• People Analytics
    英文学习:Workforce Analytics: what employee data can tell us now 周末英文学习 Workforce analytics—or analysing employee data to solve business problems—isn’t new, but it’s earning more attention than ever. This thanks to a stream of technology tools promising to shed light on how employee performance can improve business outcomes, coupled with mounting pressure on HR units to play a strategic role in overall business planning. Champions of workforce analytics say analysing data taken from HR systems (e.g., payroll, engagement surveys, talent suites) and business operations reveals insight that helps companies raise the quality of new hires, build high-performing sales teams, predict future staffing needs, implement more effective training solutions and drive up customer satisfaction rates, among other things. Skeptics point out that the benefit of the approach is limited by the amount and quality of the data. Both sides agree workforce analytics (also referred to as “HR analytics” or “people analytics”) has the potential to offer great strategic value even though widespread adoption still has a way to go. The 2018 Deloitte Global Human Capital Trends report, for example, which was based on a survey of 11,000 business leaders globally, showed that 85 percent of companies believe people analytics is important, but only 42 percent said they are ready to address it. Workforce Analytics in Practice The following are examples of how this technology is being applied show the upside of data-driven decision making. Crunchr, an Amsterdam-based startup, offers a tool it says measures the preferences of employees and applicants, which in turn enables companies to attract and keep the right employees. Using gamification, it asks users 16 questions about what they value most in their workplace, covering areas such as salary, benefits, career growth opportunities and job security. The surveys are anonymous, but the tool also collects data such as academic background, experience and gender. The results rank the preferences of employee groups and sub-groups. “Understanding what these preferences are helps companies design an employee value proposition where money is spent wisely,” explains Dirk Jonker, Crunchr founder and managing director. For instance, a company might offer a lower-than-average salary but include higher-than average training benefits if that is shown to matter more to a candidate. Another Crunchr tool that tracks high-potential employees also predicts flight risks, says Jonker, giving companies a chance to intervene before an employee jumps ship. OLX Group, an online classifieds operating company belonging to Naspers, is experimenting with the tool to stem flight risks among key product and technology employees. It identified two flight risk markers: reaching the 12-month employment mark and working in a unit with below-average aggregate employee satisfaction levels. When these employees get flagged in the system, the company checks in to assess their engagement level, says Brad Porteus, OLX Group CHRO. “In a perfect world, great line managers would do this instinctively, but with data and insights, we are able to be more targeted in our outreach, especially to ensure that individuals don’t fall unexpectedly through the cracks.” Workforce analytics providers say their technology also addresses the thorny issue of gender pay gap by comparing salary, employee and performance data to exposewage discrepancies. Beyond traditional HR areas, people analytics has been deployed to improve customer satisfaction and sales. McKinsey describes in a case study how its software helped a large restaurant chain pinpoint ways in which staff performance affects these levels. It collected and analysed front-line employee data in three areas: personality traits, day-to-day management practices, and behaviour and interactions on the job. One surprising insight was that financial incentives were less effective than career development opportunities in boosting employee motivation. Changes here and in other areas have driven up customer satisfaction, revenue by outlet and speed of service. The Limits of People Analytics Those cautious about workforce analytics point to its limitations. For one thing, data analysis works best with large data sets, yet companies have limited amounts of information on employees. Jonker admits that “advanced questions” companies want answers for, such as “can you predict which of these candidates will make the best salesperson?” simply cannot be answered with the data they currently have. There are also restrictions on how much data companies can collect beyond what’s gathered internally—EU’s tighter privacy laws prevent employers from looking at social media profiles without the owner’s consent. Employee data cannot be legally moved or examined across national borders in some cases. Data quality matters, too. “You can only apply statistical analysis when you have a large number of homogenous units” (like sales teams that do the exact same kinds of work), argues Alec Levenson, senior research scientist at the Center for Effective Organizations at the University of Southern California and author of “Strategic Analytics: Advancing Strategy Execution and Organizational Effectiveness.” For data to be meaningful, it must be “cleaned” so that, for instance, job titles or salaries in different currencies are consistently standardized across data sets. That’s a feat in itself. “For OLX Group, with nearly 5,000 people working in 25 unique countries, to get even basic reporting has been more challenging than meets the eye,” says Porteus. More broadly, most companies fail to do data analysis across decision-making centres—business operations, finance and HR—says Levenson, which diminishes the value of HR insights into company strategy. “Even in really big companies, the number of times it happens is astonishingly low. Decisions get compartmentalised.” Starting Simple Currently, investment in HR analytics is concentrated among large multinationals that have both the data and the skills to extract value from it. Smaller companies aren’t prioritising it, Levenson comments. But most organisations can begin extracting value with people analytics in simple but high-impact areas, says Jonker. He suggests companies look at failed starters (employees who leave within 12 months after hire). By analysing data from these employees and the managers who hired and supervised them, a company gains insight on which managers may need coaching for making hiring decisions, what triggers new hires to leave (e.g., problems with selection, onboarding or development), and the best recruitment channels. Porteus believes people analytics can raise employee satisfaction by prompting human interaction. “Data analytics can help us stay in front of the curve and ideally ensure that we are on our front foot instead of our back foot.” Browse human resources courses for executives -- Kate Rodriguez is a former senior career search researcher and government analyst who covers career development and higher education marketing for The Economist Careers Network. 原文:https://execed.economist.com/blog/industry-trends/workforce-analytics-what-employee-data-can-tell-us-now?fsrc=blog_socialshare_twitter&utm_source=t.co&utm_medium=referral
    People Analytics
    2018年09月16日
  • People Analytics
    人力资源和工作流程——生产力系统 HR & the flow of work – Systems of Productivity 文/J Jerry Moses 文章导读: 在TechHR18会议的第2天,德勤(Deloitte)的Bersin创始人乔什•伯辛(Josh Bersin)对新一代招聘、管理、学习、职业和员工体验工具是如何从根本上扰乱市场进行了分析。 他认为:技术与商业问题相一致,技术才有意义。 以下是Josh Bersin在TechHR 18会议上对人力资源技术趋势的一些见解: 技术、自动化、机器人技术都在发挥作用! 生产力是一个问题! 作社会型企业! 持续的性能管理具有巨大的影响——获取工具 大型人力资源技术供应商没有跟上步伐 人才管理需要工具来处理 我们给员工发工资方式将会被打乱 企业学习才是真正的事情! 员工福利市场具有真正的潜力 软件市场正在成长 员工体验进入工作流程 英文原文: On Day 2 of TechHR18, Josh Bersin,Founder of Bersin by Deloitte, presents a research-based analysis of how a new generation of recruiting, management, learning, career, and employee experience tools are radically disrupting the marketplace Micro trends are driving change – changes in the HR technology landscape, the way we work, and particularly, the changes in how organizations are being managed and are managing. The world of HR and HR tech is undergoing a significant shift. HR is now over Cloud, Social and Mobile – this is the time for a new breed of systems - intelligent platform strategies that are making HR and its processes real-time, productive, agile and data-driven. But “Nothing in technology makes sense unless its aligned with the business problems we are trying to solve” as Josh Bersin says. Here are a few insights on HR tech trends from Josh Bersin’s session at TechHR’18. Technology, Automation, Robotics are here and they work! According to Bersin’s research, 45 percent of companies are still focused on basic process automation. The business ecosystem is almost a decade into the economic growth, and has a plethora of generations working together in it. We are living longer, the average career spans 70-75 years, and technology is disrupting where we work along with our daily lives. Most of HCM trends, technology, robotics, AI, automation, is actually becoming real. However, we don’t know what to deal with it all because most companies are still struggling with the challenges of the right skills, structures, organizational design, and rewards systems. Productivity is an issue! Productivity is lagging. The real key for HR going forward is becoming the Chief of Productivity.  If employees use products and tools that the organizations provide to them, employes will feel better, happier, and engaged. And this is the secret of what is going to happen to HR technology – building systems for the HR that make people productive. With agility, team-centric organizations, burnout is becoming an issue while employee engagement and communication tools are overwhelming employees. This is the time for businesses to build HR software that really improves productivity and helps teams work better together? Business as a social enterprise!  CEOs are now being asked to take social positions on topics and act on behalf of communities, stakeholders, shareholders, and employees and customers. The future of business is in becoming a socially conscious enterprise and here, the most important thing would to be to develop a technology strategy that provides purpose, meaning, transparency and fairness. Businesses can no longer afford to buy technology that implements practices that someone else coded. Continuous Performance Management has a huge impact – get the tools Continuous performance management is transformative. It really and truly works! Ratings will not go anywhere but the crucial part will be to build newer and continuous processes for goal setting, coaching, evaluation, and feedback.  This is time for organizations to reconsider performance philosophy. Even with the success of the cloud HCM vendors in the market, a comprehensive solution for performance management is not available. “Team-centric” tools will be the future of HCM market in the future. Big HR Tech vendors are not keeping up Most of the ERP vendors are struggling to keep up with the evolution and changes in the business ecosystem. ERP vendors are not getting good marks for ease of use, integration, or value to the end users or employees. There is a stiff competition in the ERP market and it is becoming crowded. Talent management is done! The whole idea of Talent Management was about pre-hire to retire. But we don’t work like that anymore. Most of us work at many companies during our careers and organizations are also going through change, disruption and reorganization. Managing employees through the entire lifecycle is not really the problem but managing employees in a new management environment that is about teams, empowerment, mission, purpose, clarity and transparency of goals. It’s a totally different management environment and we need tools to deal with that. How we pay people will be disrupted The most disrupted area of HR to come is the way we pay people. Only 1 in 5 companies believes that their rewards system is actually aligned with their corporate strategy. We are still paying people the way we did in the past — salary bands, annul reviews, policies of secrecy and who is getting paid what – all this will be disrupted and we will have a whole new set of tools for employee experience. Corporate Learning is the real deal! Platforms like Degreed and Edcast are transforming corporate learning — experience platforms, micro-learning platforms, modernized LMS systems, AI-based systems to recommend learning, find learning, and deliver learning, and Virtual Reality-based learning are giving employees and organizations all the things they need. Employee wellbeing market has the true potential It’s all about the moments that matter. There is a need to improve productivity but there is a significant impetus on employee wellbeing, reducing the cognitive overload and augmenting human performance.  This vendor market is moving fast. The new world of work will be about “engagement, productivity, and wellbeing” all in one. ONA software market is now growing With the explosion of HRMS data, wellbeing data, networking data, among many other forms of structured and unstructured data, HR is struggling to deal issues of ethics, privacy, and becoming more transparent about the analytics they are doing. The Organizational Network Analytics is growing and so is a new world of “relationship analytics”. People Analytics will guarantee success. Getting into the Flow of Work Employee experience is the buzzword and we are trying to reform it in a way that applies and improves the work experience of every individual in an organization. Organizations define employee experience as a project of looking at the moments that matter, transitions, periods of time in career where one is stressed and what can HR do to make that easier. But none of the tools are designed to measure or map something like this. All tools are designed for the HR function, not this. There is a new category of software being built to help HR with the employee experience - to shield employees from the complexities of the backend HR systems and deliver all the different things the HR does in the flow of work.
    People Analytics
    2018年08月07日
  • People Analytics
    8月3日,2018人力资本分析高峰论坛-People Analytics Forum在沪成功举办! 2018年8月3日,由HRTechChina主办的“人力资本分析高峰论坛-People Analytics Forum”在上海成功举办。 会议当日,虽逢台风天气,嘉宾参会热情不减,均准时到达会场,大会得以成功举办。近70位招聘科技领域的科学家、HR资深高管、行业大咖参加会议,其中包括许多知名企业高管:阿里巴巴、英格索兰、罗氏、腾讯、米其林、ARM、霍尼韦尔、好时、凯德管理、中宏保险、延锋、jotun等。 本次峰会主题为:“用数据驱动人力资源”,主办方邀请了3位业内知名人士进行了精彩的主题分享。演讲嘉宾包括科石首席顾问人力资源数据分析专家杨冰,世界500强公司亚太区人力资源总监范珂,前美世咨询组织分析专家 六点一刻创始人许菊艳,共同探讨中国最前沿招聘科学技术,深度挖掘如何将大数据更好应用于招聘领域,促进招聘工作的科学化,精准化,更好把握招聘领域科技未来的趋势和方向。 首位分享嘉宾是世界500强公司亚太区人力资源总监范珂,就“如何通过人力资源数据讲故事”的主题发表了自己的观点。 接着前美世咨询组织分析专家 六点一刻创始人许菊艳分享的主题是:以始为终,有效利用人力资源数据推动业务价值实现数据重塑影响力,她从三个维度分别向大家介绍了数据是如何推动业务价值的实现-由外而内的价值创造思维;数据驱动的效能计量系统;先于业务的战略支持维度。深入浅出的剖析了大数据在人力资源领域的应用,大量案例分析的佐证,使演讲通俗易懂,赢得嘉宾阵阵掌声。 最后分享的嘉宾是科石首席顾问人力资源数据分析专家杨冰,在他的分享里,着重强调了组织人效管理。从三大板块对组织人效管理进行全面解读:组织人效管理的任督二脉-构建人效管理仪盘表的核心逻辑;如何通过数据分析诊断组织健康问题;组织效能优化路径和案例探讨。 本次峰会就招聘行业的最新领域——人力资本分析做的深度探讨,对人力资本发展方向有着深刻的意义。随着招聘科技的发展,人力资本分析将越来越多的应用于招聘领域,前景不可小觑。
    People Analytics
    2018年08月06日
  • People Analytics
    如何为人力分析专业人士创造职业道路-How to create career paths for people analytics professionals(续) 文/David Green 文章导读 往期回顾: Geetanjali在2017年9月在费城举行的人力分析与未来工作会议上发言要点回顾: MERCK&CO.的人力分析团队 这个团队由三支柱组成:咨询、高级分析、报告和数据可视化 创建一个数据驱动的文化:高层领导的支持对于人员分析功能的成功至关重要 在人力分析中创造职业道路:一个能够提供发展和职业发展的组织和领导者,可以成为吸引和留住人才的关键因素。 三“C”模式:Capability-Capacity-Connectivity 今日导读: 领导人员分析团队 问7、在谈到你作为一个人分析领导者的角色时,你会对这个角色的新手或者将来想成为一个人分析负责人的人提出什么建议呢? 分享五个我认为普遍适用的特性,并且对于成为这个领域的有效领导者很重要。 优先考虑:对于人员分析领导者来说,学习如何无情地优先考虑团队将花费时间和精力的项目是至关重要的。 位置: 一个好的领导者知道如何找到合适的机会去重新定位、结合和展示这项工作。这不仅对获得声望和对人员分析的认可很重要,而且对提升团队的士气也很重要。 连接: 当你建立起新的职业联系时,你也开始建立友谊,这是一个支持网络,可以帮助你在这个相当模糊的、新的人力分析空间中导航。 与时俱进:作为一个优秀的人员分析领导者,重要的一点是要跟上外部变化的步伐,并将这种学习带回您的业务中 发展:一个有效的领导者需要投入时间和精力来建立自己的内部和外部网络,并与他们的团队分享他们的进 问8、我观察到的一个挑战是,作为一个人分析的领导者,你必须平衡在内部构建能力的重大挑战,同时关注在外部快速发展的领域。作为一名分析人士的领导者,你如何平衡这两个优先事项,以及你如何了解公司外部发生的事情? 尽可能多地阅读各种不同的出版物(博客、文章、白皮书、书籍),这些内容让我与人力分析的各个方面:从社会科学到人工智能都保持联系。 此外,与来自不同行业的其他从业者建立联系很有帮助,我通过非正式的和正式的对等网络进行联系。 最后,我试着每年参加一些活动来学习新的东西和认识新的人。   人力分析的未来 问9、你认为人力分析的主要趋势是什么? 我认为人力分析中的一些“热点领域”将在未来继续变得“更热”。 我还认为,随着研究的增长和越来越多的组织对这一领域的投资,网络的力量将得到充分的挖掘和释放。 最后,要实现所有这些类型的分析,最重要的领域之一将是关于数据使用、隐私和人员分析领域的安全性的伦理研究。   问10、我们如何平衡我们能做什么以及我们应该做什么? 谈谈你对道德和隐私等方面的关注。 过度反应或倾向于采用过于保守的方法,这可能会妨碍人员分析领域的一些重要工作。 话虽如此,与适当的实践专家密切合作,就业法律、隐私法律、伦理、通信、业务合作,和工人委员会合作是一个很好的方式,以确保除了工作的合法性。 另一种从道德角度是预先与内部客户分享你分析的可能结果,并向他们清楚地说明在每个场景中他们将采取什么行动。 在人力分析领域工作类型需要把伦理放在最重要的日程上 英文原文: LEADING THE PEOPLE ANALYTICS TEAM 7. Turning towards your role as a People Analytics Leader, what would your advice be to someone who is new to this role or who aspires to be a Head of People Analytics in the future? I think everyone has different strengths and experiences, which means their approach will vary with regards to them proving successful as a people analytics leader. But based on my personal experiences and observations of others, I can share five attributes that I think apply universally and are important to being an effective leader in this space. Prioritise: Whether you have a small or large people analytics team, it will never be big enough to meet all the demands of your clients, particularly as awareness of the team’s capabilities grow. So, it is critical for the people analytics leader to learn (and teach!) how to relentlessly prioritise the projects on which the team will spend its time and effort. A good rule of thumb is to think about the magnitude of business impact that an analysis has the potential to deliver, or a key relationship that it can help build in the business for future collaborations and sponsorship. Many teams even use formal prioritisation grids to help the process, but ultimately the leader needs to ensure that the criteria used to allocate resources to projects aligns with the vision and mission of the people analytics team (which in turn, should align with the objectives of the enterprise). It is critical for the people analytics leader to learn (and teach!) how to relentlessly prioritise the projects on which the team will spend its time and effort. Position: A critical skill for a people analytics leader is the ability to effectively position analyses before the right decision-makers at the right time to maximise positive outcomes and build a strong people analytics brand. This is probably one of, if not the most, important part of being a people analytics leader. On many occasions, brilliant workforce analyses have been underutilised in their original scope, but a good leader knows how to find the right opportunities to repurpose, combine and present this work. This is not only important in gaining prestige and recognition for people analytics, but also for boosting the morale of the team. Connect:  There is a small, but growing, community of people analytics leaders globally who collectively have a spectacular amount of experience and knowledge. Fortunately, this community is inclusive and generous, in terms of sharing their knowledge and connections with others in the field. The group is a great resource to learn about new technologies, techniques, vendors, and also receive tips and tricks that can help a new leader to avoid mistakes and grab the right opportunities. Most importantly, as you build new professional connections you also begin building friendships that are a support network to help you navigate this fairly ambiguous, new(ish) space of people analytics. Evolve: Since a people analytics leader needs to have some depth in analytical methods, it is always a good idea to read, listen and learn. Thanks to social media there are amazing resources available, many of them free, that any analytics leader can and should leverage to keep oneself updated and evolving. There are some extremely prolific writers (like David Green!) who share both original and curated content on various forums including LinkedIn. Whether you are looking for detailed tutorials on advanced data science methods or want to learn about the latest technological breakthrough and its application to people data, there is a publication, podcast, or video out there on it. Another reason why this mind set of curiosity and awareness is important is because the people analytics space is sensitive primarily due to ethics and privacy reasons; and keeping a handle on that also demands a leader who keeps their eyes and ears open. An important part of being a strong people analytics leader is to keep up with the pace of change externally and bring that learning back to your business. An important part of being a strong people analytics leader is to keep up with the pace of change externally and bring that learning back to your business Develop:  Last, but certainly not the least, a critical part of being a good people analytics leader is simply being a good leader. This implies being someone who invests in the development of their team. It is of particular importance because it is a space that has attracted a lot of exceptional talent, but still has somewhat limited opportunities for advancement. Therefore, an effective leader needs to invest time and effort in building their own internal and external network; and share it with their teams for their advancement. They should also be committed to actively finding or creating opportunities for their team members to learn new skills and develop themselves as multi-faceted professionals. An effective leader needs to invest time and effort in building their own internal and external network; and share it with their teams for their advancement 8. One of the challenges I’ve observed in being a people analytics leader is that you have to balance the significant challenge of building capability internally whilst keeping an eye externally on what is a fast-developing field. As a people analytics leader, how do you juggle these two priorities, and how do you keep abreast of what is happening outside the organisation?  I strive to practice the same behaviours that I would advise new people analytics leaders to try. For example, I follow and subscribe to content by certain thought leaders in people analytics and read as many varied publications as possible (blogs, articles, whitepapers, books) which keep me connected to the different aspects of people analytics; from social science to artificial intelligence. In addition, it really helps to connect with other practitioners in the field from different industries, which I do via both informal and formal peer networks. This helps to broaden one’s worldview, spark new ideas, and offers a forum to ask questions of your peers. Most likely, if you are facing a people analytics quandary, there is a leader out there who has faced it too and would be willing to share their experience. Finally, there are a plethora of great conference events out there, and the quality and number of these keeps rising every year. I try to participate in at least a few such events every year to learn new things and meet new people. THE FUTURE OF PEOPLE ANALYTICS 9. What do you believe will be the main trends moving forward in people analytics?  I think that a number of “hot areas” in people analytics will continue to get “hotter” in the future. The idea of employee experience will grow even wider with focus on the end-to-end experience all the way from being a prospective candidate stage to becoming an alumni of the company. This is likely to grow simultaneously with the focus on managing and optimising a new, fluid workforce that may at any one time be full-time and freelance, human and robotic. I also think that the power of networks will be fully explored and unleashed as research grows and more organisations invest in this space. The applications of network analysis are so varied and relevant, that it should continue to gather steam in the future. Finally, from my perspective to enable all these types of analyses, one of the most critical areas that will grow in importance will be the study of ethics relating to data use, privacy and security in the space of people analytics. 10. Finally, how do we balance what we can do with what we should do? How concerned are you about areas such as ethics and privacy? This is a great question, and a difficult one to answer. The frontiers of what is possible are being pushed at a break-neck speed thanks to ever larger datasets being at our disposal faster, and at cheaper cost. And that pace makes it tough to process the implications in real time. In fact, this often leads to an overreaction or the inclination to adopt an overly conservative approach that can hamper some great work in the people analytics space. That being said, I believe that an extremely important fact to understand about the space we work in is that we should not do something just because it is possible. Besides being legally compliant, the type of work being undertaken in this field needs to put ethics at the very top of the agenda even before beginning work on an analysis. Working closely with the appropriate experts in the practices of employment law, privacy law, ethics, communications, business partners and workers councils is a good way to ensure that besides the legality of the work, its potential impact on people is also being considered through the lens of ethics, privacy, and empathy.  Most established organisations have extensive reviews involving these types of stakeholders already in place. Another way to pressure test the approach from an ethics lens is to share possible outcomes of an analysis with the internal clients beforehand and ask them to articulate what actions they would take in each scenario. Obviously, this method is not possible in every situation, but when applicable it can be a useful “stop and reflect” moment. The type of work being undertaken in the people analytics field needs to put ethics at the very top of the agenda
    People Analytics
    2018年07月31日
  • People Analytics
    如何为人力分析专业人士创造职业道路-How to create career paths for people analytics professionals 文/David Green 文章导读 根据德勤于2017年11月发布的“高影响力人力分析研究”(High-Impact People Analytics study), 69%的大型机构(10,000多名员工)现在拥有一个“人力分析团队”。 Geetanjali Gamel在旧金山举行的“人民分析与未来工作会议”(People Analytics & Future of Work Conference)上的演讲这个话题。Geetanjali是默克公司劳动力分析的全球领导者。在2017年9月在费城举行的人民分析与未来工作会议上发言。 为什么要人力分析? 问1、你好,Geetanjali,请解释一下吸引你到人力分析领域的原因。 我工作中最有趣的部分是理解、测量和预测人类行为及其对销售和收入等业务结果的影响。因此,我很自然地被这个机会所吸引,这个机会将科学的方法引入到人们的数据中,并帮助塑造一个组织如何为其投资者带来价值,同时为其员工带来更丰富的经验。 MERCK & CO.的人力分析团队 问2、请您描述一下默克公司的劳动力分析团队的规模和结构,以及它是如何与业务联系起来的。 默克的劳动力分析团队(WFA)拥有15名成员,在全球80多个市场,69000名员工。 这个团队由三个主要支柱组成:咨询、高级分析、报告和数据可视化。 咨询——每个咨询师都与我们的业务部门(如制造、研究、销售等)保持一致。他们与领导者紧密合作,以理解和预见棘手的业务问题,并运用正确的方法解决问题,将分析转化为可操作的观点。 高级分析——高级分析团队是一群灵活的数据科学家和专业人士,他们主要专注于需要高级技术技能或很有意义的项目。它们围绕业务问题进行组织。 报告和数据可视化——他们直接与来自业务各个部门的内部客户合作,以确保合适的人在合适的时间拥有合适的数据。驱动了内部客户满意度。 三个WFA团队紧密合作,以确保识别和利用业务活动之间的协同作用。 创建一个数据驱动的文化 问3、德勤(Deloitte)的“高影响力人物分析”(High-Impact People Analytics)研究发现,在创造高级能力方面,最重要的因素是需要创建数据驱动的文化。你在默克公司是如何做到这一点的? 我们首先在人力资源社区中推广数据,推出了一个基于云的劳动力分析平台。我们还开发和部署了一个能力构建程序,其中的模块主要集中在度量选择、假设测试、数据可视化、推荐开发等方面。 此外,我们一直在利用的另一个渠道,加速人力资源数据驱动文化,是让我们更广泛的人力资源社区的成员成为分析“冠军”。 最后,我们还建立了一个人力资源领导团队,在人力资源中传达建筑数据和分析能力的信息。 高层领导的支持对于人员分析功能的成功至关重要 在人力分析中创造职业道路 问4、您对为人力分析专业人员创建职业发展道路充满热情。 为什么你认为这是如此重要? 我热衷于为那些使人力分析成为可能的人们建立更好的工作体验! 我发现这个团队能够为职业道路,继任计划和大型员工的人才流动等领域做出决策,但经常陷入无处可扩展的境地。 此外,大多数人分析团队都是人力资源部门的一员,而且往往被贴上高度专业化的“人力资源精英”卓越中心(CoE)的标签,这限制了横向或向上进入CoEs或业务部门的其他人力资源角色的机会。 最后,一个能够提供发展和职业发展的组织和领导者,可以成为吸引和留住优秀人才的关键因素。 如果我们能让更多人力分析人才流动起来,就会为人力资源和企业的其他部门增加技能、方法和拓宽视角,为企业创造额外的价值。  一个能够提供发展和职业发展的组织和领导者,可以成为吸引和留住优秀人才的关键因素 问5、关于人才分析团队的职业发展,你在默克制定了什么计划?关于人才分析团队的职业发展,你在默克制定了什么计划? 从我在默克公司工作的第一天起,我的首要任务之一就是了解我的团队的力量和抱负,并将他们的发展与他们的职业目标结合起来。我得出了一个Capability-Capacity-Connectivity模型,为我们的人员分析团队提供一个可持续发展项目。这种模式成功的一个关键驱动力是你的领导的支持和与其他团队的合作。 问6、职业发展计划的主要好处和收获是什么? “3C”方法是围绕解决障碍和为人学分析团队创建促进职业发展的桥梁而构建的。 第一个“C”:能力,能力必须在两个级别上处理。 能力级别1:构建数据、技术和分析精明的客户 能力级别2:提升人员分析团队 第二个“C”:Capacity容纳度 如果没有时间远离日常的活动,就不可能专注于一个人职业生涯的下一步 第三个“C”:连接 将人员分析团队与其他人力资源,数据科学,技术和业务专业人员联系起来,建立对双方不同类型工作的认识和相互欣赏。 英文原文: According to Bersin by Deloitte’s High-Impact People Analytics study, which was published in November 2017, 69% of large organisations (10,000+ employees) now have a people analytics team. It is a surprise then that many organisations overlook the need to develop the careers of their people analytics team. Given the pace of evolution of the field and the high-demand for talent in the space, this is an oversight that needs correction. As such, it was refreshing that the main focus of Geetanjali Gamel’s presentation earlier this year at the People Analytics & Future of Work Conference in San Francisco (see key learnings here) was on this very topic. Geetanjali is the global leader of workforce analytics at Merck & Co., Inc. (NYSE: MRK, known as MSD outside the United States and Canada). I caught up with Geetanjali recently to ask how she has created career development paths for her team as well as discuss other related topics in the people analytics field. Geetanjali Gamel speaking at the People Analytics & Future of Work Conference in Philadelphia in September 2017 WHY PEOPLE ANALYTICS? 1. Hi Geetanjali, please can you introduce yourself, describe your background and explain what attracted you to the people analytics space. Like many of my colleagues in people analytics, I’ve had a non-linear path to my current role. I am a trained economist and began my career in research at the Federal Reserve Bank of St. Louis studying topics like macroeconomic forecasting, unemployment and inflation.  With this foundation in social science methodology and research, I soon transitioned to business forecasting, predictive analysis and scenario-planning to drive customer growth and revenue projections in corporate planning and finance departments in the energy sector. The most intriguing part of my work was in understanding, measuring and predicting human behaviour and its impact on business outcomes such as sales and revenue. So, I was naturally attracted by the opportunity to bring scientific methodology to people data and help shape how an organisation can drive value for its investors along with enhanced experience for its employees. I began by building a predictive analytics function from scratch in HR in my previous role at Mastercard and since 2016 I have led the advanced workforce analytics, consulting and reporting organisation in Merck HR. THE PEOPLE ANALYTICS TEAM AT MERCK & CO. 2. Please can you describe the size and structure of the workforce analytics team at Merck and how it aligns to the business Merck’s workforce analytics team (WFA) has 15 members who support 69,000 employees in over 80 markets worldwide through a rich portfolio of people analytics products. The team consists of three primary pillars; Consulting, Advanced Analytics, and Reporting & Data Visualisation (see Figure 1 below). Figure 1: The Workforce Analytics team at Merck & Co (Source: Geetanjali Gamel) Consulting - Each consultant is aligned to one of our business divisions like manufacturing, research, sales, etc. They work closely with leaders to understand and anticipate burning business questions, utilise the right methodology to find the answers; and convert the analyses into actionable insights. Advanced Analytics - The advanced analytics team is a nimble group of data scientists and specialised professionals who focus mainly on ad hoc projects requiring advanced technical skills and/or initiatives of enterprise level significance. They are organised around business questions and may support several divisions at a time, in contrast to the end-to-end approach that the consultants take with each initiative. Reporting & Data Visualisation – This team forms the backbone of all the amazing work we are able to do, as well as the internal customer satisfaction we drive. They work directly with internal clients from all parts of the business to ensure that the right people have the right data at the right time. The three WFA teams work closely with each other to ensure that any synergies between business initiatives are identified and leveraged. CREATING A DATA-DRIVEN CULTURE 3. The recent Bersin by Deloitte High-Impact People Analytics study found that the single biggest predictor in creating advanced capability is the need to create a data-driven culture. How have you achieved this at Merck particularly with regards to HR Business Partners and the wider HR function? I agree that culture can be the strongest catalyst or impediment for people analytics. It is also ridiculously difficult to identify and alter, particularly because organisations at any given time tend to be collections of sub-cultures. But there are some patterns of behaviours, decision-making, and incentive-rewards, which distinguish data driven cultures from others. These behaviours can be purposefully incubated through a combination of upskilling, training and mind-set building. At Merck, we believe that a leading HR function is one where analytics capability is not only for the analytics team, but the whole HR team. This does not imply that every role requires equal depth in analytics, but a new baseline of data interpretation and communication skills is critical to being effective partners to the business. To this end, we started out by democratising data within our HR community by rolling out a cloud based workforce analytics platform. This is helping us drive greater familiarity and reliance on data among our HR users. We have also developed and deployed a capability-building program with modules focused on metric selection, hypothesis testing, data visualisation, recommendation development, and more. Another channel that we have been leveraging to accelerate a data driven culture in HR has been to engage members of our wider HR community as analytics “Champions”. These superheroes are critical to spreading the adoption of data informed insights, since they live and breathe the daily challenges of their colleagues; and can share relatable examples with their counterparts on how data can unlock value. Finally, we also have an HR leadership team that is aligned and strong advocates in relaying the message of building data and analytics capability in HR. Needless to say, sponsorship of senior leaders is imperative to the success of a people analytics function. Sponsorship of senior leaders is imperative to the success of a people analytics function CREATING CAREER PATHS IN PEOPLE ANALYTICS 4. You are passionate on the need to create career paths for people analytics professionals. Why do you believe this is so important? I firmly believe that the goal of people analytics is to drive value for the business as well as provide a better experience of work for employees. So naturally, I am equally passionate about building a better work experience for the people who make people analytics possible! I find a sad irony in the fact that the team which enables decision-making on areas like career pathing, succession planning, and talent movement for the larger workforce, is often stuck in a position of having nowhere to grow. From my discussions with many colleagues in this field, I have learned that the typical people analytics team usually tends to have a group of individual contributors (analysts, data scientists, consultants) and a director or senior director level leader. This leaves only one spot for the entire team to aspire to, at least for upward movement. In addition, most people analytics teams sit within HR and tend to be branded as a highly-specialised “HR-lite” centre of excellence (CoE), which limits the opportunities to move laterally or upward into other HR roles in CoEs or business units. And this reality of being “boxed-in” can be very frustrating for bright, highly-employable individuals. If you are a leader in people analytics, and if you have had to recently recruit new talent for your team, I would guess you are acutely aware of the gaping chasm between talent demand and supply in this field. In my opinion, an organisation and a leader who can offer development and career growth can be a key differentiator in attracting and retaining the best people analytics talent. Broadening that vision, if we enabled more fluid movement of people analytics talent, it would add to the diversity of skills, approaches and perspectives to other parts of HR and the business, and would create additional value for the enterprise. An organisation and a leader who can offer development and career growth can be a key differentiator in attracting and retaining the best people analytics talent 5. What program have you put into place at Merck regarding the career development of the people analytics team? From the first day of my role at Merck, one of my top priorities was to understand the strengths and aspirations of my team and align their development to meet their career goals. After multiple discussions and numerous iterations on ideas, I arrived at a Capability-Capacity-Connectivity model to power a sustainable development program for our people analytics team. The underlying idea is that if we can build the right capability within the analytics team and its clients; reallocate capacity that is being consumed by suboptimal tasks; and drive connectivity between people analytics teams and other parts of the business; then we can potentially discover and create new career paths and opportunities. But please bear in mind that a key driver of success for such a model is sponsorship from your leaders and partnership with other teams. In our case, we were fortunate to have both. This has empowered us to be inventive and co-create development opportunities for our team.   6. Please can you provide more detail on what comprises each of the Capability, Capacity and Connectivity elements of this approach. What have been the key benefits and learnings from the career development program?  The “3C” approach is built around tackling barriers and creating bridges that promote career development for people analytics teams. At the outset we knew that the team was faced with a high volume of requests needing significant manual effort. (see Figure 2 below): Figure 2: Challenges in accelerating maturity in people analytics (Source: Geetanjali Gamel) Since the day-to-day work was time and effort intensive, there was not much room to hone more sophisticated skills or build knowledge sharing relationships with others, leaving the people analytics team stuck in a loop. So, we put careful thought and purpose into adopting the following model. Capability The first “C”, or capability, had to be addressed at two levels. The first was to empower our broader HR team with the right tools and training to have greater autonomy to perform analyses. We moved to an intuitive analytics platform and organised workshops, office hours, and learning sessions to improve data literacy among our internal HR clients. This type of effort is important to free-up time for the people analytics team to build their own skillset (and path to growth), while also creating a greater awareness in other parts of HR about analytics. Figure 3: Capability - Level 1: building data, technology and analytics savvy clients (Source: Geetanjali Gamel) The second area of capability building had a more direct impact on the team. We held a team strategy session where we identified areas that needed focus for internal functional, technical and strategic competency building. These focus areas were carefully selected to create dual impact – provide us with a skill or knowledge we could use immediately in our work; and more importantly, help us practice a new behaviour that would develop us as well-rounded professionals. For example, on the technical side, we organised an in-house R-training curriculum, created and delivered by some of our own colleagues to the rest of the team. This helped us build a technical skill we could immediately put to use to do better work, and also built coaching and confidence skills for those who led the program. Another great example was of an external guest speaker series that we launched, which brought recognition to the team for bringing new insights to the company, and also helped the team gain experience in organising an event successfully end-to-end. Figure 4: Capability - Level 2: Upskilling the people analytics team (Source: Geetanjali Gamel) Capacity At first, capacity building measures may not sound like a natural fit with developing career paths. But it is impossible to focus on the next steps in one’s career if there is no time to step away from the daily barrage of activity to have a conversation; listen to a webinar; learn about a new project; or simply, chat with colleagues over lunch. As such creating capacity for the team is critical to allow them to develop their skillset to be more widely applicable, as well as to build the networks they need to find new opportunities. As mentioned before, our journey began with democratising data and providing a range of workforce metrics and even results of our enterprise voice survey in accessible cloud platforms to our HR community. We continue to supplement our efforts to empower our internal clients, and in the process unlock capacity for our team, by forming global communities of practice for analytics. Another effort to scale our analytics delivery and save precious time has been by finding opportunities to utilise process automation on repeatable tasks. It is impossible to focus on the next steps in one’s career if there is no time to step away from the daily barrage of activity Connectivity Despite efforts in building capability and reallocating capacity, there can’t be much career development if there is nowhere to go! This is when the third “C” of connectivity comes into play. In fact, it could just as easily be C for creativity, because we need a great deal of innovative thinking and risk taking to create opportunities where they don’t always exist. We started with small yet effective steps rather than trying to construct huge, formal programs. Connecting the people analytics team with other HR, data science, technology, and business professionals builds an awareness and appreciation for different types of work on both sides. We leveraged opportunities to co-create part-time assignments with other teams, participate in cross functional events, invite guest speakers to team meetings, and collaborate on projects to expose the team to other areas of analytical work. Connecting the people analytics team with other HR, data science, technology, and business professionals builds an awareness and appreciation for different types of work on both sides To create development assignments for the people analytics team we were creative and went with “quasi-experiments”. The first was an opportunity for a team member to take on the role of an HR business partner on a part-time basis for a few, smaller client groups. This gave the individual an opportunity to apply their analytical skillset to the role and get much greater exposure than before to business clients and business issues. Such an experiment has a multiplier effect. Where typically a business partner track is not easily available to a people analytics professional, creating such an opportunity internally can open up a new career path. Moreover, even if the individual does not end up pursuing this new career direction at the end of the experiment, it is still a valuable learning experience for them to be in the shoes of their internal client, i.e., the HR business partner. Finally, it may help to lay the foundation for what I like to call the HRBP 3.0 model. Where the original HRBP role had a heavy component of operational (and even transactional) work, the HRBP 2.0 model that many companies follow today aims at strategic business partners who enable key business decisions. The HRBP 3.0 model takes it a step further by envisioning an analytical HR business partner, who relies on both data driven insight and business acumen to support their client. Another “experiment” in creating new career opportunities was a mini-assignment we created for one of our people analytics team members to lead a large, remote team in the service delivery space. This was a completely different line of work from people analytics, and was heavily focused on operational and organisational skills like identifying and escalating issues on short deadlines, supplier relationship management, building relationships with a variety of HR and non HR stakeholders, and leading a service centre team to drive customer satisfaction. Clearly, this would not be a typical career path for a people analytics professional, but that is exactly why we need to be bold and creative with such experiments. This assignment not only exposed the individual to a different type and pace of work, but also gave them an opportunity to bring their analytical skills to the table to significantly elevate the usage and interpretation of transactional data. While many mature organisations have good-sized people analytics teams, there are still many where the teams are pretty lean. This model may work well for most purposes, but it usually limits the opportunities for team-members to have people management experience. This is not always necessary for upward mobility, but it many cases it is difficult to move upward without some kind of experience of leading a team. Keeping this in mind, we built more depth in our people analytics team, creating enterprise advanced people analytics and data visualisation and reporting sub-teams within the larger group, which are led by two of our team members. Taking a chance on subject matter experts and giving them the opportunity to lead and delegate not only helps to open up doors for them, it also gives them a chance to coach others on their team to be future experts and leaders. Lastly, we also created a new learning analytics role on our people analytics team which is a step toward building greater synergies between people analytics and learning practices, but also our small contribution in creating a new capability (and career path!) that is still evolving in many organisations.
    People Analytics
    2018年07月30日
  • People Analytics
    备受瞩目!2018招聘科技高峰论坛成功举办!超1400位招聘科技达人莅临现场!会场爆棚!(多图) 2018年7月27日,中国备受瞩目并引领人力资源招聘科技前沿的峰会-2018招聘科技高峰论坛于上海四季酒店隆重举行。本次峰会以“Hire Better With Tech”为主题,聚焦当下最新的招聘科技发展趋势以及潮流,解密科技如何助力企业招聘。会议当日有近20位招聘科技领域的科学家、HR资深高管、行业大咖、杰出的招聘领袖进行了精彩绝伦的分享,同时深度探讨了20多个招聘科技的主题如:全球招聘科技趋势、人工智能、大数据、GDPR、区块链、人力资本数据分析等;并有超过1400 位来自企业的招聘负责人以及企业高管到场学习。 本次峰会由HRTech China主办,得到了领英,e成科技,CIIC, 中国平安,科锐国际,谷露,携程商旅,赛码网,猎聘,仁云,有招,优面宝,合晟正信,互动吧,计蒜学院以及人力资源杂志、薪酬网、HR沙龙、招聘兄弟会、HR圈内招聘网、培训杂志、世链财经、NACSHR等伙伴的大力支持,再次表示诚挚的感谢! 2018招聘科技峰会吸引了超过1400+的招聘科技达人莅临现场,更是吸引了众多知名企业的CHRO以及企业中的招聘科技负责人,参会嘉宾来自上海、北京、浙江、广州、苏州、湖南、江苏等20多个长三角、京津冀、珠三角及部分内陆地区的城市,同时还有部分来自港澳台以及北美地区的招聘科技同仁! 2018招聘科技峰会由计蒜学院首席运营官杨斌先生作为特邀主持嘉宾,为大家拉开会议序幕!杨斌先生作为招聘领域的资深专家,曾任百度、优酷土豆人力资源高级总监,在开场中谈到一路在互联网企业尤其能够感受到科技对于招聘的助力! 接下来首位分享嘉宾是来自HRTechChina 的顾问Gawain,他就“全球招聘科技发展趋势及我的观点”发表了主题演讲,在演讲中谈到最新科技在招聘中的应用,但是中国市场与全球其他地区市场的巨大差异,比如在美国人工智能作为招聘除了核心解决效率之外,另外一个最重要的作用就是帮助招聘人员解决“就业平等、多样化、职场偏见”的问题,同时Gawain指出“中国的模式中一个重要的领域就是围绕微信为生态,很多招聘的公司就是基于微信的生态圈构建了很多的玩法,这是中美非常大的一个不同点”。同时建议招聘官应该更多关注宏观经济角度的一些数据比如失业率、生育率、老龄化等关键问题。 接下来,领英中国征才解决方案顾问段祎辰先生则就“拥抱智能,演绎故事-领英大数据深度解读2018人才趋势”发表了自己的观点,段祎辰先生谈到:大数据是领英非常擅长的一个领域,我们在全球现在已经有6亿的用户,是全球最大的一个职场社交平台。而且他对大数据的未来十分看好,90%的招聘人员认为至少在将来会用到大数据。主题演讲历时20分钟。段祎辰先生的谈话中多次提及领英的相关报告数据,强调更重要的是各位怎么利用企业故事去吸引你想要招的人,这才是我们最终的目标。 接下来的重量级嘉宾是来自e成科技的首席科学家-陈鸿博士。他主要分享了e成科技在面试机器人场景的探索,并表示:面试机器人在测试的结果里面,现在已经完成了超过5千次的测试,数据上还是可以满意的,我们的一面通过率超过了一半,主要是后续一面是基面评价的相似度,通过基面以后会给他打一个分数,这个分数和后面一面的人类考官给这个人打的分数相似度是85%。杨斌先生在评价陈鸿博士时,说道:“整个的招聘科技方面应该说它的发展日新月异,也给在座各位从事招聘工作的各位同仁带来了很多的机遇以及挑战。” 陈鸿博士的技术角度的分享引发了在场参会嘉宾的热烈讨论。 接下来分享的是原顺丰、大众点评HRVP-Tony。他根据自身经验,分享了CEO的人才观。他的演讲将企业分为蓝海,红海,黑海三种类型来谈。以小米为例,Tony谈到:“小米今天不一定是在蓝海,有些领域在蓝海,有些领域早就已经在红海了,也许也可以尝试黑海。每个企业在不同的成长阶段都会跳入不同的游泳池去玩一玩。”Tony的演讲精彩绝伦,观点独到,引发了观众席的阵阵掌声。在本次会议的参会交流微信群中,参会嘉宾纷纷表示听了Tony 的分享之后深受启发,并感叹未能几年前听到,以减少职业发展的弯路! 在四位嘉宾精彩的主题演讲之后,迎来了本次峰会的一个重头戏:候选人体验大奖评选颁奖环节。候选人体验大奖的颁奖由两位评审为代表,一位是kevin,一位是丁鹏。评选旨在甄选出在候选人体验上做出卓越实践,通过提升候选人入职企业前的体验以提高入职率,从来帮助企业吸引更多的人才。评委会同时建议企业的HR们可以就候选人体验方面做更多的沟通、交流和分享,以便更好的造福人才,成就企业,贡献社会。 评委会认真审查企业各项指标,多番讨论与研究,最终确立本次候选人体验大奖的获奖企业为: 获得候选人体验大奖企业金奖的企业有: 平安集团,天安骏业,康得新集团,凤凰网,票易通,施耐德电气,上海辰渝机电成套设备有限公司、京东集团。 获得候选人体验大奖产品金奖的企业有:优面宝,赛码网,e成科技,HR-X。 祝贺获奖的企业! 颁奖结束以后进入到以“科技助力招聘”为主题的圆桌论坛,来自网红HR STORYWAY联合创始人-Maggie Shao分享了她在《脑力男人时代》电视栏目里面试蔡康永、大S、薛之谦、冯德伦等的面试经历,之后打开了HR混迹娱乐圈之门,之后又参与湖南卫视的节目等经历. 本次对话,Maggie邀请了PWC大中华及香港地区的HR Director的Steven Sheng,原顺丰、大众点评HRVP的Tony,北京凤凰网的招聘总监王志红以及蓝白律师事务所合伙人陆胤先生开始了圆桌论坛。 Steven Sheng表示:“庞大的人才进和出,现在最重要的是数据”,同时他还表示:“我们在全球启动人力资源的科技服务平台。可以这么说-我们从18、19、20年的规划里面,所有人员的落地项目都离不开人力资源科技。”结束时,他总结自己的发提到,“其实我们这个行业也是有危机的,但同时也是机遇。我们在提升员工体验的同时,也不能忘记个人隐私及信息保护。对于创业者来讲,应该更快更好的利用目前这个科技跨越式提升,人们不断重视科技的大环境。” Tony则谈到:“简历做假也是一个很大的问题。我做人力资源这么多年,现在简历做假简直是让你觉得可怕。”这一现象在Tony看来与人的品性挂钩,他强调:“一旦你有欺骗,你也不要再想自己开店开业了。”Tony最后谈到:“不管白猫黑猫,能抓到老鼠的就是好猫,用科技的手段去抓还是我们用原始的方法去抓,确定找到了一只能抓老鼠的猫。” 针对Tony提出的问题,Maggie Shao则表示:“其实也有人从区块链的角度探讨过这个可能性。之前我们在探讨区块链技术如何运用到人力资源领域的时候,第一个就是可追溯,不可逆,同时不可篡改。能不能把区块链这个特点与刚才Tony谈到的简历上来,如果能识别真假简历,那就是一个新的产品。” 凤凰网的招聘总监王志红就科技招聘发表观点:“凤凰也在做自己的招聘系统。几万人的公司肯定要做自己的招聘系统。其实痛点来自于,很多时候纯的招聘系统是适合大众的,但不适合凤凰网的。现在如果通过这个系统,只要轻轻一按,符合所有晋升条件的员工就会出现在你的面前。凤凰网的痛点是人少,还需要借助科技的力量为我们分担和解忧。”最后,她表示:“当招聘的HR被第140位候选人放了鸽子的时候,这就是一场修行,你修行到一定的位置了,所以我们今天就是看得见未来但是需要面对现实,继续耕耘美好。” 随后陆胤先生则从法律的角度谈到了信息的真伪,面对这一问题他表示:“是不是应该建议他们制度,这个确实国家也在建立一些征信体系,但是我可以跟大家说一个现在还没有定的,但这是可以预期的,不太会建立一个个人职场征信体系。”他说道:“实际上法律不能给大家一个最好的结果,但是法律一般来讲是避免一个最坏的结果。招聘也是这样的。不见得能够招到一个最好的人,但每次遴选都是在踢出那些最不好的人,实际上你就是挑了一个最不会不好的人。”最后以陆胤先生的总结,结束了本次的圆桌论坛。 展区的部分精彩! 下午会场精彩内容分享: 首位演讲嘉宾是网红HR STORYWAY 联合创始人Maggie Shao女士。她分享的主题是每个雇主品牌都需要一个好故事。Maggie Shao女士以故事的方式,结合One Sight的经典案例,向大家展示了在科技的渗透之下,HR如何更好第为员工服务,为求职者服务,为企业服务,使企业面貌焕然一新。 接着猎聘首席数据科学家-单艺给大家带来了“AI/大数据赋能招聘”的主题演讲。演讲中单艺先生始终围绕“人才最贵”展开演讲,谈到了用大数据去衡量人才能力,并且强调更加聪明的方式是用AI处理大数据。他谈到:“我自己越来越相信,招聘这个行业的未来是一个人机协作的事态”,深度向人们剖析了大数据给人力资源带来了更多的机会,用以提高企业效率,增加其价值。Roy 也是HRTechChina平台多年的粉丝,HRTechChina能够有这样的机会邀请到Roy来分享也是荣幸之至。 随后的演讲嘉宾是六点一刻创始人&CEO Daisy Xu女士,她演讲的主题是“数据挖掘驱动招聘效率提升”。 Daisy Xu女士的演讲中引用了大量成功运用数据的案例,对比传统的招聘方式,大数据招聘更科学化,准确化。她还表示:“如果我们知道,我们在做计划的时候,我们要招的人他的画像越来越精准的话,我相信我们招人哪怕是招的慢一点,可能对组织的贡献也会更大一点。”  Daisy Xu 在数据分析与人力资本分析方面有着深厚的造诣,下周五(8月3日)人力资本分析高端峰会--People Analytics Forum  在上海亦将作为主咖分享! 继以上三位嘉宾精彩分享之后,是来自上海蓝白律师事务所的首席合伙人陆胤先生的又一轮精彩演讲,陆胤先生演讲另辟蹊径,从不同的切入角度,就“谈GDPR与个人信息保护法对招聘及招聘科技的影响”这一主题发表了自己的看法。陆胤先生表示在招聘过程中,个人隐私的保护值得引起重视,招聘科技使招聘更加信息化、透明化,使得个人隐私难以得到很好的保护。他表示:“我认为GDPR从长远来讲,对全球的信息采集这个行业是会有非常大的影响,我们轻松的获取没有责任去使用这种个人信息的时代已经结束。” 紧随其后的资深人力资源高管Rick Wu,他分享了“数据化引领全面HR和招聘管理”。他的演讲中再次强调了大数据的重要性。Rick Wu表示 :“从现在人力资源来看,我们要有用数据化做人力资源的思维,更多是靠数据来展现我们对事物的判断和前瞻性的规划。” 接着,来自百姓网的董秘高奕峰,结合最新科技,为大家带来了“区块链在招聘与激励中的应用”的主题演讲。高奕峰首先为大家深度剖析了区块链,接着谈到了如何将区块链和人力资源的日常应用进行紧密的结合,包括在某些知识点上进行了映射,列举了他们百姓网在HR工作当中的应用。 最后的主题演讲嘉宾是雇势新媒创始人欧阳泽林先生,“教你用抖音来招聘”的主题演讲将会场的气氛瞬间点燃。欧阳先生频频与听众互动,带动了全场气氛。他在演讲中,深度分析了现代人才的特点、爱好、兴趣、生活规律,也谈到:“我说的个体,讲个人品牌,有一个方法跟路径,当然每个背后都是要具体做的事情,组织讲雇主品牌也是一样的。”作为HR,懂得与各类人群交流,时刻关注最新的话题与科技,保持与时俱进,才能更好的拉近与人的距离,更好的为招聘人才服务。 随后,候选人体验最佳案例专场演讲将会议带向了高潮,由凤凰网招聘高级总监王志红带来了“凤凰的体验之旅”分享。王志红女士网名为钱多多,在招聘领域有非常丰富的实践经验和具有持续的探索精神。钱多多(王志红)女士详细介绍了凤凰网如何为候选人提供用心贴心的体验之旅!参会嘉宾纷纷表示凤凰网HR,对于候选人体验的规划设计与实践之用心,非常值得学习! 最后,票易通人力资源副总裁黄渊明带来的精彩案例分享。在候选人体验中,他总能在每一家企业身上找到一些反光点,他用“能以任何人为师,你就可以成为大师”结束了他今天的分享。 演讲结束后,各HR科技从业者在四季酒店进行了深度地沟通交流,其余获奖嘉宾及机构也分别进行了专题照片的拍摄。 中国人力资源科技飞速发展阶段,科技的快速发展带来的不仅仅是信息的快速膨胀,也给我们的招聘工作带来极大的机遇和挑战。如何更好的运用技术手段提升工作质量和效率,成为我们不得不面对的工作。相信接下来将有更多的企业和资本加入到人力资源科技领域!这也是未来不可避免的趋势。中国人力资源科技服务平台将始终保持以人为本(People First)的初心,持续不断地传播科技如何更好的赋能企业与个人,发挥全部潜能。 预告下接下来HRTechChina 在中国的活动安排: 中国人力资源三支柱论坛  上海  8月8日 200人 中国人力资源科技高峰论坛 深圳 9月7日 800-1000人 中国人力资源科技高峰论坛 北京 10月17日 800-1000人 中国人力资源科技博览会 上海  11月16日  3000人 在美国的活动安排: 中美人力资源科技高层论坛  9月28日    硅谷  200人 最后再次感谢我们的分享嘉宾、合作伙伴以及参会嘉宾!
    People Analytics
    2018年07月28日
  • People Analytics
    人力分析领导者的角色——第2部分:创造企业文化和塑造未来 文/David Green 来源:My HR future blog 在决定一个组织是否能够成功地实施人员分析并创建一个可持续的长期数据驱动的人力资源文化方面,人员分析的负责人是绝对关键的。 Arun Chidambaram帮助了四家财富500强公司在人员分析方面建立了可持续的能力,并在同行中被广泛认可为该领域的主要支持者和空想家之一。 在本系列的第1部分(问题1-8)中,Arun分享了他在一个人分析团队中所需要的技能和能力的经验,这些经验是如何随时间发展的,以及如何将团队与业务联系起来。Arun还概述了他进行人员分析项目的五步方法,许多人自此评论了他们发现的有用帮助。 人民分析领导者的角色-第2部分:领导团队,创造组织文化和塑造未来  在第2部分中,Arun和我涉及以下领域: 带领团队:深入论述了人员分析领导者的角色,包括典型的挑战,所需的技能和能力,以及在组织成熟度和动态外部环境中角色的演进。 发展企业文化:使分析成为人力资源和组织DNA的一部分的方法 塑造未来:关注人们分析的未来,以及我们可以期待看到的一些发展 道德与信任:透明、道德和数据隐私在人员分析中的重要性。 领导团队 问9:人力分析主管必须兼顾多个优先事项、不断上升的内部预期和迅速发展的外部领域。你认为你的角色的主要职责是什么?你如何平衡这些职责?  《人物分析》的负责人必须同时兼顾多个优先事项,大卫,你说得对,由于兴趣和需求的激增,《人物分析》是一个充满挑战和活力的领域。我将我的角色分为团队内部和团队内部的职责(如下面的图5所示)。对于领导者来说,很重要的一点是要充分了解这种氛围的每个元素,以支持他们的团队,并为企业提供可持续的、高价值的服务。 图5:PEOPLE ANALYTICS LEADER的公司内部和内部职责(来源:ARUN CHIDAMBARAM) 人员分析是过程、技术和技能的组合(参见第10和图7),在三者之间取得正确的平衡对于提供长期的可持续性能力至关重要。 应该记住的是,分析的作用在不同的公司之间是不同的。例如,一些公司将报告和分析合并在一起,而另一些公司则将它们区分开来。如果我们将关注点局限于分析,我相信团队将从事9个不同的工作类别(参见下面的图6)。作为领导者,您必须设计业务计划、创建预测并做出投资决策,如图5所示。 图6 -由人员分析团队承担的九大类工作(来源:ARUN CHIDAMBARAM) 问10:在你提到的三个要素中——过程、技术和技能——每个要素的主要特征是什么?哪个(如果有的话)是最重要的?这种情况会随时间改变吗? 过程 对我来说,这是三个中最难的一个。你必须得到高层领导的支持,你需要确保你完全符合商业计划,理解你的组织成熟的分析,向正确的人报告,并与内部的其他人建立强有力的合作关系。 技术 我强烈主张在技术方面,把时间花在企业内外。与支持企业分析团队的内部IT团队合作。在这里,您可以与具有高级可视化和统计背景的数据科学家合作。它们和你公司的其他商业分析团队一样是很好的资源。与他们合作,了解他们如何使用新技术。在供应商方面,参与并成为他们社区的一员,与你的同行交谈,找到可以帮助你解决对你的组织最重要的业务重点的合作伙伴。创建一个试点环境,并尝试与这些供应商的新事物。小心不要被压垮。你必须承认,你不可能买到你看到的每一件很酷的技术! 技能 人员的分析本质上是跨学科的。你需要能够理解员工行为的I/O心理学家,能够分析数据的经济学家和统计学家,以及有经验的人力资源从业者,他们可以帮助你进行文化转型。雇佣合适的团队是成功的最重要的一步,在这些技能上不要妥协。但同样重要的是确保你在合适的时间雇佣合适的技能。如果你在准备好接受高级数据科学之前就雇佣了一个统计学家,你最终会得到一个不快乐的露营者。作为一个领导者,你有责任为团队设定正确的路径,并确保每个成员都知道以下方面: 公司的决策文化 人力资源是如何工作的 数据隐私 你所在国家的劳动法。 领导者必须在分析团队对高级工作的渴望与业务和人力资源的成熟程度和准备程度之间取得平衡。这可能是一个微妙的过程,也可能是一个关键的过程,就好像两者都不同步一样,那么分析之旅就可能处于危险之中。 如果你在准备好接受高级数据科学之前就雇佣了一个统计学家,你最终会得到一个不快乐的露营者  问11:人力分析主管必须具备的最重要的技能和能力是什么?  我发现这五个特质帮助了我自己的成功,我领导的团队和我服务的人力资源/商业领袖: 要有耐心 变革管理在任何领域都是困难的,人员分析也一样。在建立一个成功的人员分析功能时,有很多可变动的部分。时机决定一切,但正如我们已经讨论过的,在引入与组织成熟度相关的新概念时,你必须冷静思考。人力资源部同事对分析的共同理解是非常不同的,因此你必须提供相应的分析支持。此外,领导者在非分析过程中有相当多的时间,所以耐心是成功的关键。 创新和整体思维  由于他们与来自不同背景的人一起工作,所以people analytics的领导者必须具有不同的思维模式。例如,业务和人力资源领导者较少谈论数据,并且要求与业务相关,而您的直接团队则希望进行关于数据和分析的技术讨论。“人民分析领袖”还与来自金融、IT、安全、法律、隐私、学术界和外部智库的不同人士合作。每个人都有不同的观点和目标,所以整体思考能力是分析领导者应该掌握的非常关键的技能。 项目和流程管理  人力分析领导者通常在人力资源部门领导一个相对新的、不断发展的计划,因此需要从前面领导,引导大多数的对话和项目。领导者不仅可以将时间限制在工作的技术方面,还需要在非技术方面领先。 例如,如果您正在引入组织网络分析(比如作为试点),那么领导者的角色就是识别和管理项目,寻找赞助,设计流程,做出购买租金的决定,与法律和 隐私,教育采购等。领导者必须在战术和战略思维之间轻松切换,并习惯处理模糊性和复杂性。 适应性领导  人员分析领导者管理一群非常聪明且需求量很大的人。 数据科学是最热门的业务领域之一,人力资源方面的人才供应短缺。这意味着领导团队是具有挑战性的。作为一个领导者,你需要非常清楚地设定和管理期望,以及对团队的需求保持开放和关注。你必须保持团队的参与,保护他们不受分析的要求,把时间花在他们的发展上,教育他们关于数据的隐私,帮助他们了解人力资源如何工作,以及你公司内部的商业文化是如何决策的。作为领导者,您还必须为团队创建一个生态系统,以便花时间在研究和数据上。 注意不要将他们的工作变成无休止的重复报告生成计划,而是将创造力保持在其中。 分析|品牌大使的经纪人/催化剂 人员分析领导者必须与业务范围内和整个行业内的其他分析群组建立联系。这样做的好处包括利用分析工具在整个公司实现规模经济。其他好处包括知识共享、资源共享和为团队确定职业道路(以及其他业务方面的人才)。 让分析成为组织DNA的一部分 问12:在绝大多数人力资源组织中,基于数据的决策仍然是一个新兴领域。如何改变企业文化,在人力资源商业伙伴(HRBP)、人力资源和更广泛的组织中融入分析思维?你如何确定并让人力资源和业务的利益相关者支持你实现这一目标?  首先要记住的不是“us”和“them”,而是“we”。我们首先要了解HRBP的作用,如果我们期望他们理解我们的工作,那么推荐HR领导或业务利益相关者一个流程,其中一个分析团队在项目开始时参与其中,然后通过实现与HRBP和业务涉众保持联系。通过这样做,你建立了相互信任,并在以下领域变得更有效: 正确地定义你要解决的问题 利用包括预期结果在内的正确变量 理解你需要接触的利益相关者、决策过程、讲程序和可视化技术,这些最有可能让你的观点被付诸实践 作为项目一部分所需的外部和内部数据源,以及可能需要收集的任何新数据 你需要接触的法律伙伴和工作委员会 数据隐私和文化问题 与HRBPs和商业利益相关者合作,更好地从他们的角度看待问题 在嵌入分析性思维方面,无论如何都要为HRBPs和更广泛的人力资源团队制定一个培训计划,以激发他们的热情,让他们对数据更加满意。给他们一些工具。例如,我发现为HR社区提供对Tableau或类似工具的访问权限可以帮助他们感受到我们工作的一部分。 最重要的是,在与HRBP和人力资源社区合作时,要有学习心态; 多听,少说话。 相信我,你会得到回报。 在与HRBP和人力资源社区合作时,要有学习心态; 多听,少说话。 相信我,你会得到回报 问13:当我与其他分析领导者交谈时,最大的挑战之一就是优先考虑你所做的项目。您如何建议确定项目请求的优先顺序?  创建一个过程来正确地定义和确定项目的优先级是人员分析团队发展到以下阶段的关键步骤: 确保团队的工作与关键业务目标和挑战保持一致 帮助人力资源和企业了解团队是什么(关键是团队没有什么) 优化团队的工作量。例如,通过将特定的项目与具有解决项目问题的优势或相对优势的团队成员配对,或者定期与团队进行评估,使他们在接受的工作中保持流动性; 支持团队的成长和该学科的投资计划 我过去为支持这一点而采取的一些步骤是: 规划和调整 在计划周期的早期,制定一个商业计划并与人力资源运营计划保持一致,这样你就能非常清楚地了解战略业务需求。这加强了与部门HRBPs的伙伴关系,支持计划,并确保从一开始就与所有利益相关者建立正确的期望。 创造一种氛围,让你可以说“不” 创造一种氛围,你可以对不属于团队责任的请求说“不”,例如,如果报告不是团队的一部分,那么要小心拒绝这方面的请求。否则,你可能会被大量的请求淹没,这些请求会分散你对你应该做的工作的注意力。仅仅因为你有信息并不意味着你应该提供它。 自动化和民主化的数据 开发一个通用的指示板,它为业务/人力资源涉众提供了在单击按钮时访问多个指标的机会。除了阻止您收到的大量请求之外,它还有助于教育您如何通过分析将描述性数据的提供与业务区分开来。 分享和交流 定期分享和沟通我们的工作 - 包括我们的生态系统的过程:我们如何工作,我们如何运行模型等。我发现越多的业务/人力资源利益相关者了解人员分析团队的工作,然后您获得的不当请求数量下降。 建立利益相关者的生态系统 将业务中的涉众与类似的请求连接起来,从而使项目进行一次,而不是多次。使用像R这样的程序,您可以运行一个一般化的代码,以根据需要分析不同组的见解,并从本质上生成请求。这方面的一个例子是我们对损耗的分析。 人员分析的未来  问14:人员分析空间正在迅速发展。 您如何掌握数据源(例如可穿戴设备),技术,分析工具以及您可以做的项目范围(例如网络分析和组织设计)的所有发展?  我建议花合理的时间在实验室环境中试验新的方法和技术。分析团队的部分共同作用应该是识别和连接新的供应商、对等组、参加关键的会议和研讨会,以及与分析领域的内部业务团队合作。 需要记住的重要一点是,需要对关键的HRBPs和人力资源领导团队进行循环,使他们能够通过演示和其他知识共享技术及时了解人员分析领域的进展。个很好的例子是组织网络分析(ONA),我们首先开始学习它背后的科学,同时,确定一个合适的试点项目,在整个公司中利用这一科学。我们与多家供应商、学术界和思想领袖合作,并将其带回我们的实验室,以更好地理解代购租赁的选择。 尽量不要被市场上的炒作淹没。专注于你想要解决的商业问题,关注你的公司文化。例如,如果你的组织还没有准备好接受包含员工可穿戴数据收集和分析的项目,那么就不要这样做。花时间尝试新的数据源和技术,等待合适的时间。在跳到解决方案前进行测试并保持耐心。 问15:你认为《人物分析》的主要趋势是什么?  人员分析是如此令人兴奋的工作领域的原因之一是空间中的活力和快速发展。我希望看到的一些趋势是: 法律、隐私和数据科学作为需求、经验和标准/治理在这些群体之间变得更加普遍。 人员分析将成为业务决策的核心,因此,人力资源战略和计划的设计周期将更加突出和更早。 透明度将成为新的准则——公司越透明,数据越大众化,就越能在数据科学(如可穿戴设备、社会感知等)中应用更新的技术。 作为一个功能,人力资源部门将花费更多的时间来衡量其项目的结果,并通过实验变得更加普遍。 IT、金融和营销等其他业务部门的分析人才将越来越多地将人力资源视为职业发展的机会。人力资源部门应该会看到人才在分析领域的供给增加。这是必需的,因为对人才分析人才的需求将呈指数级增长。 随着人力资源开始采用人工智能等新技术,人力分析团队将高度依赖于这种能力的开发和增长。 问16:最后,我们如何平衡我们应该做什么?你对道德和隐私等领域有多关心?对于那些寻求培养人们分析能力以获得员工信任的人,你有什么建议?  我们一直在讲道德和隐私可能是人们分析学科面临的最大也是最重要的挑战。鉴于我在可穿戴设备和人工智能等新兴数据源以及欧盟(eu)将于2018年5月生效的《综合数据保护条例》(GDPR)等法律方面所强调的趋势,这一比例只会上升。 对于那些寻求开发人员分析能力的人,我的建议是: 对公司透明,在你做的每一件事上都要透明。花更多的时间来沟通你为什么想要做某事,以及对员工的好处,而不是你在做什么。 在项目早期和交流结果之前,与人力资源、法律和IT部门密切合作。使其成为治理过程的核心组件。 不要想当然地认为你的人力资源团队了解数据隐私、法律要求和道德。与他们合作,共同理解法律法规。 密切关注你如何沟通你的团队工作,在适当的时候分享你在组织内外的成功经验。 使用可穿戴设备等新数据源,从小做起,进行实验。把它放在实验室里,从中学习,分享结果,然后再考虑扩展项目。 保持简单、可衡量和有形的结果。 以上内容由AI翻译,仅供参考 原文链接:https://www.myhrfuture.com/blog/2018/2/25/the-role-of-the-people-analytics-leader-part-2-creating-organisational-culture-shaping-the-future
    People Analytics
    2018年07月24日
  • People Analytics
    Workday、Ultimate、Slack的收购关注两因素:生产力和员工体验 文/JOSHBERSIN 如今,人工智能的收购已经很难跟上步伐,仅在2017年,就有超过108亿美元的资金投资于人工智能初创企业。在我所到之处,我发现软件公司都在开发更智能、更有预见性、更智能的工具。 在过去的几周里,我想提到的有三个重要的交易,每个都集中在一个主题上:使用人工智能和对话界面来改善员工体验,并对我们的生产力产生积极的影响。 太多的信息:工作效率正在下降  正如我在过去一年中所写的,生产率落后是一个经济问题,导致工资下降,很多人加班。如今,人们每天有35%的时间在阅读电子邮件,而我们在交流的新工具上花费过多。 我们对超连通职场的研究发现,平均每家公司都有7个不同的沟通系统,70%的高管预计会购买更多。技术供应商正以最快的速度发明它们。 Slack现在有800万用户,微软有20多万家公司使用团队,Facebook有3万家公司使用Workplace, Gmail上有12亿多用户,所有这些用户都可以使用Hangouts。在我们的消费者生活中,它甚至更容易让人分心:统计数据显示有15亿人使用WhatsApp, 13亿人使用Facebook messenger, 10亿人使用微信,3亿人使用Skype。  我们问人们这些新工具是否对他们的工作有帮助,超过三分之二的人告诉我们新工具正在阻碍我们。我们喜欢我们的个人工具,但我们花太多时间处理这些工具。一项相当惊人的研究发现,我们每6分钟检查一次这些系统,而我们40%的人在工作中从未有过30分钟不受干扰的时间。 这是荒谬的。我们的交流模式被打破了。为什么公司中的任何人都有机会在我们向他们发送电子邮件,给我们发送消息或在Slack上提及我们的时候分散我们的工作注意力? 这是不健康的。研究表明,为了应对这一冲击,压力会大幅增加。作为回应,我们现在正在购买“幸福解决方案”,为这个问题贴上“创可贴”的标签。当然,瑜伽、正念和冥想都很好——但真正的原因不正是效率低下的工作场所吗?  生产力成为人力资源的新主题  虽然我知道你们大多数人都有一个专注于“员工体验”的新项目,但我真的认为人力资源的新重点应该放在生产力上。生产力是健康、快乐和工作投入的关键,很多研究都支持这一点。 也许最令人信服的是特里萨·阿玛比尔的《进步原理》一书。通过对员工工作日志的分析,她令人信服地证明,工作中最令人愉快、最有价值的部分是“把事情做完”。所以,让我们把注意力集中在提高人们的工作效率上,我们将看到参与程度、幸福感以及其他衡量标准的提高。 当然,我们必须处理工作场所、管理实践、目标和奖励等问题,但最终如果我们想办法帮助人们完成他们的工作,所有这些项目都有更多的关注和价值。例如,如果你在管理一个研究部门,你的人才战略应该集中在帮助人们进行伟大研究的项目上。销售、市场营销和其他业务部门也是如此。 而这个问题,即简化工作的需要,正导致一些大型的人力资源技术并购。 Workday收购Stories.bi 我要强调的第一个是Workday收购一家名为Stories.bi的增强分析公司。 我刚刚看到这个系统的演示,它让我大吃一惊。 该公司使用人工智能监控和分析公司数据库(现在主要集中在Workday),以识别趋势,数据偏离范围,或与计划的差异。然后,它会用简单的英语(或其他语言)生成一个对话界面,指出它学到的东西。 这是一个例子: 正如你所看到的,这些小卡片准确地告诉你正在发生什么,你不需要进入一个电子表格,点击一个仪表盘,或者雇佣一个统计学家来弄清楚为什么一些商业指标没有朝着正确的方向发展。它是一个人工智能工具,叫做增强分析(Augmented Analytics),但实际上它是为了提高生产率。Workday计划将该系统整合到其平台和新的Workday Prism分析产品中,这将使我们的生活变得更加轻松。 我研究分析学已经有30年了,整个市场仍然是一个工具。虽然许多像Visier这样的高级供应商现在提供开箱即用的解决方案,但是它是像 Stories.bi这样的工具。这将使分析对每个人来说都很容易。我必须相信,这种增长将出现在我们的大多数人力资源产品中。 Slack收购使命 第二个我想指出的是Slack的使命收购,在Slack内部创造工作流程和“员工旅程”。 如果你接受这样一个事实:我们一半的生命都在这些消息平台上度过,为什么我们不利用它们来做更有意义的事情呢? 一群小型初创公司正在构建工具来阅读和解释你的信息,并发送提示、建议和培训提示,使你的工作生活更轻松。 (其中有一个叫迪斯科的,当你对某人说“谢谢”的时候,你会知道,并建议你把这些信息发送给他们的员工记录。) 刚刚获得的产品Slack是帮助人力资源部门(以及其他部门)在消息传递平台上构建员工体验的工具。这种类型的“嵌入式人力资源工作流”正变得非常流行(IBM的认知助手也这么做),而Slack现在正使其成为产品的一部分。 虽然大多数公司还没有把Slack作为企业范围的平台(微软、谷歌和Facebook也都想要这个市场),但我认为这个功能使这个目标更有可能实现。Slack现在被我们称为“员工体验平台”,是一个巨大的新兴快速发展的商业市场。(这里的领导者有ServiceNow、PeopleDoc、Salesforce等。) 在接下来的几个月里,我将会写更多关于这个领域的文章,但从某种意义上说,Slack刚刚“进入这个市场”。 这里的目标是生产力。我们不需要离开我们的“生产力系统”去完成我们的人力资源工作,这是市场上一个巨大的趋势。 Ultimate 收购PeopleDoc  我想指出的第三个交易是我的ERP朋友们正在关注的: Ultimate软件收购PeopleDoc,一个快速增长的员工体验平台。这家公司的总部设在法国,因此它为许多欧洲公司提供服务,在这些公司,单是雇佣合同的管理就令人头疼。 在过去几年,PeopleDoc发现了员工自助服务、案例管理、文档和服务管理软件(我称之为“员工体验平台”市场)的市场,他们开始疯狂扩张。(目前这个市场最大的玩家是ServiceNow,他们正在创造一个市场,随着时间的推移,这个市场可能会变成一个价值数十亿美元的市场。) 虽然我还没有关于Ultimate软件计划的任何细节,但我可以再次向您保证,这项交易也是出于提高生产率和员工工作经验的需要。Ultimate软件公司(Ultimate Software)是市场上管理最好的人力资源软件公司之一,最近收购了Kanjoya(一个基于人工智能(ai)的员工调查和参与工具),这正好符合该公司的战略。 关注人力资源技术的更多信息  秋天即将来临,所以我已经开始着手我的年度“人力资源技术中断”年度研究。我想指出的一个大主题是人力资源软件市场从“参与系统”到“生产力系统”的巨大转变。这三桩交易只是冰山的一角,在接下来的几个月里,我们将拭目以待。 以上内容由AI翻译,仅供参考 原文链接:https://joshbersin.com/2018/07/ultimate-workday-and-slack-acquisitions-focus-on-productivity-and-employee-experience/
    People Analytics
    2018年07月23日
  • People Analytics
    人力分析领导者的角色-第1部分:建立能力 文/David Green 第1部分:建立团队和组织能力。 第2部分还将介绍people analytics leader的角色和职责,如何创建分析文化和分析的未来 正如我之前所写的,在人力资源分析和数据驱动决策中,成功开发和构建了可持续能力的组织具有许多共同的特点。 领先公司共有的一个特点是有一个鼓舞人心的领导者——“人力分析主管”。乔纳森•费拉尔(Jonathan Ferrar)撰写的这篇文章,收录了2017年40篇最佳人力资源分析文章。“人力分析”(People Analytics)的负责人阿伦•奇丹巴拉姆(Arun Chidambaram)列出了乔纳森描述的所有问题,他在“人力分析”领域工作了15年。在此期间,Arun帮助了四家财富500强公司在人员分析方面建立了可持续的能力。 Arun当之无愧地被同行认可为该领域的主要权威和梦想家之一。他经常被邀请分享他在会议上的见解,就像他去年在伦敦的人物分析世界(见此处的亮点)和费城的人物分析和工作的未来(见下图和此处的重点)。对于那些在纽约地区的人,您将能够在4月5日的Hunt Scanlon主持的数据驱动公司活动中看到Arun(见下图)。 2017年9月,Arun Chidambaram在费城的人力分析和工作未来发表演讲 PEOPLE ANALYTICS LEADER的角色-第1部分:建立团队和增强组织能力  我很高兴Arun同意分享他在《人物分析领袖的角色》这两集系列文章中的一些见解。“第1部分涵盖以下领域: 人员分析团队所需要的技能和能力,以及这些技能是如何随时间发展的 关于团队应该如何与业务保持一致的不同选项。 进行人员分析项目的方法 开发团队成熟度的关键里程碑 关键的学习和成功的秘诀。 问1:嗨,Arun,根据你的经验,在一个人分析团队中你需要的技能范围是什么? 团队的技能和组成取决于许多因素,包括组织在分析方面的成熟度,以及团队是否也负责报告。如果我们把报告部分放在一边,我所建立和领导的分析团队将拥有数据科学、行为经济学、工程和数学背景的成员结合在一起。直接向CHRO或CHRO的一个领导团队报告非常重要,因为它向业务和人力资源部门证明了分析是人员战略的一个组成部分。 问2:团队应该如何与业务保持一致? 通常,大多数人分析团队最初都是按照部门和关键的人力资源兴趣区域进行协调的。在我的经验中,这种结合一开始可以很好地工作,但是随着业务需求的增长,您需要以不同的方式思考。您需要这样做,一方面是为了优化容量,另一方面也是为了确保团队正在进行对业务很重要的项目。对工作进行优先排序可能很快成为一个问题,这对分析人员的负责人来说是一个重大挑战。为了缓解这一问题,我采访并与人力资源领导团队进行定期对话,共同确定最重要的3-5个主题,这是实现业务和人力资源战略的关键。然后,我将团队中的一名成员作为每个主题的中小企业来管理传统和创新的分析项目。 优先考虑这项工作可能是人力分析的主要挑战。 问3:你能解释一下“传统”和“创新”项目是什么意思吗? 当然,传统工作仅限于对现有的一般人力资源项目进行微调,并利用分析来获得更大的价值,例如在继任规划等领域。相反,创新的工作包括使用新的和新兴的方法,如组织网络分析(ONA)来帮助解决业务问题。你如何平衡你在每个项目上花费的时间取决于你的组织成熟度。 下面的图1说明了组织成熟的重要性。图上的顶线显示分析能力以指数速度增长。底线代表了人力资源消费者的意识,从我的经验来看,这一意识增长得更不规律,而且速度也更慢。知道你适合的地方和差距的程度有助于传统和创新之间的过渡和平衡。 图1 -了解你的适合程度和差距的程度-人分析的组织成熟度(Y轴=投资/成熟度/产品等);X轴-时间)-来源:Arun Chidambaram 2月13日与Arun一起参加网络研讨会,与Stela Lupushor和Antony ebel - ebanda一起讨论组织网络分析(ONA)的实际应用。 问4:团队的结构是如何随着时间演进的?这与组织成熟度有什么关系?  好的问题和团队结构是我非常感兴趣的话题。不用说,团队的结构会在公司之间有所不同,但我相信组织成熟度的水平在这个结构随着时间的发展过程中也扮演着重要的角色。 我使用的模型(见图2)描述了我在这个领域的想法: 图2:人员分析团队结构和业务一致性的演进(来源:Arun Chidambaram) 部门一致  一个典型的人力资源结构有一个商业伙伴支持每一个业务,包括奖励和多样性等专业领域。我所见过的最常见的人员分析结构将一个团队成员与支持一组业务单元/部门的HRBPs联合起来。随着你的组织趋于成熟,需求将远远超过供给,而这种结构有崩溃的危险。 人力资源主题一致  组织你的团队的第二种方式,除了部门一致性之外,是了解公司的关键人力资源优先事项,并使你的团队专注于这些关键主题,如员工规划和人才预测。这种方法可以帮助您确定工作的优先级,并在一定程度上解决需求海啸。然而,就像在业务单元/部门一致中一样,随着人员分析能力的增强,这种结构将无法维持需求的强大力量。 中小企业一致  最后,随着需求的增长和成熟度的不断提高,我认为人员分析功能将需要划分为两个主要领域:1)面向客户;ii)主题专家(或非客户端)(见图3)。 图3 -将人员分析团队与主题专家和面向业务的顾问组织起来并进行对齐(来源:Arun Chidambaram) 在此模型中,人员分析团队中面向客户的团队与业务部门和HRBP建立联系,以了解问题,管理项目并运行事后分析和干预。虽然这个团队应该具备基本的核心分析技能,但他们的专业技能将更侧重于咨询、讲故事、沟通以及项目和项目管理。 中小型企业(或非面向客户的角色)需要跨关键学科的深入主题专业知识,如数据工程、研究和数据科学、实验和设计思维、可视化/报告和技术。我设想每一个中小企业都是由一个致力于自己专业领域的人领导的。 如今的团队结构通常会让成员同时面对双方(中小企业和客户)——这种模式的潜在挑战是,当一些分析师在决定专攻哪个方向时,他们会发现很难放弃另一方。 问5:根据您的经验,在组织内建立一个坚实的人员分析基础的关键里程碑是什么? 根据我的经验,我将把它归纳为五个主要里程碑: 建立一个可持续的和长期的分析能力,重点是交付业务结果 与业务中的其他分析团队建立紧密的合作关系,并开发一个实践社区来共享过程、技术和科技。 开发一个严格的5步方法,所有项目都要涉及,这对成功至关重要 建立与法律和数据隐私的关系,以便更好地理解人才分析中数据的使用 建立一个人才分析实验室,测试分析思维,并尝试新的举措,如组织网络分析(ONA)  问6:请您提供您的5步研究方法的更多细节,以及它是如何对您的成功至关重要  每个潜在项目的方法始于人力资源和业务同事之间关于问题声明的对话,遵循五个严格的步骤,从撰写研究建议到支持业务进行事后分析,并参与下面图4所示的行动后审查。 图4:People Analytics的五步研究方法(来源:Arun Chidambaram) 这五个步骤可概括为: 问题范围——这一步涉及到与人力资源或相关团队成员沟通,以了解业务问题及其影响 概念设计——对于每一个被接受的研究提案,我的团队会制定项目的概念设计 数据——收集和管理来自调查业务问题所需的各种来源的数据。 分析——这是我们花时间构建、分析和测试模型的技术步骤 Post hoc -这个关键步骤包括评估干预的影响和测量结果/ROI,以及检查模型是否符合规范,并在必要时进行必要的调整。 这5个步骤的方法有助于团队、人力资源和业务客户对业务问题达成相互理解,并以有效和及时的方式解决问题。 问7:在构建组织能力和领导人们分析功能时,你遇到过哪些典型的挑战和关键经验?  在我工作过的机构中,建立本质上是一种新能力的做法,既有回报,也有挑战。关键经验包括: 理解组织的分析成熟度(参见图1和对问4的响应)对于保持这种能力是绝对重要的 平衡定性和定量科学 与法律和隐私密切合作——不要认为你的人力资源团队应该或确实知道关于数据隐私规则的一切 区分分析和报告——两者都很重要,但是您需要清楚您的愿景和人员分析的目标。 为人员分析团队创建正确和最优的结构来支持业务目标 倾听人力资源利益相关者和商业同事的意见,并加强合作 在工作中保持透明,专注于你正在做的事情,而不是你如何去做。 以上内容由AI翻译,仅供参考 原文链接:https://www.linkedin.com/pulse/role-people-analytics-leader-part-1-building-capability-david-green/
    People Analytics
    2018年07月20日
  • People Analytics
    数据显示:人力分析能为企业增加价值 HR Tech China获悉人力分析最新数据,下面我们来看这组数据: 数据显示: 人力分析能为企业增加价值 全球75%的人力资源专业人员正在使用数据来了解员工绩效和生产力问题 65%在企业中具备强大的人力分析文化的专业人士,报告说业务表现强劲 在那些分析文化较弱的企业中,只有32%的人报告说业务表现强劲  对人力资源能力缺乏信心 全球53%的人力资源专业人士认为,他们的人力资源团队具有可证明的数字和统计技能,而金融专业人士的这一比例为36% 英国的人力资源分析能力和信心落后于其他市场 21%的英国人力资源专业人士有信心进行高级分析,而在东南亚,这一比例为46% 以上内容由HR Tech China综合整理报道
    People Analytics
    2018年07月17日
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