【HR术语】什么是预测性人力资源分析？（What is predictive HR analytics?）
什么是预测性人力资源分析？
预测性人力资源分析是人力资源部门用来分析过去和现在的数据以预测未来结果的一种技术工具。预测性人力资源分析以数字化方式挖掘数据，提取、剖析和归类信息，然后识别模式、不规则性和相关性。通过统计分析和预测建模，分析可实现有关人力资源职能的数据驱动决策。
预测性人力资源分析系统让人想起蚯蚓。蚯蚓吸收天然废料和残渣，排出营养丰富的肥沃土壤。预测性分析也是如此，它吸收未使用的原始数据，并将其转化为适用的信息，为更明智的业务决策提供支持。
人力资源预测分析实例
以下是当今组织如何应用人力资本预测分析的一些示例：
招聘。预测分析可帮助人力资源专业人员确定最有效的顶尖人才来源。通过分析成功招聘的历史数据，企业可以将招聘工作重点放在能产生最佳效果的平台和渠道上。
留住员工。预测模型可以分析员工数据，如绩效考核、缺勤率和任期，以识别有离职风险的员工。这样，人力资源部门就可以采取积极措施，如提供职业发展机会或解决工作场所的问题，留住有价值的人才。
劳动力规划。预测分析可以通过考虑退休率、人员流动和新兴行业趋势等因素，预测公司未来的技能缺口。然后，人力资源部门可以制定培训和发展计划，弥补这些差距，确保员工队伍保持竞争力。
员工绩效管理。预测性人力资源分析可根据历史绩效数据预测团队成员的未来绩效。这有助于人力资源团队识别可能成为关键职位潜在接班人的高绩效人员，并帮助他们发现其他人可能落后的原因。
员工参与和福利。预测分析能够发现影响员工敬业度的问题。人力资源专业人员可以通过监控工作量和工作时间等因素，识别可能面临职业倦怠或其他心理健康问题风险的人员。然后，人力资源部门可以为有需要的人提供有针对性的支持和资源。
预测性分析如何帮助人力资源部门？
预测性人力资源分析可以帮助组织预测挑战，从而可以：
避免风险
减少人为错误
预测将在组织中茁壮成长的典型员工情况
加强招聘实践
鼓励实现最佳工作绩效
最终，预测性人力资源分析可帮助人力资源领导者做出清晰明确的决策，从而增加整体利润，提高员工的积极性、忠诚度、参与度和工作效率。
预测性和描述性人力资源分析有何不同？
描述性人力资源分析包括检查历史人力资源数据，以全面了解组织内发生了什么及其原因。
而预测性人力资源分析则不局限于此，而是通过分析历史数据和过去的趋势来预测未来会发生什么，从而使组织有机会采取预防措施或抓住出现的机遇。同时使用预测性和描述性两种人员分析形式的组织，都能为自己带来最大的影响。
如何成功实施预测性人力资源分析系统？
人力资源领导者可以利用以下技巧率先实施有效的预测性人力资源分析：
确定业务目标。人力资源领导者可以与团队合作，确定公司的长期目标，团队成员也可以帮助确定支持实现这些目标的相关指标。
确保透彻理解。预测性人力资源分析是一个复杂的领域，不熟悉数据科学的人力资源专业人员可能会对此感到畏惧。然而，为整个人力资源团队提供一致且多样化的学习选择，可以减轻他们对这一主题的不适感，加深理解，并鼓励员工持续发展。方法之一是鼓励人力资源团队熟悉每种分析算法的基本推理。人力资源部门还可以让数据科学家或人力资源数据分析师参与进来，以确保预测分析流程的最佳运作。
解决道德问题。为了避免对员工的不公平歧视待遇，预测分析团队可以预先防范可能出现的道德问题。公司可能会有意或无意地虐待员工中的特定人群，或者由于不正当的数据驱动推理而偏袒某些团队成员。因此，透明地遵守公司的行为准则和人力资源道德准则至关重要。员工需要知道他们的雇主是公平对待他们的，这样他们才会有参与感，才会有茁壮成长的动力。
利用预测分析的力量。人力资源领导者可以通过将预测分析应用于特定目标，最大限度地发挥其作用。例如，人力资源领导者可以结合预测分析来设计有效的职业发展计划，以解决能力差距和未来的能力需求问题，从而按照员工所希望的学习轨迹对其进行培训。
预测性人力资源分析如何改善企业文化？
预测性人力资源分析提供了一种方法，可帮助领导者做出明智的决策，从而培养一支充满热情和高绩效的员工队伍。有效、合乎道德地使用人力资源分析，可以使公司有能力识别、雇佣、吸引和留住符合公司文化并乐于为公司发展做出贡献的高素质专业人才。
为企业选择合适的预测性人力资源分析工具
选择合适的人员分析软件是人力资源专业人士和企业必须迈出的关键一步，这样他们才能收获人力资源预测分析的所有回报。
工具的选择应符合具体的业务需求、资源和目标。要做出明智的决定，有几个关键点需要牢记：
集成。工具能否与现有人力资源系统无缝集成？兼容性和数据传输的便捷性对于准确的预测建模至关重要。
可扩展性。合适的工具能够随着企业的扩张而扩展人力资源预测分析工作。
用户友好界面。寻找能够提供直观的仪表盘、可视化和报告功能的工具，使人力资源专业人员能够轻松访问和解释洞察力。
可解释性。确保工具对其预测做出解释。这样，您的人力资源团队就能理解为什么会做出某些预测，并采取适当的行动。
数据安全性和合规性。人力资源数据通常包括敏感和机密信息。确保工具遵守数据隐私法规，并有保护数据的安全措施。
支持和培训。考虑工具供应商提供的支持和培训水平。充分的培训和持续的支持对人力资源团队有效使用工具并最大限度地发挥其优势至关重要。
成本和投资回报率。评估总体拥有成本，包括许可费用、实施成本和持续维护费用。通过估算工具的洞察力如何对人力资源成果和组织绩效产生积极影响，计算潜在的投资回报。
用户反馈和评论。向使用过该工具的人力资源专业人士征求反馈意见，并阅读行业内其他组织的评论。他们的经验可以为了解工具的优缺点提供宝贵的见解。
通过仔细考虑这些因素，您可以为您的人力资源团队提供一个预测性劳动力分析工具，从而增强决策能力，推动人力资源战略，促进整体业务成功。
以下为文章原文：
What is predictive HR analytics?
Predictive HR analytics is a tech tool that HR uses to analyze past and present data to forecast future outcomes. Predictive HR analytics digitally digs through data to extract, dissect, and categorize information and then identify patterns, irregularities, and correlations. Through statistical analysis and predictive modeling, analytics enables data-driven decisions regarding HR functions.
Predictive HR analytics systems are reminiscent of the earthworm. The worm ingests natural waste material and residue and excretes nutrient-rich, fertile soil. Predictive analytics, too, intakes unused, raw data and transforms it into applicable information that supports wiser business decisions.
Predictive HR analytics examples
Here are some examples of how organizations today apply human capital predictive analytics:
Recruitment. Predictive analytics helps HR professionals identify the most effective sources of top talent. By analyzing historical data on successful hires, organizations can focus their recruitment efforts on the platforms and channels that yield the best results.
Employee retention. Predictive models can analyze employee data, such as performance reviews, absenteeism, and tenure, to identify people at risk of leaving the company. This allows HR to take proactive measures, such as offering career development opportunities or addressing workplace concerns, to retain valuable talent.
Workforce planning. Predictive analytics can forecast future skill gaps within a company by considering factors like retirement rates, turnover, and emerging industry trends. HR can then develop training and development programs to fill these gaps and ensure the workforce remains competitive.
Employee performance management. Predictive HR analytics can forecast a team member’s future performance based on historical performance data. This helps the HR team identify high-performing people who could be potential successors for critical roles, and can help them discover why others may be lagging behind.
Employee engagement and wellbeing. Predictive analytics has the ability to uncover issues that affect employee engagement. HR professionals can identify people who may be at risk of burnout or other mental health issues by monitoring factors like workload and working hours. HR can then provide targeted support and resources to those in need.
How does predictive analytics help human resources?
Predictive HR analytics assists organizations in anticipating challenges so they can:
Avoid risk
Reduce human error
Forecast the typical employee profile that’ll thrive in the organization
Enhance recruitment practices
Encourage optimal work performance
Ultimately, predictive HR analytics helps HR leaders make crystal-clear decisions that can increase overall profit and nurture employee motivation, retention, engagement, and productivity.
What is the difference between predictive and descriptive HR analytics?
Descriptive HR analytics involves examining historical HR data to get a thorough understanding of what has happened within an organization and why.
Predictive HR analytics, on the other hand, goes beyond this and analyzes historical data and past trends to predict what will happen in the future—giving an organization the chance to take preventive measures or to seize opportunities as they arise. Organizations that use both predictive and descriptive forms of people analytics set themselves up to achieve the greatest impact.
How do you implement a successful predictive HR analytics system?
HR leaders can spearhead effective predictive HR analytics using the following tips:
Define business objectives. HR leaders can collaborate with their teams to identify long-term company goals, with team members also helping determine the relevant metrics that support the achievement of these objectives.
Ensure a thorough understanding. Predictive HR analytics is a complex field, and HR professionals unfamiliar with data science can feel intimidated by it. However, providing consistent and diverse learning options for your entire HR team can mitigate their discomfort with the subject, elevate understanding, and encourage continual employee development. One way to do this is to encourage your HR team to familiarize themselves with the fundamental reasoning driving each analytics algorithm. HR can also involve a data scientist or bring an HR data analyst on board to ensure optimal functioning of the predictive analytics process.
Address ethical considerations. To avoid unfair discriminatory treatment of employees, predictive analytics teams can pre-empt possible ethical issues that may arise. Companies could intentionally or unintentionally mistreat specific demographics within the workforce or perhaps show favoritism to certain team members due to illegitimate data-driven reasoning. Thus, transparently adhering to the company’s code of conduct and the HR code of ethics is paramount. People need to know that their employers are treating them fairly to feel engaged and motivated to thrive.
Harness the power of predictive analytics. HR leaders can maximize predictive analytics by applying it to specific objectives. For example, HR leaders can incorporate predictive analytics to design an effective career development program that addresses competency gaps and future competency needs, allowing them to train people in their desired learning trajectory.
How can predictive HR analytics improve company culture?
Predictive HR analytics offers a way to help leaders make informed decisions that nurture an enthusiastic and high-performing workforce. Effective and ethical use of HR analytics can empower companies to identify, hire, engage, and retain quality professionals who align with the company culture and are excited to contribute to its growth.
Choosing the right predictive HR analytics tool for your business
Selecting the right people analytics software is a crucial step for HR professionals and organizations to take, so that they’re able to reap all the rewards of HR predictive analytics.
The choice of tool should align with specific business needs, resources, and objectives. There are a few key things to keep in mind to be able to make an informed decision:
Integration. Can the tool seamlessly integrate with your existing HR systems? Compatibility and ease of data transfer are essential for accurate predictive modeling.
Scalability. The right tool will be able to expand your predictive HR analytics efforts as your organization expands.
User-friendly interface. Look for tools that offer intuitive dashboards, visualizations, and reporting features, making it easy for HR professionals to access and interpret insights.
Explainability. Ensure that the tool provides explanations for its predictions. That way, your HR team can understand why certain predictions are made and take appropriate actions.
Data security and compliance. HR data often includes sensitive and confidential information. Make sure the tool adheres to data privacy regulations and has security measures to protect your data.
Support and training. Consider the level of support and training provided by the tool’s vendor. Adequate training and ongoing support are essential for HR teams to effectively use the tool and maximize its benefits.
Cost and ROI. Evaluate the total cost of ownership, including licensing fees, implementation costs, and ongoing maintenance expenses. Calculate the potential return on investment by estimating how the tool’s insights can positively impact HR outcomes and organizational performance.
User feedback and reviews. Seek feedback from HR professionals who have used the tool and read reviews from other organizations in your industry. Their experiences can provide valuable insights into the tool’s strengths and weaknesses.
By carefully considering these factors, you can empower your HR team with a predictive workforce analytics tool that enhances decision-making, drives HR strategies, and contributes to overall business success.
改善企业文化
2024年03月05日
改善企业文化
【HR术语】什么是人力分析？（What is people analytics?）
什么是人力分析？
人力分析是一种以数据为导向的方法，旨在改进有关团队成员和客户的业务决策。人力分析并不完全依赖直觉或传闻经验，而是为人力资源领导者提供全面的数据，以做出有据可依的战略决策。
人力分析整合了人力资源信息系统软件，以收集和检查大量信息，预测趋势，并提供与员工生命周期不同阶段相关的宝贵见解。人力分析也被称为人才分析，公司利用人力分析将合适的人才匹配到合适的岗位上。
人力分析为何重要？
人力分析可对数据进行评估，以加强以下方面的工作：
招聘和录用
入职培训
劳动力规划
薪酬实践
留住人才
绩效
生产力
参与
不仅仅是人力资源部门，所有部门都开始采用人才分析功能。这种转变预示着人力资源自动化程度的提高： 人力资源领导者必须做好迎接这些变化的准备，以提供最新、准确的结果。
利用人力资源自动化工具，人力资源领导者可以做出明智的决策，提升员工体验，促进公司目标的实现。在竞争激烈、不进则退的市场中，人力资源领导者必须表现出灵活性，不断适应工作场所的创新。
人力分析实例
人力资源中的人力分析包括员工生命周期的各个方面。人力分析的例子包括:
流失预测。这包括分析历史数据，找出导致团队成员流失的模式和因素，使您有能力预测哪些员工有离职风险。
招聘优化。人力分析有助于改进招聘方法，以吸引和留住顶尖人才。
绩效分析。这包括评估关键绩效指标（KPI）、目标实现情况和能力评估等绩效数据，以获得有助于识别高绩效人才及其成功因素的见解。
员工参与度。调查数据和情感分析有助于深入了解员工满意度、敬业度以及影响因素。这些信息有助于组织设计提高员工敬业度的措施，并创造更加积极的工作环境。
学习与发展。分析可追踪培训成果、技能掌握情况以及教育计划带来的绩效提升，帮助您优化与业务目标相一致的培训投资。
关键人员分析指标
早期离职率。该指标指的是在公司工作第一年内离职的人员比例。它有助于评估留住人才的努力。
缺勤率。这衡量的是一个人意外缺勤的频率，无论是由于疾病、压力还是其他个人原因。团队成员缺勤率高，说明对工作场所不满意。
参与度得分。这些分数反映了员工对工作和整个组织的投入程度和满意度。
绩效评级。根据预定指标和目标对个人或团队的绩效进行评估。
每次招聘成本。评估招聘流程的总成本，包括广告、面试和入职成本。
如何利用人力分析做出决策
人力资源人力分析的有效性取决于将从数据中获得的见解付诸行动。以下步骤将帮助您为组织做出清晰、明智的决策：
确定目标。明确概述您打算利用人力分析来应对的具体组织挑战。
收集数据。从人力资源信息系统（HRIS）或人力资源管理系统（HCM）、绩效考核、调查及其他来源收集相关数据。
分析。采用统计方法、可视化工具或人力分析平台，从收集的数据中得出有意义的见解。
识别模式。从数据中寻找相关性和趋势，从而深入了解员工行为和组织面临挑战的原因。
做出明智决策。利用从数据中收集到的洞察力，做出有据可依的决策，帮助组织实现其目标。
人力分析仪表盘
人力分析仪表盘是关键人力资源指标和数据的可视化呈现。它提供的关键信息一目了然，如离职率、参与度评分、绩效数据和招聘统计数据。
仪表盘使人力资源领导和管理人员能够跟踪和了解劳动力指标，从而轻松做出明智的决策。用户友好、信息丰富的仪表盘可让利益相关者迅速访问和解释重要数据，而无需完全依赖 IT 部门或分析师。
如何成功实施人才分析系统
将人才分析纳入多个部门需要人力资源领导者挺身而出，指导他人完成这项新举措。人力资源领导者可以通过实施这些做法来支持人员分析的整合：
以身作则。展示对人才分析的熟练程度，或至少是对人才分析的理解，可以让人力资源领导者有效地使用人才分析，并在其他人学习的过程中为他们树立榜样。
观察。人力资源领导者可以确定其组织目前进行的数据收集水平，并注意公司目前使用的数据分析方法，如数据收集技术和类别，以及哪些人力资源领导者对数据负责。
向所有人力资源专业人员介绍人力分析。为所有人力资源人员提供人员分析 "基础培训"，可以提高他们对系统的认识。让人力资源专业人员熟悉人员分析，可以增强他们的能力，同时将这种方法融入公司文化和思维模式。
培训分析团队。教育人力分析专家如何阅读和仔细检查数据、警惕不准确的数据并做出基于数据的决策，这一点非常重要。这些人力资源专业人员决定着人才分析系统的有效性。
注意潜在隐患。公司可以利用人力资源信息系统平台简化、过滤数据，并以易于理解的方式将数据呈现给管理人员。另一个需要注意的挑战是通过数据加密和遵守诚实、公平和透明的政策来保护员工的隐私。
人力分析与人力资源分析
专业人士会交替使用 "人员分析 "和 "人力资源分析 "这两个术语。然而，两者之间是有区别的：
人力资源分析侧重于利用人力资源部门的数据来了解和管理员工。它深入研究团队成员的个人行为、绩效和参与度，旨在优化员工生命周期中的各种人力资源流程。
虽然人员分析也使用人力资源数据，但其关注点超出了这一范围，而是扩展到整个组织中更广泛的数据源，如整体业务绩效、财务、市场营销和销售。它收集更广泛的数据，以获得更深入的见解，为战略决策提供依据。
人力分析趋势
企业接受人员分析的程度以及使用人员分析的方式正在发生变化：
关注员工体验。现在的趋势是改善员工的整体旅程，强调健康和富有成效的远程工作体验等方面。
合乎道德的数据使用。随着人们对数据隐私的日益关注，数据使用的道德考量以及保持数据收集和分析的透明度将受到更多重视。
平台整合。人员分析工具将整合来自企业不同软件和应用程序的数据，从而更容易从单一来源获得所有必要的见解。
多样性、公平性和包容性。人们越来越重视利用人员分析来提高组织内部的多样性、公平性和包容性，而且这种情况只会继续增加。
人工智能集成。人力分析平台开始整合人工智能驱动的工具，以简化数据分析，并从复杂的数据集中获得更深入的见解。
人力分析如何改善企业文化？
人力分析为人力资源领导者、经理和高管提供数据支持，使员工绩效与公司目标保持一致。对这些数据进行有效评估并采取行动，有助于制定有效的招聘和培训策略、提高员工参与度，进而促进公司文化的发展。
以下为文章原文：
What is people analytics?
People analytics is a data-driven method that aims to improve business decisions regarding team members and customers. Rather than solely relying on instinct or anecdotal experience, people analytics provides HR leaders with comprehensive data to make evidence-based, strategic decisions.
People analytics integrates HRIS software to assemble and examine extensive information, predict trends, and provide valuable insights relating to the different stages of the employee lifecycle. Also known as talent analytics, companies use people analytics to match the right talent to appropriate roles.
Why is people analytics important?
People analytics assesses data to enhance the following areas:
Recruiting and hiring
Onboarding
Workforce planning
Compensation practices
Retention
Performance
Productivity
Engagement
Talent analytics is a function that all departments, not just HR, are beginning to adopt. This is a transformation that heralds an increase in HR automation: HR leaders must be ready to embrace these changes to deliver up-to-date, accurate results.
Leveraging HR automation tools enables HR leaders to make informed decisions that elevate the employee experience and promote company objectives. In a competitive, sink-or-swim market, HR leaders must demonstrate agility as they continuously adapt to innovations within the workplace.
Examples of people analytics
People analytics in HR encompasses various aspects of the employee lifecycle. Examples of people analytics include:
Attrition prediction. This involves analyzing historical data to identify patterns and factors leading to team member turnover, giving you the ability to predict which of your people are at risk of leaving.
Recruitment optimization. People analytics can help with refining recruitment approaches to attract and retain top talent.
Performance analysis. This involves evaluating performance data such as key performance indicators (KPIs), goal achievement, and competency assessments to gain insights that aid in identifying high-performing individuals along with the factors that contribute to their success.
Employee engagement. Survey data and sentiment analysis provide insights into employee satisfaction, engagement levels, and the factors influencing them. This information helps organizations design initiatives to improve engagement and create a more positive work environment.
Learning and development. Analytics can track training outcomes, skill acquisition, and performance improvements resulting from educational programs, helping you optimize training investments that align with business goals.
Key people analytics metrics
Early turnover rate. This metric refers to the percentage of people leaving within the first year of working at a company. It helps with assessing retention efforts.
Absence rate. This measures how often a person is unexpectedly absent from work, whether that’s due to sickness, stress, or other personal circumstances. A high absence rate among team members can indicate dissatisfaction in the workplace.
Engagement scores. These capture how committed and satisfied people are about their work and the organization as a whole.
Performance ratings. These evaluate individual or team performance against predefined metrics and goals.
Cost per hire. This assesses the total expenses of the hiring process, including advertising, interviewing, and onboarding costs.
How to use people analytics to make decisions
The effectiveness of HR people analytics depends on putting the insights gleaned from data into action. The steps below will help you make clear and knowledgeable decisions for your organization:
Define objectives. Clearly outline the specific organizational challenges you aim to address using people analytics.
Data collection. Gather relevant data from your HRIS or HCM, performance reviews, surveys, and other sources.
Analysis. Employ statistical methods, visualization tools, or a people analytics platform to draw meaningful insights from the collected data.
Identify patterns. Look for correlations and trends in the data that offer insights into workforce behaviors and the causes of your organization’s challenges.
Make informed decisions. Use the insights you’ve gathered from the data to make evidence-based decisions that help your organization reach its objectives.
People analytics dashboard
A people analytics dashboard is a visual representation of key HR metrics and data. It provides critical information at a glance, such as turnover rates, engagement scores, performance data, and recruitment statistics.
A dashboard empowers HR leaders and managers to track and understand workforce metrics so they can easily make informed decisions. A user-friendly and informative dashboard allows stakeholders to access and interpret essential data swiftly without having to rely exclusively on an IT department or analyst.
How to successfully implement a people analytics system
Incorporating talent analytics into multiple departments demands that HR leaders step up to guide others through this new initiative. HR leaders can support the integration of people analytics by implementing these practices:
Lead by example. Demonstrating proficiency in, or at least an understanding of, people analytics allows HR leaders to use it effectively and set an example for others as they learn the ropes.
Observe. HR leaders can identify the level of data collection they currently conduct at their organization and take note of the prevailing data analysis methods the company uses, e.g., data collection techniques and categories and which HR leaders are accountable for the data.
Introduce all HR professionals to people analytics. Providing people analytics “basic training” for all HR personnel will improve their knowledge of the system. Acquainting HR professionals with people analytics empowers them while infusing this method into the company culture and mindset.
Train the analytics team. It’s important to educate people analytics specialists on how to read and scrutinize data, watch out for inaccurate data, and make data-informed decisions. These HR professionals determine the effectiveness of the talent analytics system.
Be aware of potential pitfalls. Companies can use an HRIS platform to simplify, filter, and present the data in a digestible manner to managers. Another challenge to be mindful of is the essential protection of people’s privacy through data encryption and adherence to an honest, fair, and transparent policy.
People analytics vs HR analytics
Professionals use the terms “people analytics” and “HR analytics” interchangeably. However, there’s a difference between the two:
HR analytics focuses on leveraging the HR department’s data to understand and manage the workforce. It delves into individual team members’ behaviors, performance, and engagement, aiming to optimize various HR processes across the employee lifecycle.
While people analytics also uses HR data, its focus extends beyond this to wider data sources across the organization, such as overall business performance, finance, marketing, and sales. It gathers a broader spectrum of data to gain deeper insights that inform strategic decisions.
People analytics trends
The extent to which organizations embrace people analytics and the ways they use it are already changing:
Focus on employee experience. There’s a shift toward improving the overall employee journey, emphasizing aspects like wellness and productive remote work experiences.
Ethical data use. With the increased concern around data privacy, there’ll be greater emphasis on ethical considerations around data usage and maintaining transparency in data collection and analysis.
Platform integration. People analytics tools will integrate data from an organization’s different software and apps to make it easier to get all the necessary insights from a single source.
Diversity, equity, and inclusion. There’s a greater focus on using people analytics to improve diversity, equity, and inclusion within organizations and this will only continue to grow.
AI integration. People analytics platforms are starting to integrate AI-driven tools to streamline data analysis and derive deeper insights from complex data sets.
How can people analytics improve company culture?
People analytics provides HR leaders, managers, and executives with data to support the alignment of employee performance with company objectives. Effectively assessing and acting on this data contributes to effective hiring and training tactics, employee engagement, and in turn, a robust company culture.
改善企业文化
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