• People Analytics
    人力资源分析如何帮助提高员工绩效 文/ Ritesh Patil 人力资源是全球许多企业的重要组成部分。这一角色在过去几年中不断演变。人力资源不仅仅局限于一个组织的招聘和退出过程,它还有更重要的作用。随着行业间竞争的日益激烈,人力资源管理者在组织中寻找和招募最优秀的人才变得越来越具有挑战性。从招聘空缺职位到寻找和雇佣人才,这是一项艰难的工作,招聘人员的任务直接影响到公司的底线。为了帮助人力资源部门验证它作为商业表现的重要角色,人力资源分析被应用了。 什么是人力资源分析? 人力资源分析是关于收集、组织和验证与人力资源运营相关的数据,如招聘、培训和开发、员工福利、员工关系和保留,以帮助他们在所有这些领域做出更好的决策。人力资源部门每天都在使用不同类型的软件和技术来创建大量的数据。然而,人力资源分析将这些数据转化为有价值的洞察力。 将人力资源分析应用到业务结构中有显著的好处,越来越多的企业都在争取更好的ROI。在这篇文章中,我们列出了5点,展示了人力资源分析是如何帮助你提高底线增长的。 人力资源分析如何帮助你改善公司文化 1. 重视员工培训计划? 对于企业来说,专业培训是雇佣和留住高素质员工的一个重要方面。如果对职业发展培训没有或几乎没有贡献,这可能会导致员工疲惫、士气低落和缺乏方向。 此外,一个专业发展培训计划描述了你正在帮助你的员工实现他们的全部潜力,并激励他们在他们的专业领域学习新的技能。这是一个成长中的企业重视员工和他们对公司的贡献的标志。 人力资源分析有助于识别员工的相关专业培训课程,衡量员工的进步。它分析了培训的有效性和培训过程中每个参与者的成本。 通过对参加培训的员工数量和所涉及的成本的深入了解,您就可以确定这对您的企业是否是一种具有成本效益的方法。 2. 改进招聘流程 招聘过程对雇主来说有点挑战性。通过人力资源分析,你可以通过收集员工之前的招聘信息来改善招聘流程。 例如:在面试你公司现有职位的10位候选人时,你发现6位候选人有不适合你公司文化的共同特点。利用这些信息,你可以自动删除这些申请人的特点,从空缺的职位在不久的将来,并改善招聘程序。 这是一种聪明的方法,可以减少用于评估不合适的应用程序的时间,并加快流程。同时,你有更多的时间来评估适合你的业务的候选人。 3.提高员工保留率 对于一家需要解决的公司来说,员工保留率降低可能是一个令人担忧的问题。虽然可能有各种各样的原因,但重要的是直接研究公司的文化、薪酬、结构和商业模式,以便更深入地了解裁员背后的原因。此外,您需要应用策略来限制员工数量的下降。人力资源分析可以提供数据驱动的理解为什么员工选择离开和工作的漏洞。 可能的原因包括表现不佳、缺乏技能、薪酬问题或其他公司政策。通过离职和留职面谈、员工满意度调查和团队评估,您可以发现组织中可能存在的影响员工自尊和归属感的问题。 不要忽视这些问题,你必须主动解决它们。这可以帮助你提高整体的底线,因为你将避免支付与招聘和培训新候选人相关的不必要的成本。 4. 为未来的前景让路 就像你可以提高员工流动率,避免聘用效率较低的员工一样,识别、聘用和提拔合适的员工应该是人力资源管理的重点。这就是人力资源分析帮助您识别那些可以预测组织成功的特征的地方。所以,最好是寻找人才,避免犯那些代价高昂、需要花费大量时间来改正的错误。 有时,如果个性和他们的技能以正确的方式结合在一起,这可以是一个完美的融合,以提高一个团队的效率。分析有助于优化流程,以更快地组装和释放高效团队。这不仅仅是避免错误——这是关于鼓励个人以最好的方式使用他们的技能。所有这些都是为了您的组织和客户的利益。 5. 数据收集 为了识别出相互响应良好的基本特性,以及那些不符合公司文化的特性,收集足够的数据非常重要。在这个有着复杂系统、大型企业中的团队动态和业务流动性的时代,您只需要数据。世界上的大公司投入巨资获取员工、竞争者和客户的数据是有原因的。这些组织知道数据在其合作伙伴和公众中的重要性,无论是好是坏。为了在激烈的竞争中茁壮成长,他们用数据塑造自己成功的未来。 结语 出于几个原因,企业中的人力资源分析是一个公司成功的关键因素。通过人力资源分析收集有价值的数据,可以更好地改善公司的支出、运营和生产率。 以上为AI翻译,内容仅供参考。 原文链接:How HR Analytics Can Help Improve Employee Performance
    People Analytics
    2019年01月28日
  • People Analytics
    人员分析:为什么统计不是浪费时间 文/Erik van Vulpen 许多人力资源从业者都有人力资源管理研究或工业和组织心理学的背景,而这些研究严重依赖于向学生讲授统计数据。作为一名学生,通常很难想象为什么统计数据如此重要。特别是如果你不想成为一名学术研究人员,统计数据会让你感到浪费时间。我们大多数人都希望与人合作,只是“做”人力资源,与统计数据的相关性便开始缺失。 然而,正如大多数人员分析人士所知,人力资源中统计数据的应用是我们称之为人力资源分析的基础。了解统计数据,了解如何以不同方式查看数据,以及在需要时分析数据,有助于我们做出更好的决策。 事实上,这是我经常从统计学的学生那里听到的。在制定更好和基于证据的决策方面,没有什么比对基于统计数据的结论和基本理解更有帮助了。 人员分析统计 聚合多个系统的数据并创建HR指标的仪表板,如使用Excel,Power BI或R来制作可视化数据,是实现人员分析的重要步骤。 但是,如果事实证明您拥有的数据不具代表性,那么您的结论和决定会发生什么?如果您需要轻松检查数据的质量和准确性,并轻松删除偏差结果的错误异常值,该怎么办?能够系统地思考数据对于人员分析至关重要,并且知道如何检查相关性以及因果关系成为人员分析的核心。 统计上显着的异常值 统计数据是人员分析的重要组成部分,适用于各种分析。例如: 如果您的大多数人表现“满意”,您将如何区分好或坏的表现?对数据进行区分,以得出结论并充分理解,是人员分析不可或缺的。 或者,当您启动分析项目时,您是否发现数据有回归到正常平均值的趋势?分析项目通常是对组织中问题的响应,但这个问题可能是由数据中的偶发性异常值引起的。这意味着下次我们进行测量时,这个异常值将降低到正常水平,这被称为回归均值。 另一个例子是问卷的答复率。您上次参与调查是否在组织中的不同群体之间获得了相同的回复率?或者这是你没有检查的东西?要了解某些群体在您的调查中是否过多或不足,您可以使用一些相对简单的统计技术来检查这一点。 对于我们的读者,Daniel Kahneman的书《思考的慢与快》强调了对数据进行深思熟虑和系统思考的重要性。通常我们能够在看到信息后立即快速处理信息,但这会受到我们的偏见和其他情绪的影响。只有采取更加审慎和合乎逻辑的方法,我们才能开始做出更客观的决定。统计学的学生在这方面表现得更好,因为他们知道人们容易受到的许多谬误引导。   以上为AI翻译,内容仅供参考。 原文链接:People Analytics: Why Statistics Is Not a Waste of Time
    People Analytics
    2018年12月19日
  • People Analytics
    人员分析:在人员流动模型中建立可解释性 文/Ridwan Ismeer 最近,我有幸与来自新加坡理工大学的一群才华横溢的学生一起工作。他们的任务是帮助构建一个非常普通的人员分析应用程序:预测员工流动率(此类应用程序的优点、相关性和伦理值得商榷,可以单独讨论)。 摘要:建立一个能够准确预测员工情绪的模型,在0-6个月,6-12个月和>12个月的时间范围内的周转风险。 这两项不可谈判的要求是: 1.准确性:真阳性高,假阳性低。大多数实践者会强调低假阴性,但我们有理由不这么做。 2.可解释性:在人员分析中,模型的可解释性是采用模型的关键。人员分析的最终用户通常想要理解为什么模型要预测它是什么。事实上,GDPR有新的规定要求人工智能的决定是可解释的。 现在,任何分析实践者都可以很快地指出,这两个需求之间存在一个内在的平衡。精确的模型很少是可解释的。可解释的模型很少是准确的。但我们想检验这个假设的二分法。因为在人员分析中,仅仅精确是不够的——它需要用户能够理解。 除了我们两个严格的要求外,我们还为团队提供了一个强大的人力资源指标列表、一个足够大的数据集以及评估以下算法所需的基础设施: 和往常一样,xgboost在预测营业额方面表现最好(引用Kaggle上最常用的算法之一)。事实上,它的TP和FP速率满足了我们对精度的要求。容易解释的模型,如GLM和逻辑回归只是没有比较。 然而,任何以前使用过这个算法的人都可以证明,要想弄清楚它的黑盒子里发生了什么是多么困难。我们可以告诉股东鲍勃的离职风险很高,但我们无法解释原因。 或者我们可以吗? 将可解释性构建到像XGBoost这样的算法中并非易事,但这是可能的。除了向涉众提供处于风险中的员工的姓名之外,我们还为他们提供了一个交互平台,用于修改现有的功能,并重新运行模型,以指向导致模型将其评为处于风险中的功能。如果鲍勃去年升职了,模特会得出同样的结论吗?是的,它将。如果Bob在一个较小的团队中,模型会得出相同的结论吗?是的,它将。如果他的工资比市场上的要高呢?不。瞧。 由于用户需要进行多次迭代才能更好地理解每个案例,因此需要进行大量的工作,但是它允许我们保持较高的准确性,同时为涉众提供必要的模型内部工作,以使其更易于解释。 一些免责声明:   1.本帖旨在解决可解释性和准确性之间的错误二分法,而不是鼓励使用个人离职模型。事实上,我甚至会说,诸如加薪和提供晋升等行动绝不应以离职风险为基础。这对精英文化来说可能是灾难性的。对一般离职动因的综合分析应该是离职模型所能做到的。 2.首先,关于可解释性的必要性有很多争论。埃尔德研究中心的约翰·埃尔德博士认为,人类过于依赖基于先前经验的确认偏差,无论如何都无法客观地解释模型的结果。辩论还在继续。点击这里了解更多内容。 3.图像中使用的数据完全是基于虚假数据,仅用于说明方法。 4.我有自己的看法。   以上为AI翻译,内容仅供参考。 原文链接:People Analytics: Building for Interpretability in Turnover Models
    People Analytics
    2018年11月30日
  • People Analytics
    员工敬业度的未来:个性化福利和预测分析的好处 作者:Prarthana Ghosh 根据一项新的哈里斯民意调查,样本规模为2,257人力资源专业人员和CareerBuilder的招聘经理,错误的候选人选择使普通雇主在2017年花费了14,900美元。此外,10%的参与者表示缺乏足够的工具造成严重影响错误的候选人选择。这些数字说明了无处不在的招聘障碍,并指向甚至更大的保留障碍。难怪今天的每个组织都在升级员工敬业度!公司最终制定(或正在制定)将员工视为数字消费者的转变,他们需要能够以与家中相同的舒适度连接和插入工作。 例如,Deloitte的ConnectMe不仅利用Salesforce的一流CRM云解决方案,还通过富有洞察力的数据挖掘和基于需求的解决方案提供真正数字化工作场所的创建和维护,并改善员工体验,从而更好地参与。 个人风格 随着工作的概念不断发展,今天更多的员工似乎想要在家工作。无论是他们的工作地点,他们使用的工具,还是他们遵循的计划,员工都会寻求一定程度的个性化,使他们更好地与工作联系起来。 随着我们最近的数字飞跃,个性化现在可以达到一个全新的水平,因此是工作场所,行业和地理区域的普遍趋势。今天的体验式员工可能希望“会面”并与世界各地的同事进行面对面的交谈,并与新的AR(增强现实)工作场所不再是虚构的工作场所。员工现在可以在AI助手的帮助下将日程安排从日常任务中解放出来。他们可以通过充分利用直观的软件并使用分析来预测未来的步骤来更好地规划他们的工作。具有讽刺意味的是,非人为干预可以增加人类个人的触觉,这是今天不可避免的必要条件。 以下是不同参与程度的图示。个性化必须扩展到所有这些级别: 个性化创新的含义 因此,今天工作中的个性化不仅仅是允许员工引入他们自己的系统或咖啡杯。它还可以承认员工需要从“无干扰”的位置远程工作。目前,个性化的参与努力正处于从事后的困境转变为常态的过程中。 随着工作文化演变为相互联系,有凝聚力的生态系统,BYOS(自带软件)等新趋势越来越受欢迎。此外,这指向了一个更有趣的转变 - 允许员工自由个性化工作流程的组织 - 选择他们认为最有利于他们的企业应用和软件。 随着软件产品本身逐渐转向智能,个性化,特定和量身定制的体验,每个人都有权在工作中获得自己的个性化品牌。这对软件公司也有影响,因为他们现在不仅要保持领先地位,而且要确保他们的产品能够与客户收听的其他应用和软件相得益彰。对于试图适应这些新趋势的组织而言,这是一个关键的学习点,以便信息和通信在不同平台之间无缝流动。 工作中个性化面临的主要问题是安全性和合规性。监督的基本格式要求在保护公司信息,遵守不公开和其他此类协议方面进行变更。每个组织都要权衡允许BYOS环境的好处是否会抵消风险。 参与重新定义 今天有相当大比例的员工会选择生活津贴而不是更大的薪酬。劳动力行为方面的这些重大变化有助于引领我们今天在行业中看到的思想复兴。现代员工希望他/她各自的组织为他们的生活增加更多的财务价值。承认,个人和职业发展,幸福和健康,工作与生活的平衡是工作的其他方面,在参与和保留方面越来越重要。 根据Forrester Research的研究,员工体验为2017年的工作未来提供动力,除了因工作努力而得到认可外,员工还寻求技术驱动的体验式,身临其境的流程以及个性化福利等切实变革。美国海斯在2017年进行的调查显示,71%的参与者表示,他们希望接受较低的工资,以便在过去的经验,现有需求和未来计划方面实现更大的角色协调。此外,可定制的福利似乎对员工忠诚度产生直接和积极的影响,如MetLife,2017年第15期美国员工福利趋势研究报告所示。 预测分析:行为的水晶球? LifeWorks的分析,关注:如何开发和支持今天的员工,2017年,列举了组织如果未能调整他们的战略以提供个性化和真正吸引人的员工体验,他们将面临失去优质员工风险的风险。这就是使用预测分析的礼物发挥作用的地方。员工是人,分析人类行为往往造成困难,因为它的活力和需要考虑到个体差异。这些数据点不仅有助于跟踪工资单,福利登记或增长预测,还可以预测员工的成长和寿命。 “如果你有分析能够帮助你根据他们过去的表现,他们的技能水平,他们的个性和他们的文化契合来预测候选人的成功,那么它可以更好地描绘出他们如何适应你的公司,”Michael Fauscette说。 ,G2 Crowd的首席研究官。“如果分析能够预测候选人的成功,那么这对招聘流程来说可能是一个巨大的好处,如果合适,那么留住员工是一个巨大的好处。” 与工作中的任何技术组合一样,行为分析也伴随着一系列法律和道德问题,因为监控员工行为有其复杂性并需要得到承认。因此,它需要一定程度的员工教育,让所有员工了解他们的数据如何被使用以及用于何种目的。这也有助于更好地分析法律影响。此外,在组织实现转变之前,各级领导层和人力资源部门必须允许个性化和预测分析的渗透。 虽然员工参与空间会改变,变异和发展,但目睹未来的变化将会很有趣。公司是否会继续使用反应方法来回顾它,或者我们是否准备好进行直观,预测和主动的行动? 以上为AI翻译,仅供参考学习~   原文如下: The Future of Employee Engagement: Perks of Personalization and Predictive analytics According to a new Harris Poll with a sample size of 2,257 HR professionals and recruitment managers for CareerBuilder, the wrong choice of candidate cost the average employer a steep $14,900 in 2017. Moreover, 10% of the participants stated the lack of adequate tools contributed severely to wrong candidate choices. These numbers speak of a ubiquitous recruitment hurdle and point towards and even greater retention obstacle. No wonder every organization today is upgrading their employee engagement methods! Companies have finally made (or are in the process of making) the shift to regarding their employees as digital consumers who need to be able to connect and plug into work with the same comfort level they have at home. ConnectMe at Deloitte for example, not only utilizes the best in class CRM cloud solution by Salesforce but also provides for the creation and maintenance of a truly digital workplace through insightful data mining and need-based solutions and improve employee experience and thus look at better engagement. A personal touch With the concept of work having evolved, more employees today seem to want to feel at home at work. Whether it is the location they work out of, the tools they use or even the schedule they follow, employees look for a certain level of personalization that makes them relate better to work. With our recent digital leaps, personalization is now possible at a whole new level and is thus a pervasive trend across workplace, industries and geographies. The experiential employee of today might want to “meet” and have a face-to-face conversation with colleagues across the world and with the new AR (Augmented Reality) enabled workplaces that is no longer fiction. Employees can now free their schedules off routine tasks with the help of AI assistants. They could plan their work better by making the most of software that is intuitive and use analytics to predict the steps ahead. It’s ironic that non-human interventions could increase the essentially human personal touch that is an unavoidable requisite today. The following is a pictorial depiction of the different levels of engagement. Personalization must be extended across all these levels: Implications of personalized innovation Personalization at work today is thus more than just allowing employees to bring in their own systems or coffee mugs. It could also be acknowledging the need of an employee to work remotely from a “distraction-free” location. At the moment, personalized engagement endeavours are in the middle of moving from being an afterthought to being the norm. With work cultures evolving into connected, cohesive ecosystems, new trends like BYOS (Bring Your Own Software) is gaining popularity. Moreover, this points towards a more intriguing shift – organizations allowing employees the freedom to personalize work processes – to choose enterprise apps and software that they feel benefit them the most. With software offerings themselves moving toward intelligent, personalized, specific and tailored experiences themselves, everyone is entitled to their own slice of personalized brand of reality at work. This has implications for software companies too since they now not only have to stay ahead of the curve but at the same time, ensure that their offerings play nice with the other apps and software that their customers tune into. This is a key learning point for organizations who are trying to adapt to these new trends so that information and communication flows seamlessly across platforms. Primary issues that confront personalization at work are that of security and compliance. The basic format of monitoring then calls for a change with regard to protection of company information, compliance with non-disclosure and other such agreements. It is for each organization to weigh out whether the benefits of allowing a BYOS environment negate the risks. Engagement redefined There is a sizable percentage of employees today who would choose lifestyle perks over a bigger pay package. Such crucial changes in terms of workforce behavior have been instrumental in leading the thought renaissance that we see around the industry today. The modern employee wants his/her respective organizations to add more than financial value to their lives. Recognition, personal and career development, happiness and wellness, work-life balance are among the other aspects of work that are of mounting importance when it comes to engagement and retention. According to Forrester Research, Employee Experience Powers the Future of Work, 2017, besides being recognized for their effort at work, employees seek technology-driven experiential, immersive processes and tangible changes like personalizing benefits. The Hays US What People Want Survey conducted in 2017 revealed that 71% of the participants indicated that they would be keen to accept lower pay for a job that allowed greater role-alignment in terms of what their past experience, present needs and future plans. Furthermore, customizable benefits seem to have a direct and positive influence on employee loyalty as seen in the MetLife, 15th Annual U.S. Employee Benefit Trends Study, 2017. Predictive analytics: the crystal ball of behaviour? An analysis by LifeWorks, Taking Care: How to Develop and Support Today’s Employees, 2017, enumerates how organizations run the risk of losing quality workers if they fail to tweak their strategies in order to provide employee experiences that are personalized and truly engaging. That is where using the gifts of predictive analytics come into play. Employees are human and analyzing human behavior often poses difficulties due to its dynamism and the need to take into consideration individual differences. These data points not only help in tracking payroll, benefits enrollment or growth projection but also allow for the prediction of growth and longevity of an employee.   “If you had analytics that could help you predict the success of a candidate based on their past performances, their skill levels, their personality and their cultural fit it could paint a better picture of how they will fit into your company,” says Michael Fauscette, chief research officer for G2 Crowd. “If the analytics can predict the success of a candidate, then it could be a huge benefit to the hiring process, and if that fits, then it is a huge benefit to retaining an employee.” As with any technological incorporation at work, behavioural analytics too comes with its set of legal and ethical concerns since monitoring employee behaviour has its complexities and that needs to be acknowledged. It thus needs a certain level of employee education where all employees are made aware of how their data is being used and for what purposes. This would also help in analyzing legal repercussions better. Moreover, before the organization is enabled in making the shift, all levels of leadership and of the HR function must allow a permeation of personalization and predictive analytics. While the employee engagement space modifies, mutates and evolves, it would be interesting to witness the changes yet to come. Would companies continue to work towards it in retrospect with reactive methods or are we ready for intuitive, predictive and proactive moves?
    People Analytics
    2018年11月25日
  • People Analytics
    分析人士对价值80亿美元的SAP-Qualtrics收购交易进行了评估,认为这不会改变游戏规则 文/Ron Miller 今天,SAP首席执行官Bill McDermott因公司周末价值80亿美元的Qualtrics收购案而备受关注。McDermott相信Qualtrics提供的数据可以弥补公司运营数据和客户之间的差距,无论客户在哪里。 Qualtrics的理念是,要理解客户的情绪。McDermott认为,这是该公司客户管理难题的关键部分,它不仅可以推动该公司成为客户体验领域的重要参与者,还可以推动公司的基础云业务。这是因为它提供了一种来自客户的持续反馈的方式,而这种方式很难以其他方式确定。 在这种背景下,他认为这笔交易具有变革性。“通过将这些经验数据与操作相结合,我们可以通过Qualtrics和SAP将其结合起来,这是世界上从未有过的,我从根本上相信它将改变我们今天所知道的这个世界。” 其他密切关注该行业的人则不这么认为。虽然他们喜欢这笔交易,并看到了合并这些数据的潜力,但这可能不是麦克德莫特在花了80亿美元后所希望的游戏规则改变者。 保罗•格林伯格(Paul Greenberg)是56家集团的董事总经理,著有影响深远的CRM书籍《光速下的CRM》(CRM at The Light of Light)。他表示,对该公司来说,这无疑是一笔巨大的收购,但他表示,要挑战市场领导者,需要的不仅仅是一两次收购。格林伯格表示:“这将是一次有益的收购,因为SAP希望继续将公司转向面向客户的方向,但无论如何,这都不是一次决定性的收购。” 客户体验是一个宽泛的术语,它涉及到从细粒度层次上了解客户,预测他们想要什么,了解他们是谁,他们买了什么,以及他们正在寻找什么。这些问题比你想象的要难解决,特别是因为它们涉及到从不同供应商的系统收集数据,这些供应商处理不同的问题。 Adobe和Salesforce等公司已将这作为其主要业务重点。SAP的核心是ERP公司,通过管理财务、采购和人力资源等关键的内部运营系统来收集数据。 Real Story Group创始人兼首席分析师托尼•伯恩(Tony Byrne)表示,他喜欢Qualtrics对SAP的影响,但他不确定它是否像McDermott建议的那样重要。Qualtrics可以让你做一些营销人员肯定想要的更复杂的调查,但它的双重好处是——不像SurveyMonkey和其他公司——Qualtrics在数字化工作场所方面有经验,可以补充SAP的一些人力资源工具。但他补充说,这并不是CEM的核心部分,他的公司的研究发现SAP仍然存在漏洞,尤其是在营销工具和技术方面(MarTech)。 CRM Essentials创始人布伦特•利里(Brent Leary)同意SAP收购了一家不错的公司,尤其是在今年早些时候以24亿美元收购了CallidusCloud之后,但要赶上Salesforce和Adobe还有很长的路要走。Qualtrics的确提供了一个更广泛的客户视角,因为来自后台和前台系统的运营数据。Callidus的收购有助于将洞察力转化为某些以bb为中心的客户体验。但我认为,在B2C体验创建工具方面,可能还需要更多的东西,Adobe和Salesforce等公司正专注于营销/体验云。 McDermott认为,这是否会真正改变游戏规则还有待观察,但我们采访的行业专家认为,这将更多地是一项渐进式举措,有助于推进公司的客户体验计划。如果他们是对的,McDermott可能还没有完成购物。   以上为AI翻译,内容仅供参考。 原文链接: Analysts weighing in on $8B SAP-Qualtrics deal don’t see a game changer 相关阅读:SAP在调查软件公司Qualtrics上市之前,以80亿美元将其收购
    People Analytics
    2018年11月13日
  • People Analytics
    评估技术开发商Imbellus宣布获得1450万美元 A轮融资,目前已筹集2300万美元 据美通社2018年10月31日报道,基于模拟的评估技术开发商Imbellus宣布结束由Owl Ventures领导的1450万美元 A轮融资。该公司目前的总资金达到2300万美元,包括Upfront Ventures和Thrive Capital在内的先前投资者与Rethink Education一起参与了此次投资。 “Imbellus团队的成就代表了改善教育与就业生态系统评估的独特机会,” Owl Ventures的Ashley Bittner说。“这项工作对K-12系统的未来产生了影响。它是关于实现一种专注于解决问题,系统思考和创造力等技能的教育范式。” Imbellus不是将评估映射到大学的学术要求,而是与以创造力或解决问题等技能而闻名的组织合作,研究这些技能在现实世界中的应用。然后,Imbellus将观察到的技能和属性转化为学习科学和心理测量学的语言,以设计复杂的挑战,通过抽象的,基于模拟的评估将问题解决背景带入生活。 “我们正在努力将内容掌握与对潜在认知技能和能力的评估脱钩,以便不仅了解人们所知道的内容,还了解他们的思考方式,” Imbellus的创始人兼首席执行官Rebecca Kantar说。“我们的长期目标是重新定位教育系统,培养提出正确问题的思想,想象下一个要解决的问题,以及驾驭复杂系统。这是为了让所有学生都能做好公共教育的承诺,而不仅仅是对于最富有的10%。“ 自2016年推出以来,Imbellus的学习科学家,游戏开发人员,AI / ML工程师和心理测量学家团队与评估和评估最前沿的研究人员合作,包括国家评估,标准和学生测试研究中心(CRESST) )在加州大学洛杉矶分校。 “在我们发现自己陷入前所未有的混乱中,理解并准确衡量个人解决问题的无数方式对于更好地将人们与工作相匹配将变得越来越重要。在麦肯锡,了解人们如何思考对我们来说一直很重要,而不仅仅是他们所知道的,“ Keith McNulty说麦肯锡公司数字与人力分析总监,自2017年起与Imbellus合作,将其数字化,基于情景的评估作为招聘和招聘流程的一部分进行试点。“Imbellus”技术正在帮助我们将案例研究访谈的原则扩展到更广泛的人才,提供引人入胜的体验,使他们能够解决我们所解决的问题,同时向我们提供有关他们如何思考的准确而详细的信息关于问题。“ Imbellus评估不是评估内容知识和有限的学习技能,而是利用自然世界模拟环境中的多步骤丰富场景。与专注于工作记忆,处理速度或思维流动性的智商测试或神经科学游戏不同,Imbellus评估旨在量化将人类智能与机器智能区分开来的技能,例如批判性思维,决策制定和元认知。 。 支持Imbellus评估的技术平台通过使用虚拟世界来防止作弊和黑客攻击,该虚拟世界利用AI为测试者生成不断变化的场景,以完成任务,具有可靠的可比性。   以上为AI翻译,内容仅供参考。 原文链接:Imbellus Raises $23 million to Take on the Testing Establishment
    People Analytics
    2018年11月03日
  • People Analytics
    人力资源分析战略对高绩效企业至关重要的3个原因 文/ Chiradeep BasuMallick 工敬业度和生产力正在发生变化。随着您的员工在多个平台上分享意见,评论和评论,大量数据量涌入其中,充满了丰富的见解。拥有强大的人力资源分析战略可以帮助衡量绩效,调整劳动力管理蓝图,并将雇主推向更高的高度。 如今,全球各地的企业都在使用人力资源分析。对于高绩效雇主而言,智能人力资源分析战略可以带来几项总体优势,同时提高投资回报率。那么人力资源分析如何真正发挥作用,以及它对企业盈利的真正影响是什么? 我们分享了关于良好表达的人力资源分析战略影响的5个原理说明。 提高招聘精度 招聘仍然是公司的一个重要领域,充满了几个波动的挑战。人力资源分析战略可以帮助您查看以前的决策和方法,改进方法,并使招聘更符合特定要求。通过消除浪费在无用应用程序上的时间并专注于真正重要的连接,这使得该过程更快。 提高员工保留率 高员工流动率是现代企业的另一个问题。通过强大的人力资源分析战略,您可以确定员工离开公司的原因,让您重新考虑保留策略。它甚至可以检测员工脱离,这是保留的一个重要区别。 从IBM的案例中汲取灵感:Big Blue利用他们的人力资源分析战略来实时了解员工敬业度。通过分析员工之间的社交媒体数据使用情况,发现可以事先获得48%的员工参与度分数变异性。IBM开发了Social Pulse,一种“社交媒体情绪”工具,作为回应,并创建了一个基于数据的渠道来听取员工的声音。 通过评估员工流失数据,进行离职面谈和满意度调查,您的人力资源分析战略必须超越数字,并明确了解对企业有用的内容以及需要修复的内容。这最终降低了雇用新员工以取代一连串退出的成本,从而提高了底线。 释放人类潜能 招聘,维护和培养表现最佳的人才是整体企业生产力不可或缺的一部分。人力资源分析策略应该旨在消除混乱,并提供关于员工工作记录,满意度,产出以及参与项目或目标的关键见解。 因此,最值得尊敬的员工得到奖励和认可,参与度最佳,个人有能力发挥自己的最大潜能,并改善对公司核心目标的贡献。 SAP SuccessFactors人力资本管理研究高级副总裁Steven Hunt博士在与HR技术专家的对话中说。“在金融危机之后,一家大公司不得不迅速降低总劳动力成本。高级领导人获得了显示不同部门薪资和员工人数的电子表格。 他们确定了一个团队正在研究一种新的但非关键的产品,这种产品的劳动力成本相对较高。但领导者从未查看过显示团队成员能力的数据。 在让团队离开后不久,该公司发现它已经淘汰了几位技术娴熟的工程师。几个月后,该公司不得不重新聘用这些员工担任顾问,其费率远高于他们作为全职员工的薪酬。他们对公司承诺的感觉已经丧失。 这些领导者是聪明的人,他们以错误的方式解释准确的数据并盲目做出决定。他们缺乏的是充分了解其决策背景及其影响的额外数据,无论是积极的还是消极的。 使用人力资源数据的部分技术是以引导人们得出适当见解和结论的方式呈现它。这是关于在正确的背景下提供数据以及有效的分析解释。   总结 在数据是真正的变革代理的情况下,人力资源分析战略可以完全改变您的雇佣方式,员工的承认方式,评估价值和生产力的方式,最后使产出和盈利能力更加精简。所需要的只是实用和个性化的应用。   以上为AI翻译,内容仅供参考。 原文链接:3 Reasons Why an HR Analytics Strategy is Essential for High Performance Companies
    People Analytics
    2018年10月22日
  • 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