates on the performance of S&P500 firms from 2020-2023. The key findings, as summarised by Nick, are illuminating: (1) RTO mandates are more likely in firms with poor recent stock performance, and in those with powerful male CEOs. (2) Glassdoor data finds RTO mandates significantly reduce employee ratings for job satisfaction, work-life balance, and senior management. (3) There is no significant impact of RTO mandates on either firm profitability or firm stock-returns. FIG 21: Distribution of firms’ RTO mandates (Source: Yuye Ding and Mark Ma) FROM MY DESK January saw the first three episodes of Series 36 of the Digital HR Leaders podcast, sponsored by our friends at ScreenCloud. Thank you to Luke Farrugia. DAVID GREEN - The best 60 HR & People Analytics articles of 2023 Part 1 | Part 2 – My tenth annual collection of HR and people analytics resources is spread across two articles and ten themes. Part 1 covers i) the future of work and people strategy, ii) workplace design and strategy, iii) AI and the world of work, iv) people analytics, and v) employee experience, listening and wellbeing. Part 2 covers: vi) the evolution of HR, HR operating models and the CHRO, vii) building a data driven culture in HR, viii) workforce planning, skills, and talent marketplace, ix) leadership and culture, and x) diversity, equity, inclusion and belonging. THOMAS RASMUSSEN, DAWN KLINGHOFFER, AND JEREMY SHAPIRO - HR in 2024: The Impact of People Analytics, AI & ML – In a special episode of the Digital HR Leaders podcast to kick off 2024, I was joined by Thomas Rasmussen, Dawn Klinghoffer, and Jeremy Shapiro to discuss the outlook for HR and people analytics in the coming 12 months. SERENA HUANG - How to Enhance Your Career in People Analytics - Serena H. Huang, Ph.D., who has led people analytics functions at companies including GE, PayPal and Kraft Heinz, joins me to discuss the common career paths observed in the people analytics field and how they have evolved over the years. KAZ HASSAN AND LUKE FARUGGIA - How to Bridge the Gap Between Customer and Employee Experience - What can HR learn from marketing's journey in using data, analytics and technology to understand and personalise the customer experience? How can we leverage these insights in HR to boost our employee experience initiatives? Kaz Hassan and Luke Faruggia join me to discuss these topics and more. THANK YOU Finally, this month I’d like to thank: Recruit CRM for nominating me as ‘The People Analytics Pioneer’ in their list of 50 Recruitment Influencers to Follow in 2024 Likewise, a huge thank you to 365Talents for including me as one of the Top 50 HR Influencers to Follow in 2024 Similarly, thanks to HRCap, Inc. for including me in their list of 10 HR Influencers who Provide Remarkable Insights The Social Craft (here) and The Talent Games (here) for also including me in their lists of HR and HR Tech leaders to follow. HRDConnect for quoting me in their article Data Literacy: A must-have for HR professionals in 2024. Gianni Giacomelli for including the Data Driven HR monthly in his list of seven must-read newsletters. HR Geckos for including Excellence in People Analytics as a book recommendation in their HR Bytes Newsletter for January 2024. Sebastian Szachnowski for including Excellence in People Analytics in his list of books to get better at people analytics. Leapsome for including the Digital HR Leaders podcast as one of its Top 10 HR Podcasts for 2024. Similarly, Alexandre Darbois for also including the Digital HR Leaders podcast as one of his 5 HR Podcasts. Melissa Meredith for using my 12 Opportunities for HR in 2024 article to highlight the importance of the HR-Finance partnership in building a thriving company. Bill Brown for also highlighting my 12 Opportunities for HR in 2024 article in his Eleven Trends Transforming the Future of Work in 2024. Mirro.io for including me as a contributor in their list of 15 HR Trends for 2024. Dhanesh K for including as one of his 10 Top HR Leaders to Follow. Lanteria HR for recommending me as one of their HR Experts to Follow in 2024. Semos Cloud for including my 12 Opportunities for HR in 2024 as part of their round-up of HR insights. Thomas Kohler for including my Best HR and People Analytics Articles of 2023 in their collection of HR resources to read. Thinkers360 for including me in their Top Voices EMEA 2023. ABOUT THE AUTHOR David Green ?? is a globally respected author, speaker, conference chair, and executive consultant on people analytics, data-driven HR and the future of work. As Managing Partner and Executive Director at Insight222, he has overall responsibility for the delivery of the Insight222 People Analytics Program, which supports the advancement of people analytics in over 90 global organisations. Prior to co-founding Insight222, David accumulated over 20 years experience in the human resources and people analytics fields, including as Global Director of People Analytics Solutions at IBM. As such, David has extensive experience in helping organisations increase value, impact and focus from the wise and ethical use of people analytics. David also hosts the Digital HR Leaders Podcast and is an instructor for Insight222's myHRfuture Academy. His book, co-authored with Jonathan Ferrar, Excellence in People Analytics: How to use Workforce Data to Create Business Value was published in the summer of 2021. SEE ME AT THESE EVENTS I'll be speaking about people analytics, the future of work, and data driven HR at a number of upcoming events in 2024: Feb 21 - Discover how Leading Companies shift People Analytics from insight to impact (Webinar) Feb 28 - People Analytics World 2024: Exploring the Potential of Analytics and AI in Employee Experience (Zurich) March 4-6 - Gloat Live! (New York) March 14-15 - Wharton People Analytics Conference (Philadelphia) April 24-25 - People Analytics World (London) May 7-9 - UNLEASH America (Las Vegas) September 24-26 - Insight222 Global Executive Retreat (Colorado, US) - exclusively for member organisations of the Insight222 People Analytics Program October 16-17 - UNLEASH World (Paris) More events will be added as they are confirmed.
    Productivity
    2024年03月02日
  • Productivity
    How Generative AI Adds Value to the Future of Work 这篇Upwork的文章深入探讨了生成式人工智能（AI）在重新塑造工作价值方面的变革力量，强调了自动化和创新不仅改变了工作岗位，还在各个行业提高了生产力和创造力。文章着重讨论了对劳动力市场的细微影响，强调了技能发展和道德考虑的重要性，并对人工智能与人类合作的未来提供了前瞻性的视角。 Authors:  Dr. Ted Liu, Carina Deng, Dr. Kelly Monahan Generative AI’s impact on work: lessons from previous technology advancements In this study, we provide a comprehensive analysis of the initial impact of generative AI (artificial intelligence) on the Upwork marketplace for independent talent. Evidence from previous technological innovations suggests that AI will have a dual impact: (1) the displacement effect, where job or task loss is initially more noticeable as technologies automate tasks, and (2) the reinstatement effect, where new jobs and tasks increase earnings over time as a result of the new technology. Take for example the entry of robotics within the manufacturing industry. When robotic arms were installed along assembly lines, they displaced some of the tasks that humans used to do. This was pronounced in tasks that were routine and easy to automate. However, new tasks were then needed with the introduction of robotics, such as programming the robots, analyzing data, building predictive models, and maintaining the physical robots. The effects of new technologies often counterbalance each other over time, giving way to many new jobs and tasks that weren’t possible or needed before. The manufacturing industry is now projected to have more jobs available as technologies continue to advance, including Internet of Things (IoT), augmented reality, and AI, which transform the way work is completed. The issue now at hand is ensuring enough skilled workers are able to work alongside these new technologies. While this dynamic of displacement and reinstatement generally takes years to materialize, as noted above in the manufacturing example, the effects of generative AI may be taking place already on Upwork. For the platform as a whole, we observe that generative AI has increased the total number of job posts and the average spend per new contract created. In terms of work categories, generative AI has reduced demand in writing and translation, particularly in low-value work, while enhancing earnings in high-value work across all groups. In particular, work that relies on this new technology like Data Science and Analytics are reaping the benefits. The report highlights the importance of task complexity and the skill-biased nature of AI's impact. Skills-biased technology change is to be expected as the introduction of new technologies generally favors highly skilled workers. We observe this on our platform as high-skill freelancers in high-value work are benefiting more, while those in low-value work face challenges, underscoring the need for skilling and educational programs to empower freelancers to adapt and transition in this evolving work landscape. Understanding the lifecycle of work on Upwork and the impact of gen AI Generative AI has a growing presence in how people do their work, especially since the public release of ChatGPT in 2022. While there’s been extensive discussion about the challenges and opportunities of generative AI, there is limited evidence of such impact based on transaction data in the broader labor market. In this study, we use Upwork’s platform data to estimate the short-term effects of generative AI on freelance outcomes specifically. The advantage of the Upwork platform is that it is in itself a complete marketplace for independent talent, as we observe the full life cycle of work: job posts, matching, work execution, performance reviews, and payment. Few other instances exist where a closed-system work market can be studied and observed. Thus, the results of this study offer insights into not only the online freelance market, but also the broader labor market. How technological progress disrupts the labor market is not a new topic. Acemoglu and Restrepo (2019) argue that earning gain arises from new tasks created by technological progress, which they term the “reinstatement effect,” even if the automation of certain tasks may have a displacement effect in the labor market initially. What this means is that there may be a dynamic effect going on: the displacement effect (e.g., work loss) may be more noticeable in the beginning of a new technology entry, but as new jobs and tasks are being created, the reinstatement effect (e.g., rates increase, new work) will begin to prevail. In the broader labor market, such dynamics will likely take years to materialize. But in a liquid and active independent work marketplace like Upwork, it’s possible that we’re already observing this transition happening. Existing studies such as this provides a useful conceptual framework to think about the potential impact of generative AI. It’s likely that in the short term, the replacement of generative AI will continue to be more visible, not just at Upwork, but also in the broader labor market. Over time and across work categories, however, generative AI will likely spur new tasks and jobs, leading to the reinstatement effect becoming stronger and increasing rates for those occupations with new tasks and a higher degree of task complexity. We’ve already seen evidence of new demand as a result of gen AI on our Upwork platform, with brand new skill categories like AI content creator and prompt engineer emerging in late 2022 and early 2023. We test this hypothesis of both work displacement and reinstatement, and provide insights into how generative AI affects work outcomes. Impact of generative AI on work To understand the short-term impact of generative AI on the Upwork freelance market, we capitalize on a natural experiment arising from the public release of ChatGPT in November 2022. Because this release was largely an unanticipated event to the general public, we’re able to estimate the causal impact of generative AI. The essential idea behind this natural experiment is that we want to compare the work groups affected by AI with the counterfactual in which they are not. To implement this, we use a statistical and machine-learning method called synthetic control. Synthetic control allows us to see the impact that an intervention, in this case, the introduction of gen AI, has on a group over time by comparing it to a group with similar characteristics not exposed to the intervention. The advantage of this approach is that it allows us to construct reasonably credible comparison groups and observe the effect over time. The units of analysis we use are work groups on the Upwork platform; we analyze variables such as contract number and freelancer earnings. Instead of narrowly focusing on a single category like writing, we extend the analysis to all the major work groups on Upwork. Moreover, we conduct additional analysis of the more granular clusters within each major group. The synthetic control method allows for flexibility in constructing counterfactuals at different levels of granularity. The advantage of our comprehensive approach is that we offer a balanced view of the impact of generative AI across the freelance market. Generative AI’s short-term impact on job posts and freelancer earnings Looking at the platform as a whole, we observe that generative AI has increased the total number of job posts by 2.4%, indicating the overall increased demand from clients. Moreover, as shown in Figure 1, for every new job contract, there is an increase of 1.3% in terms of freelancer earnings per contract, suggesting a higher value of contracts. Figure 1 Effect of Generative AI on Freelancer Earning per Contract The Upwork platform has three broad sectors: 1. Technological and digital solutions (tech solutions); 2. Creative & outreach; 3. Business operations and consulting. We have observed both positive and negative effects within each of the sectors, but two patterns are worth noting: The reinstatement effect of generative AI seems to be driving growth in freelance earnings in sectors related to tech solutions and business operations. In contrast, within the creative sector, while sales and marketing earnings have grown because of AI, categories such as writing and translation seem disproportionately affected more by the replacement effect. This is to be expected due to the nature of tasks within these categories of work, where large language models are now able to efficiently process and generate text at scale. Generative AI has propelled growth in high-value work across the sectors and may have depressed growth in low-value work. This supports a skills-biased technology change argument, which we’ve observed throughout modern work history. More specifically and within tech solutions, data science & analytics is a clear winner, with over 8% of growth in freelance earnings attributed to generative AI. This makes sense as the reinstatement effect is at work; new work and tasks such as prompt engineering have been created and popularized because of generative AI. Simultaneously, while tools such as ChatGPT automate certain scripting tasks (therefore leading to a replacement effect), it mainly results in productivity enhancements for freelancers and potentially leads to them charging higher rates and enjoying higher overall earnings per task. In terms of contracts related to business operations, we observe that accounting, administrative support, and legal services all experience gains in freelance earnings due to generative AI, ranging from 6% to 7%. In this sector, customer service is the only group that has experienced reduced earnings (-4%). The reduced earnings result for customer service contracts is an example of the aggregate earnings outcomes of AI, related to the study by Brynjolfsson et al (2023), who find that generative AI helps reduce case resolution time at service centers. A potential outcome of this cut in resolution time is that service centers will need fewer workers, as more tasks can be completed by a person working alongside AI. At the same time, the reinstatement effect has not materialized yet because there are no new tasks being demanded in such settings. This may be an instance where work transformation has not yet been fully realized, with AI enabling faster work rather than reinventing a way of working that leads to new types of tasks. A contrasting case is the transformation that happened with bank tellers when ATMs were introduced. While the introduction of these new technologies resulted in predictions of obsolete roles in banks, something different happened over time. Banks were able to increase efficiency as a result of ATMs and were able to scale and open more branches than before, thereby creating more jobs. In addition, the transactional role of a bank teller became focused on greater interpersonal skills and customer relationship tasks. When taken together, the overall gains in such business operations work on Upwork are an encouraging sign. These positions tend to require relatively intensive interpersonal communication, and it seems the short-term effects of generative AI have helped increase the value of these contracts, similar to what we saw in the banking industry when ATMs were introduced. As of now, the replacement effect of AI seems more noticeable in creative and outreach work. The exception is sales and marketing contracts, which have experienced a 6.5% increase in freelance earnings. There is no significant impact yet observed on design. For writing and translation, however, generative AI seems to have reduced earnings by 8% and 10% respectively. However, as we will discover, task complexity has a moderating effect on this. High-value work benefit from generative AI, upskilling needed for low-value work Having discussed the overall impact of generative AI across categories, we now decompose the impact by values. The reason we’re looking at the dimension of work value is that there may be a positive correlation between contract value and skill complexity. Moreover, skill complexity may also be positively correlated with skill levels. Essentially, by evaluating the impact of AI by different contract values, we can get at the question of AI's impact by skill levels. This objective is further underscored by a discrepancy that sometimes exists in the broader labor markets – a skills gap between demand and supply. It simply takes time for upskilling to take place, so it’s typical for demand to exceed supply until a more balanced skilled labor market takes place. It is worth noting, however, freelancers on the Upwork platform seem more likely than non-freelancers to acquire new skills such as generative AI. For simplicity, let’s assume that the value of contracts is a good proxy for the level of skill required to complete them. We’d then assume that high-skill freelancers typically do high-value work, and low-skill freelancers do low-value work. In other words, our goal is also to understand whether the impact of generative AI is skills-biased and follows a similar pattern from what we’ve seen in the past with new technology disruptions. Note that we’re focusing on the top and bottom tails of the distribution of contract values, because such groups (rather than median or mean) might be most susceptible to displacement and/or reinstatement effects, therefore of primary concern. We define high-value (HV) work as those with $1,000 or more earnings per contract. For the remaining contracts, we focus on a subset of work as low-value (LV) work ($251-500 earnings). Figure 2 shows the impact of AI by work value, across groups on Upwork. As we discussed before, writing and translation work has experienced some reduction in earnings overall. However, if we look further into the effect of contract value, we see that the reduction is largely coming from the reduced earnings from low-value work. At the same time, for these two types, generative AI has induced substantial growth in high-value earnings – the effect for translation is as high as 7%. We believe the positive effect on translation high-value earning is driven by more posts and contracts created. In the tech solutions sector, the growth in HV earnings in data science and web development is also particularly noticeable, ranging from 6% to 9%. Within the business solutions sector, administrative support is the clear winner. There are two takeaways from this analysis by work value. First, while we’re looking at a sample of all the contracts on the platform, it’s possible that the decline of LV work is more than made up for by the growth of HV work in the majority of the groups. In other words, except for select work groups, the equilibrium results for the Upwork freelance market overall seem to be net positive gains from generative AI. Second, if we assume that freelancers with high skills (or a high degree of skill complexity) tend to complete such HV work (and low-skill freelancers do LV work), we observe that the impact of generative AI may be biased against low-skill freelancers. This is an important result: In the current discussion of whether generative AI is skill-based, there exists limited evidence based on realized gains and actual work market transactions. We are one of the first to provide market-transaction-based evidence to illustrate this potentially skill-biased impact. Finally, additional internal Upwork analysis finds that independent talent engaged in AI-related work earn 40% more on the Upwork marketplace than their counterparts engaged in non-AI-related work. This suggests there may be additional overlap between high-skill work and AI-related work, which can further reinforce the earning potential of freelancers in this group. Figure 2 Case study: 3D content work To illustrate the impact of generative AI in more depth, we have conducted a case study of Engineering & Architecture work within the tech solutions sector. The reason is that we want to illustrate the potentially overlooked aspects of AI impact, compared with the examples of data science and writing contracts. This progress in generative AI has the potential to reshape work in traditional areas like design in manufacturing and architecture, which rely heavily on computer-aided design (CAD) objects, and newer sectors such as gaming and virtual reality, exemplified by NVIDIA's Omniverse. Based on activities on the Upwork platform, we see that there is consistent growth of job posts and client spending in this category, with up to 12% of gross service value growth year over year in 2023 Q3, and over 11% in job posts during the same period. Moreover, applying the synthetic control method, we show a causal relationship between gen AI advancements and the growth in job posts and earnings per contract. More specifically, there is a significant increase in overall earnings because of AI, an average 11.5% increase. Additionally, as shown by Figure 3, the positive effect also applies to earning per contract. This indicates a positive impact on freelancer productivity and quality of work, due to the fact that we’re measuring the income for every unit of work produced. This suggests that gen AI is not just a facilitator of efficiency but also enhances the quality of output. ‍Figure 3 Effect of Generative AI on Freelancer Earning per Contract in EngineeringIn a traditional workflow to create 3D objects without generative AI, freelancers would spend extensive time and effort to design the topology, geometry, and textures of the objects. But with generative AI, they can do so through text prompts to train models and generate 3D content. For example, this blog by NVIDIA’s Omniverse team showcases how ChatGPT can interface with traditional 3D creation tools. Thus, the positive trajectory of generative AI in 3D content generation we see is driven by several factors. AI significantly reduces job execution time, allowing for higher productivity. It facilitates the replication and scaling of 3D objects, leading to economies of scale. Moreover, freelancers can now concentrate more on the creative aspects of 3D content, as AI automates time-consuming and tedious tasks. This shift has not led to a decrease in rates due to the replacement effect. In fact, this shift of workflow may create new tasks and work. We will likely see a new type of occupation in which technology and humanities disciplines converge. For instance, a freelancer trained in art history now has the tools to recreate a 3D rendering of Japan in the Edo period, without the need to conduct heavy coding. In other words, the reinstatement effect of AI will elevate the overall quality and value proposition of the work, and ultimately enable higher earning gains. This paradigm shift underscores generative AI's role in not just transforming work processes but also in creating new economic dynamics within the 3D content market. Fortunately, it seems many freelancers on Upwork are ready to reap the benefits: 3D-related skills, such as 3D modeling, rendering, and design, are listed among the top five skills of freelancer profiles as well as in job posts. A dynamic interplay: task complexity, skills, and gen AI Focusing on the Upwork marketplace for independent talent, we study the impact of generative AI by using the public release of ChatGPT as a natural experiment. The results suggest a dynamic interplay of replacement and reinstatement effects; we argue that this dynamic is influenced by task complexity, suggesting a skill-biased impact of gen AI. Analysis across Upwork's work sectors shows varied effects: growth in freelance earnings in tech solutions and business operations, but a mixed impact in the creative sector. Specifically, high-value work in data science and business operations see significant earnings growth, while creative contracts like writing and translation experience a decrease in earnings, particularly in lower-value tasks. Using the case study of 3D content creation, we show that generative AI can significantly enhance productivity and quality of work, leading to economic gains and a shift toward higher-value tasks, despite initial concerns of displacement. Acemoglu and Restrepo (2019) argue that the slowdown of earning growth in the United States the past three decades can partly be explained by new technologies’ replacement effect overpowering the reinstatement effect. But with generative AI, we’re at a point of completely redefining what human tasks mean, and there may be ample opportunities to create new tasks and work. It's evident that while high-value types of work are being created, freelancers engaged in low-value tasks may face negative impact, possibly due to a lack of skills needed to capitalize on AI benefits. This situation underscores the necessity of supporting freelancers not only in elevating their marketability within their current domains but also in transitioning to other work categories. To ensure as many people as possible benefit, there’s an imperative need to provide educational resources for them to gain the technical skills, and more importantly skills of adaptability to reinvent their work. This helps minimize the chance of missed opportunities by limiting skills mismatch between talent and new demands created by new technologies. Upwork has played a significant role here by linking freelancers to resources such as Upwork Academy’s AI Education Library and Education Marketplace, thereby equipping them with the necessary tools and knowledge to adapt and thrive in an AI-present job market. This approach can help bridge the gap between low- and high-value work opportunities, ensuring a more equitable distribution of the advantages brought about by generative AI. Methodology To estimate the causal impact of generative AI, we take a synthetic control approach in the spirit of Abadie, Diamond, and Hainmueller (2010). The synthetic control method allows us to construct a weighted combination of comparison units from available data to create a counterfactual scenario, simulating what would have happened in the absence of the intervention. We use this quasi-experimental method due to the infeasibility of conducting a controlled large-scale experiment. Additionally, we use Lasso regularization to credibly construct the donor pool that serves the basis of the counterfactuals and minimize the chance of overfitting the data. Moreover, we supplement the analysis by scoring whether a sub-occupation is impacted or unaffected by generative AI. The scoring utilizes specific criteria: 1. Whether a certain share of job posts are tagged as AI contracts by the Upwork platform; 2. AI occupational exposure score, based on a study by Felten, Raj, and Seamans (2023), to tag these sub-occupations. We also use data smoothing techniques through three-month moving averages. We analyzed data collected on our platform from 2021 through Q3 2023. We specifically look at freelancer data across all 12 work categories on the platform for high-value contracts, defined as those with a contract of at least $1,000, and low-value contracts, consisting of those between $251 and under $500. The main advantage of our approach is that it is a robust yet flexible way to identify the causal effects on not only the Upwork freelance market but also specific work categories. Additionally, we control for macroeconomic or aggregate shocks such as U.S. monetary policy in the pre-treatment period. However, we acknowledge the potential biases in identifying which sub-occupations are influenced by generative AI and the effects of external factors in the post-treatment period. About the Upwork Research Institute The Upwork Research Institute is committed to studying the fundamental shifts in the workforce and providing business leaders with the tools and insights they need to navigate the here and now while preparing their organization for the future. Using our proprietary platform data, global survey research, partnerships, and academic collaborations, we produce evidence-based insights to create the blueprint for the new way of work. About Ted Liu Dr. Ted Liu is Research Manager at Upwork, where he focuses on how work and skills evolve in relation to technological progress such as artificial intelligence. He received his PhD in economics from the University of California, Santa Cruz. About Carina Deng Carian Deng is the Lead Analyst in Strategic Analytics at Upwork, where she specializes in uncovering data insights through advanced statistical methodologies. She holds a Master's degree in Data Science from George Washington University. About Kelly Monahan Dr. Kelly Monahan is Managing Director of the Upwork Research Institute, leading our future of work research program. Her research has been recognized and published in both applied and academic journals, including MIT Sloan Management Review and the Journal of Strategic Management.
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    2024年02月21日
  • Productivity
    2024年人力资源预测：全球追求生产力 In this fast-evolving era, all companies and individuals are seeking for change and efficiency. We can see the core of productivity in the new year: AI. Let's have a look at details on the Josh Bersin Predictions for 2024. 在过去的二十年里，我一直在写关于人力资源预测的文章，但今年不同。我看到这一年打破了范式，改变了商业中的每一个角色。不仅人工智能会改变每家公司和每一项工作，而且公司将开始不懈地寻求生产力。 想想我们的过去。2008年金融危机后，世界开始了加速增长的零利率时期。公司增加了收入，雇用了员工，并看着他们的股价上涨。招聘继续以狂热的速度进行，导致2019年底失业率创下3.5%的历史新低。 随之而来的是大流行，在六个月内，一切都停滞不前。2020年4月，失业率飙升至15%，公司将人们送回家，我们重新设计了我们的产品、服务和经济，以应对远程工作、混合工作制和对心理健康的关注。 一旦经济再次启动（由于美国的财政刺激），公司又回到了旧的招聘周期。但随着利率上升和需求不足，我们看到裁员一再发生，在过去的18个月里，我们看到了招聘、裁员，然后再次招聘以复苏经济。 为什么会出现跷跷板效应？ 首席执行官和首席财务官正处于我们所说的“工业时代”——招聘以增长经济，然后在事情好转时裁员。 今天，当我们进入2024年时，一切都不同了。我们必须“囤积人才”，投资于生产力，并重新开发和重新部署人员以实现增长。 我们生活在一个失业率为 3.8% 的世界，几乎每个职位都存在劳动力短缺，劳动力权力日益增强，员工需求不断涌现：对加薪、灵活性、自主权和福利的要求。每年有超过20%的美国员工换工作（每月2.3%），其中近一半的变化是进入新行业。 为什么这是“新常态”？ 有几个原因。首先，正如我们在全球劳动力情报研究中所讨论的那样，行业是重叠的。每家公司都是数字化公司；每家公司都希望建立经常性收入来源；很快，每家公司都将使用人工智能。过去停留在行业内的职业正在转变为“基于技能的职业”，让人们比以往任何时候都更容易跳槽。 其次，员工（尤其是年轻员工）感到有权按照自己的意愿行事。他们可能会悄悄地辞职，“做兼职”，或者抽出时间转行。他们看到自己的生活很长（人们的寿命比 1970 年代和 1980 年代长得多），所以他们不介意离开你的公司去其他地方。 第三，生育率持续下降，劳动力短缺加剧。日本、中国、德国和英国的劳动力人口都在萎缩。在未来十年左右的时间里，大多数其他发达经济体也将如此。 第四，工会正在崛起。由于华盛顿的新理念，我们看到了谷歌、亚马逊、星巴克、GM、福特、Stellantis、凯撒、迪士尼、Netflix等公司的劳工活动。虽然工会参与率不到美国劳动力的11%，但在欧洲要高得多，而且这一趋势正在上升。 这一切意味着什么？ 这有很多影响。 首先，公司将更加专注于建立高保留率的工作模式（有人称之为“劳动力囤积”）。这意味着改善薪酬公平，继续混合工作模式，投资于以人为本的领导力，并为员工提供在公司内部从事新职业的机会。这就是为什么人才市场、基于技能的发展和工作流程中的学习如此重要的原因。 其次，CEO必须了解员工的需求、愿望和要求。正如爱德曼的最新研究表明的那样，职业发展现在位居榜首，同时对授权、影响力和信任的渴望也排在首位。我们称之为“员工激活”的新主题：倾听员工的意见，并将有关他们工作的决定委托给他们的经理、团队和领导者。 第三，传统的“雇佣成长”模式并不总是奏效。在这个后工业时代，我们必须系统地运作，将内部发展、工作再设计、经验和招聘放在一起。这汇集了招聘、奖励和薪酬、学习与发展以及组织设计等独立领域。（阅读我们的系统性人力资源研究了解更多信息。） “业务绩效”的真正含义是什么？ 如果你是首席执行官，你希望增长收入、增加市场份额、提高盈利能力和可持续性。如果你不能通过招聘来成长（而员工不断以奇怪的方式“激活”），你还有什么选择？这很简单：您可以自动化生产并专注于生产力。 虽然这张图表令人印象深刻，但它给每个CEO都引出了一个问题：我们在这张图表上的位置是什么？我们的运营速度是否与同行一样快、一样高效？ 我认为这导致了一种我称之为“生产力优势”的策略。如果你能帮助你的公司更快地发展（生产力意味着速度，而不仅仅是利润），你就可以比你的竞争对手更快地进行重塑。这才是真正让CEO们夜不能寐的原因。 考虑一下普华永道最新的CEO调查数据。今年，我们必须比以往任何时候都更快地重塑我们的公司。到2024年，45%的CEO（去年为39%）认为他们的业务在十年内将无法生存。 生产力优势 为什么生产力如此重要？有四个原因。 首先，CEO们关心它。 2024 年普华永道 CEO 调查发现，CEO 认为公司 40%的工作浪费了生产力。 尽管这听起来令人震惊，但对我来说却是真实的：太多的电子邮件、太多的会议、混乱的招聘流程、官僚主义的绩效管理等等。（HR 就有其中一些问题。） 其次，AI让人生产力优势成为可能。 人工智能的应用旨在提高白领的生产力。（过去大多数自动化都有助于蓝领或灰领工人。）生成式 AI 让我们能够更快地查找信息，了解趋势和异常值，训练自己和学习，并清理我们随身携带的文档、工作流程、门户以及后台合规和管理混乱的系统。 第三，公司的发展需要AI。 当很难找招聘到人时，你将如何成长？去年，招聘时间增加了近20%，就业市场变得更加艰难。你能在技术技能上与谷歌或OpenAI竞争吗？ 内部开发、重组和自动化项目就是答案。有了生成式人工智能，机会无处不在。 第四，生产力推动重塑。 如果你考虑重塑你公司（新产品、利用人工智能、进入新市场等）的需求，最大的障碍是惯性。为什么诺基亚和黑莓的手机业务输给了苹果？因为这些公司“又胖又快乐”。在这个人才和技能短缺的时代，这是灾难的根源。 普华永道（PwC）估计，“效率低下”产生了对GDP10万亿美元的税收，相当于全球GDP的7%。这种税收阻碍了您的公司转型。每当我们简化、减少会议并更好地定义决策权时，我们都会加快并实现变革。 这一切对人力资源意味着什么？ 正如我在《人力资源预测》中所描述的那样，我们有很多问题需要解决。 我们必须加快向动态工作和组织结构的转变。我们必须专注于和务实地对待技能。我们必须重新思考“员工体验”，并处理我们所说的“员工激活”。我们将不得不对我们的人力资源技术、招聘和L&D系统进行现代化改造，以利用人工智能并使这些系统更加有用。 我们的人力资源团队也将由人工智能驱动。正如我们的Galileo™客户告诉我们的那样，一个架构良好的“专家助理”可以彻底改变人力资源人员的工作方式。我们可以成为“全栈”人力资源专业人员，在几秒钟而不是几周内找到有关我们团队的数据，几秒钟与一线领导分享人力资源、领导力和管理实践。（Galileo被一些世界上最大的公司用作管理教练。） 还有一些其他变化。随着公司专注于“通过生产力实现增长”，我们必须考虑每周 4 天的工作制，我们如何将混合工作制度化，以及如何以更有效的方式连接和支持远程工作者。我们必须重新关注领导力发展，在一线经理身上花费更多的时间和金钱，并继续投资于文化和包容性。我们必须简化和重新思考绩效管理，我们必须解决令人头疼的薪酬公平问题。 还有更多。 DEI 计划必须嵌入到业务中（人力资源 DEI 警察的时代已经结束）。我们必须清理我们的员工数据，以便我们的人工智能和人才情报系统准确且值得信赖。正如我们的系统性人力资源研究所指出的那样，我们必须将思维从“支持业务”转变为“成为有价值的顾问”，并将我们的人力资源服务产品化。 所有这些都在我们本周发布的40页新报告“2024 年人力资源预测”中进行了详细说明，其中包括一系列行动计划，以帮助您思考所有这些问题。 让我提醒你一个大观念。生产力是人力资源部门存在的原因。 我们所做的一切，从招聘到辅导，从开发到组织设计，只有在帮助公司成长的情况下才能成功。作为人员流动、敬业度、技能和领导力方面的专家，我们人力资源部门每天都在提高员工和组织的生产力。2024年是专注于这一更高使命的一年。 最后一件事：照顾好自己。 该报告有15个详细的预测，每个预测都有一系列需要考虑的行动步骤。最后一个真正适合你：专注于人力资源的技能和领导力。作为流程的管理者，我们必须专注于我们自己的能力。2024年将是成长、学习和团队合作的一年。如果我们处理好这15个问题，我们将帮助我们的公司在未来一年蓬勃发展。 Josh Bersin预测的详细信息 预测研究是我们每年阅读量最大的报告。它包括我们所有研究的详细摘要，并讨论了首席执行官、首席人力资源官和人力资源专业人士的15个基本问题。它将以以下形式提供： 包含详细信息的信息图。（点击这里) Source JOSH BERSIN
    Productivity
    2024年02月01日
  • Productivity
    2024 年工作场所沟通状况 随着在家工作的劳动力比例增加到 58%（9200 万人），数字通信已成为工作场所沟通和生产力的焦点。经过分析，《福布斯顾问》发现科罗拉多州和马里兰州的远程工作者数量最多。调查还发现，28% 的受访者表示使用互联网语音协议 (VoIP) 电话系统。虽然我们调查的一半受访者在混合环境中工作，但 27% 的受访者远程工作，20% 的受访者现场工作。 要点 员工平均每周花费 20 个小时使用数字通信工具。 由于使用数字通信，45% 的员工感觉与团队的联系更加紧密。 数字通信让 58% 的员工觉得他们需要更频繁地联系。 百分之六十的员工因数字化沟通而感到更加倦怠。 近一半的员工表示，他们的生产力受到无效沟通的影响。 42% 的员工在试图形成传达正确语气的反应时感到压力。 2023 年工作场所使用的通讯工具 尽管如今有许多其他通信平台，但电话的时代可能还没有过去。工人们发现，更有效的通信平台取决于其提供的通信类型，无论是即时消息、视频通话还是 VoIP 系统。Google Meet 和 Zoom 在视频通话方面排名最高，分别有 40% 和 46% 的受访者使用。 远程和混合工作人员比办公室工作人员更频繁地使用 VoIP 系统进行通信。超过四分之一的受访者使用 VoIP 系统，其中 37% 的远程员工使用该系统，23% 的现场员工使用该系统，24% 的混合员工使用该系统。 适合办公室员工、混合员工和远程员工的最有效的通信工具 最有效的沟通工具因现场、远程和混合工作人员而异。对于现场工作人员来说，38% 的受访者认为手机是最有效的沟通方式，其次是固定电话 (22%) 和 Zoom (21%)。对于远程工作的人来说，22% 的受访者认为 Zoom 是最有效的方法，Google Chat（同样是 22%）也是如此。混合型员工也遵循类似的趋势：31% 的人认为 Zoom 是最有效的，23% 的人认为 Google Meet 是最有效的。 Covid-19 如何继续影响工作沟通 大多数人在工作中会使用标准电话以外的工具进行沟通，其中 14% 的受访者在大流行之前没有使用VoIP 。其中超过 20% 是远程工作者。显然，越来越多的人开始使用 Zoom（占受访者的 24%），但 2020 年 3 月 1 日之后，手机的使用量也激增了 20%。 自 Covid-19 以来，超过 40% 的员工感觉与团队的联系更加紧密 虽然 Covid-19 改变了办公室和团队的沟通方式，但这并不一定会导致员工感觉整体联系减少。在 Covid-19 疫情之后，总共 45% 的接受调查的员工实际上感觉与团队的联系更加紧密（43% 的现场员工、52% 的远程员工和 46% 的混合员工）。 一些员工确实感觉联系较少（25%）。远程员工最有可能表示感觉联系较少 (34%)，而现场员工 (27%) 和混合员工 (20%) 的比例较低。也有一些人没有经历任何变化。在这些受访者中，现场工作人员最有可能表示没有变化（28%）。 大多数员工每周使用数字通讯工具的时间长达 20 小时 许多员工一整天都在屏幕前度过。比例最高的受访者 (16%) 表示，他们每周在数字通信平台上花费 21 至 25 小时。平均每天大约五个小时。 15% 的人花费了 16 至 20 小时，14% 的人花费了 11 至 15 小时，12% 的人花费了 6 至 10 小时。当数字达到 31 至 35 小时时，这一数字急剧下降：只有 5% 的人表示他们在数字通信工具上花费了这么多时间。2% 的受访者每周使用数字通讯工具的时间超过 40 小时。 数字通信工具正在影响工作与生活的平衡 有了如此多的数字通信工具，越来越多的员工感受到了在正常工作时间之外与同事保持联系的压力。近 25% 的员工表示，他们总是因与同事保持联系而感到压力，而 35% 的员工表示，他们经常感到压力。而另一端——那些感觉没有压力的人——数量要少得多。7% 的人表示他们很少感到压力，而 10% 的人表示他们从不感到压力。 数字通信增加了 60% 员工的职业倦怠 无论是在家工作、在现场工作还是两者兼而有之，数字通信很可能会增加倦怠感。我们的调查显示，60% 的受访者表示数字通信增加了倦怠感。近 70% 的远程工作人员表示，他们因数字通信而感到倦怠。混合型员工和现场员工因数字通信而感到倦怠的可能性较小：分别为 56% 和 49%。 无效的沟通如何影响工作环境 只有 11% 的员工表示，无效的沟通对他们没有任何影响。对于其他受访者来说，沟通不畅极大地影响了许多地区的工人。最值得注意的是，它影响了 49% 受访者的工作效率。近 50% 的受访者表示，无效的沟通会影响工作满意度，而 42% 的受访者表示，这会影响压力水平。 沟通不畅正在影响 45% 员工的信任 对于超过 40% 的员工来说，沟通不畅会降低对领导层和团队的信任。远程工作人员受到的影响更大，54% 的人表示沟通不畅会影响对领导层的信任，52% 的人表示会影响对团队的信任。对于现场员工来说，沟通不畅并没有对信任产生同样程度的影响，尽管它仍然产生了很大的影响：43% 的人表示对领导层的信任受到了影响，38% 的人表示对团队的信任受到了影响。 工作满意度取决于大多数员工的有效沟通 受访者表示，有效的沟通影响了多个工作领域。42% 的人表示这影响了跨职能协作。工作满意度是另一个受沟通影响的重要领域：48% 的人表示他们受到了影响。近一半的受访者表示他们的生产力受到了影响。 数字通信工具正在增加工作场所的压力 对于 46% 的受访者来说，看到消息长时间被忽视会导致工作场所产生压力。45% 的受访者表示，他们的经理正在输入消息的通知给他们带来了压力。数字通信的许多其他方面也带来了压力：用正确的语气制作数字回复（42%）、破译数字消息背后的语气（38%）、领导层最后一刻的视频通话（36%）以及转向进行视频通话时关闭摄像头 (35%)。 大多数员工更喜欢电子邮件而不是其他数字通信选项 当谈到首选的沟通方式时，许多员工更喜欢老式工具。电子邮件是最受欢迎的工具，18% 的受访者将其标记为首选（25% 的远程工作人员和 10% 的现场工作人员）。视频通话是第二受欢迎的选择（17%），其次是直接消息（16%）。对于现场工作人员来说，面对面对话是迄今为止最喜欢的沟通方式，34% 的受访者表示这是他们的偏好。 不同性别的偏好相同，但在视频通话方面差异很大：22% 的男性受访者更喜欢视频，12% 的女性更喜欢视频。 年龄对沟通方式的偏好产生了影响：59 至 77 岁之间的受访者中有 40% 更喜欢面对面交谈，而 18 至 26 岁的受访者中只有 17% 的受访者喜欢面对面交谈，而 27 至 42 岁的受访者中只有 16% 的受访者更喜欢面对面交谈。 员工如何使用数字通信进行联系 对于许多员工来说，数字通信是他们日常生活的重要组成部分，但他们使用的通信方法有所不同。超过一半 (56%) 的受访者使用视频进行交流，55% 使用音频。个性化问候不太常见（44%）。表情符号和 GIF 仍然是相对常见的交流形式：分别为 42% 和 34%。 女性受访者比男性受访者更喜欢个性化问候：分别为 47% 和 40%。 男性受访者比女性受访者更喜欢音频：63% 和 50%。视频也遵循类似的模式：61%（男性）对 53%（女性）。 43 至 58 岁的受访者对 GIF 的偏好最高：42%，而 18 至 26 岁的受访者为 31%。 18 岁至 26 岁之间的受访者最有可能喜欢视频 (69%)。对视频的偏好随着年龄的增长而下降：60% 的受访者年龄在 27 岁至 42 岁之间，50% 的受访者年龄在 43 岁至 58 岁之间，只有 23% 的受访者年龄在 59 岁至 77 岁之间。 每个州有多少人仍然在家工作？ Forbes Advisor 统计了 2023 年各州在家工作的总人数。调查发现，远程工作者的比例因州而异。在在家工作劳动力最多的 11 个州中，有 20% 至 24.2% 的人在家工作。 华盛顿州在家工作的人数比例最高，占在家工作劳动力的 24.2%，其次是马里兰州 (24%) 和科罗拉多州 (23.7%)。 马萨诸塞州是在家工作比例最高的州（23.7%），其次是俄勒冈州（22.7%）、弗吉尼亚州（22.3%）和新泽西州（22.1%）。 密西西比州在家工作的劳动力数量最少。在 120 万工人中，只有 6.3%（76,556 人）在家工作。 结论 自 Covid-19 以来，虽然数字通信世界发生了很大变化，但也有一些不变的事情。尽管有许多选项和工具可用，但电子邮件和电话仍然是最受欢迎的两种通信方式。VoIP 系统也越来越受欢迎，28% 的受访者使用它们。员工平均每周在数字通信平台上花费 20 小时，这是每周 40 小时工作时间的一半。 展望未来，对于团队和小型企业来说，建立高效的数字通信系统非常重要，特别是考虑到我们调查的一半以上的人表示数字通信会导致职业倦怠加剧。 如果公司或团队围绕数字通信建立健康的文化，则可能会带来更好的工作满意度、更高的生产力以及对公司领导层和团队的更高信任度。 方法 Forbes Advisor 根据市场研究协会的行为准则，委托市场研究公司 OnePoll 对 1,000 名在办公室工作的美国人进行了调查。置信度为 95% 时，误差幅度为 +/- 3.1 个点。OnePoll 研究团队是 MRS 的成员，并且是美国民意研究协会 (AAPOR) 的企业会员。 为了了解每个州在家工作的工人数量，《福布斯顾问》从人口普查局的美国社区调查中获取了数据。 https://www.forbes.com/advisor/business/digital-communication-workplace/ https://www.forbes.com/advisor/business/digital-communication-workplace/
    Productivity
    2024年02月01日
    • 12
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