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
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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.
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.
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