【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.
数字化
2024年03月05日
数字化
【伦敦】创新数字健康平台 Vitrue Health 完成了400万美元的融资
在推动职场健康方面迈出重要步伐的同时，伦敦的创新数字健康平台 Vitrue Health 最近宣布，成功完成了400万美元的融资。这次资金的增加，将公司总融资额提升至700万美元，标志着该公司在打击职场肌肉骨骼问题（MSK disorders）方面迈出了关键一步。
Vitrue Health 以其针对普遍存在且因混合式和远程工作模式日益严重的肌肉骨骼健康（MSK health）问题的创新方法，在健康科技领域脱颖而出。该公司的数字平台 Vitrue VIDA，采用最前沿的计算机视觉和生物力学分析技术，提供个性化、基于数据的健康评估，旨在不仅减轻肌肉骨骼疼痛，还确保远程、办公室及混合型团队符合显示屏设备（DSE）健康标准。
近期的融资轮由行业领导者 MC Ventures 和 Hambro Perks 领投，同时得到了 Simplyhealth Ventures、Crista Galli Ventures 以及科技创业者 Chris Bruce 的重要支持，这反映了市场对 Vitrue Health 使命和技术实力的高度认可。这笔新资金将被用于实施雄心勃勃的扩展战略，计划扩大团队并将服务推广到美国和欧洲。
在 CEO Shane Lowe 的领导下，Vitrue Health 不仅是一家公司，它更象征着朝着更健康、更高效的劳动力前进的运动。通过着眼于解决肌肉骨骼不适的根源，该平台正彻底改变企业如何关注员工健康与安全。这一策略已经获得了包括 Bupa、NHS、Hastings Direct 和 Campari 等著名机构的信任，证明了平台的有效性和扩展能力。
在全球工作方式趋向更加灵活的今天，Vitrue Health 的解决方案变得尤为重要。该公司致力于利用科技改善职场健康，这一承诺展示了创新在促进更安全、更舒适和更高效的工作环境方面的巨大潜力。
随着 Vitrue Health 的不断发展和进步，它的旅程成为了在持续对抗职场相关健康问题中，希望与创新的象征。这家开拓者公司的未来前景光明，因为它正引领着全球企业将肌肉骨骼健康作为重中之重。
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