【HR术语】什么是工资级别？（What are salary bands?）
什么是工资级别？
薪带，又称薪酬范围或薪级表，是特定工作职位的薪酬范围。企业将其作为薪酬管理策略的一部分。
这些薪带定义了特定类别中职位的最低和最高薪酬水平，在定义的范围内为薪酬决策提供了灵活性--这样，招聘团队就可以选择薪带的穿透水平。
薪资范围通过透明度建立员工信任，也有助于吸引和留住优秀人才。
薪资范围有哪些示例？
以下是一些薪资范围的示例：
使用薪级的利弊
使用薪带可能是一把双刃剑。虽然它们有很多好处，但也会带来一些弊端：
如何创建薪带？
创建薪带涉及几个步骤：
工作评估： 评估组织内每个职位的职责和要求
市场调研： 通过薪资调查和行业报告收集市场数据，了解类似工作的平均薪资水平
确定薪酬范围： 根据职位评估和市场调研结果，制定与组织制定的薪酬管理目标相一致的薪酬范围
确定薪酬进展： 根据经验和绩效等因素，勾画出薪资范围内的薪资晋升空间
沟通和实施： 向员工明确传达新的薪带结构，并开始实施
薪资段和职位等级有什么区别？
薪带是适用于某一特定职位、多个职位或职位系列的广泛薪酬范围。它们为在规定范围内设定个人薪酬提供了灵活性。
而职位等级则是根据类似职位的价值和对组织的贡献进行分组。每个职位等级都有一个与之相关的特定薪资段，同一等级内的所有职位都有相同的薪资范围。
有哪些薪带最佳实践？
薪资范围并不是设定后就可以忘掉的。为了确保薪带保持有效，有一些最佳做法需要牢记：
定期审查： 定期审查和更新薪带，以保持在就业市场上的竞争力
数据第一：根据工作评估和市场调研的数据来决定薪资段，以保持准确和公平
灵活性： 在薪资段内留有一定的灵活性，以考虑到表现优异者，从而给予他们适当的奖励
沟通： 向所有团队成员明确传达薪酬等级，确保透明度
人力资源技术如何帮助维护薪级？
有效维护薪级可能会给你增加很多工作。但幸运的是，人力资源技术可以提供帮助。
您可以使用薪酬管理软件来轻松管理和跟踪薪级。人力资源技术还可以与薪资调查数据库整合，这样就可以确保薪资范围与最新信息保持一致，并保持竞争力。
这样，您就能继续吸引和留住优秀人才。
在薪酬方面，人力资源技术还可以帮助你关注公平性。某些工具可以生成关于薪资段分布和薪酬趋势的报告和分析，这样你就可以确保每个人都能获得公平的薪酬。
人力资源技术还能让确定奖励和晋升人选变得更容易。您可以将绩效管理系统与薪酬数据整合起来，将薪酬进步与员工绩效挂钩。
遵循上述最佳实践，并充分利用人力资源技术，可以帮助你维持公平的薪资段，并成为有竞争力的薪酬计划的一部分--促进公平并吸引最优秀的人才加入你的公司。
以下为文章原文：
What are salary bands?
Salary bands, also known as pay ranges or pay scales, are ranges of salaries for specific job positions. Organizations use them as part of their compensation management strategy.
These bands define the minimum and maximum compensation levels for jobs in a particular category, giving flexibility within a defined range for salary decisions—so that the hiring team can then choose the level of salary range penetration.
Salary bands build employee trust through transparency and can also help attract and keep talented people.
What are some examples of salary bands?
Here are some examples of what salary bands tend to look like:
Advantages and disadvantages of using salary bands
Using salary bands can be a double-edged sword. While they come with a whole host of benefits, they can also bring some disadvantages:
How can you create salary bands?
Creating salary bands involves several steps:
Job evaluation: Evaluate the responsibilities and requirements of each job position within the organization
Market research: Gather market data through salary surveys and industry reports to discover average pay rates for similar jobs
Establish salary ranges: Based on the job evaluation and market research, set salary ranges that align with the objectives of compensation management outlined by your organization
Define pay progression: Outline the pay progression within the salary bands based on factors such as experience and performance
Communicate and implement: Clearly communicate the new salary band structure to your people and start putting it in place
What’s the difference between salary bands and job grades?
Salary bands are broad ranges of compensation that apply to a particular job, multiple job positions, or job families. They offer flexibility for setting individual salaries within a defined range.
Job grades, on the other hand, group similar jobs based on their value and contribution to the organization. Each job grade has a specific salary band associated with it, and all positions within the same grade receive the same salary range.
What are some salary band best practices?
Salary bands aren’t just something that you can set and forget. To make sure they stay effective, there are a few best practices to keep in mind:
Regular reviews: Regularly review and update salary bands to stay competitive in the job market
Data first: Base salary band decisions on data from job evaluations and market research to keep them accurate and fair
Flexibility: Allow for some flexibility within the salary bands to account for exceptional performers, so you can reward them appropriately
Communication: Clearly communicate the salary bands to all team members, ensuring transparency
How can HR tech help maintain salary bands?
Effectively maintaining salary bands can add a lot of work to your plate. But luckily, HR technology can help.
You can use compensation management software to administer and track salary bands easily. HR tech can also integrate with salary survey databases, so you can make sure your salary bands are updated with the latest information and remain competitive.
That way, you’ll continue to attract and retain talented people.
HR tech can also help you keep an eye on equity when it comes to compensation. Certain tools can generate reports and analytics on salary band distribution and compensation trends, so you can make sure everyone gets their fair share.
HR tech can also make it easier to identify who to reward and promote. You can integrate performance management systems with compensation data to link pay progression to employee performance.
Following the best practices outlined above, along with making the most of HR tech, can help you maintain salary bands that are fair and part of a competitive compensation plan—promoting equity and attracting the best of the best to your company.
【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.
资讯
2024年03月05日
资讯
【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。
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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。
【HR术语】什么是学习管理系统？（What is a learning management system?）
什么是学习管理系统？
学习管理系统（LMS）是公司用来培训和教育员工、客户和业务伙伴的一种软件。传统的工作培训计划需要亲自参加，耗时数小时或数天。但 LMS 技术简化了这一学习过程。
它为教育内容提供一站式服务，提供包括视频、程序、课程、测验和指南在内的学习选项。这些内容可以是实时的，也可以是录制的，因此身处不同地点、时区和公司的个人都能轻松获取。公司使用 LMS 的目的是:
创建信息内容
在集中的数字位置组织内容
将内容直接发送给目标受众
监控学习进度
促进学习协作
人力资源领导为什么要关注学习管理系统？
学习管理系统软件提供定制化的信息内容，以吸引、激励和培养员工，同时提高生产率和员工保留率。学习管理系统可促进员工的专业成长，推动公司实现业务目标。学习管理系统可以优化人力资源功能，例如：
工作和合规培训
入职培训
技能差距分析
学习与发展
常见的学习管理系统功能和组件
学习管理系统因组织的需求而异。它们提供各种功能，旨在增强学习体验和简化管理任务。
一些常见的功能和组件包括:
用户管理。管理员可以管理用户配置文件、角色和权限，以便学习者可以访问适当的课程和材料。
课程创建。教师可以创建、组织和提供课程。他们可以上传不同类型的内容、设置作业和管理评分。
报告和分析。LMS 可提供有关学员进度、完成率和评估结果的数据，帮助管理员做出明智的决策。
设备兼容性。许多 LMS 都对移动设备友好，学习者可以使用智能手机和平板电脑访问内容和参与课程。
学习管理系统的类型
学习管理系统有多种不同类型：
企业 LMS。专为员工培训和发展而设计，具有合规跟踪、技能差距分析和绩效管理等功能。
开源 LMS。这些平台可定制且免费使用，为希望根据自身具体需求定制系统的组织提供了灵活性。
基于云的 LMS。这些在线学习管理系统由云端托管，具有可扩展性，可从任何有互联网连接的地方进行访问。
托管式 LMS。企业可以将这些 LMS 平台安装在本地服务器或硬件上，从而实现完全控制。
学习管理系统如何工作？
学员和教师可以通过创建用户账户访问企业的学习管理系统。
这些平台可能有预建课程，也可能允许企业轻松创建自己的课程。教师在平台上为学员上传课程资料，如文本、视频、测验和作业。
LMS 通常会生成关于学习者表现和课程效果的报告，因此管理层可以跟踪学习进度。管理员可以利用这些数据进行改进。
如何选择最佳学习管理系统
确定目标。明确概述学习目标和预期成果。
评估可扩展性。考虑 LMS 能否满足您当前和未来的需求。
考虑预算。确定 LMS 的预算，包括初始设置成本和持续维护费用。
确保用户界面友好。确保 LMS 为管理员和学员提供直观的界面。易用性是采用的关键。
检查内容兼容性。检查 LMS 是否支持您计划提供的内容类型，如多媒体和互动元素。
测试集成能力。如果计划将 LMS 与其他系统集成，请确保它能与这些系统协同工作。
评估 LMS 培训和支持。评估不同学习管理系统供应商提供的培训和支持水平。
如何成功实施学习管理系统
明智选择。由于学习管理系统的数量多得令人眼花缭乱，人力资源领导者必须重点考虑为什么要采用学习管理系统，以及学习管理系统将如何帮助他们实现目标。此外，了解不同的学习风格有助于领导者选择一个能促进员工成长和提高绩效的项目。
在内部推广 LMS。要想从 LMS 中获益，每个人都必须参与进来。人力资源专业人员可以采用不同的方法来激励专业人员使用 LMS，例如游戏化、激励措施，以及提前几个月让他们做好使用新 LMS 的准备。
收集反馈。员工的反馈意见至关重要，因为了解团队成员喜欢和不喜欢 LMS 的哪些方面，人力资源领导者就能对 LMS 进行调整，使其更加个性化和用户友好。
与管理人员沟通。为鼓励员工顺利过渡到 LMS，应与管理人员保持定期沟通。支持他们适应和调整新的 LMS，有助于他们带领团队接受新系统。
将 LMS 与传统学习相结合。不应忽视标准的面对面培训。例如，互动式小组研讨会和在职培训仍然很有价值，而且可能正是团队成员所需要的学习方式。人力资源领导者可以使用学习管理系统来补充传统的学习方法，并监控专业人员的学习进度。
学习管理系统如何改善企业文化？
让专业人员发展自己的知识和技能，可以培养工作场所的意义，提高他们的绩效，提升他们对公司的价值。支持员工发展可以让公司建立学习文化，促进业务增长，同时跟上瞬息万变的工作世界。
学习管理系统实例和用例
人力资源学习管理系统用途广泛。以下是一些与 HiBob 集成的平台示例及其部分功能：
360 学习。一个协作式学习平台，可帮助创建个性化的入职体验。
Learnster。一个具有多种用途的 LMS，包括合规性培训，使团队成员了解最新的法律要求和行业标准。
Learn Amp。支持学习和发展的平台。它通过提供具有明确发展路线的发展计划，帮助企业留住顶尖人才。
Auzmor。一个 LMS，专门通过预建和定制课程来提高组织专业人员的技能。
eloomi. 该平台帮助企业创建在线培训学院，提高员工参与度和客户满意度。
学习管理系统的未来趋势
说到 LMS，有几种未来趋势将重塑专业人员的学习与发展：
人工智能和个性化。学习管理系统中的人工智能将提供个性化的学习路径、建议和即时评估，从而节省教员的时间。
微学习。人们的注意力只会越来越短。简短、集中的内容模块将成为常态，以迎合学习者繁忙的日程安排。
增强现实（AR）和虚拟现实（VR）。AR 和 VR 技术将增强身临其境的学习体验。
社交学习。学习管理系统中的社交功能，如与社交媒体、聊天功能和论坛的集成，将使团队成员更容易合作和分享知识。
从学习管理系统中获益
LMS 在培训组织的专业人员及其客户和业务合作伙伴方面可以发挥关键作用。通过了解选择标准和新兴趋势，以及常见的 LMS 类型及其功能，企业将能充分获得学习与发展的好处。
以下为文章原文：
What is a learning management system?
A learning management system (LMS) is a type of software that companies use to train and educate employees, clients, and business partners. Traditionally, work training programs would take place in person over a few hours or days. But LMS technology streamlines this learning process.
It provides a one-stop shop for educational content, offering learning options including videos, programs, courses, quizzes, and guides. The content can be live or recorded so individuals in different locations, time zones, and companies can easily access it. Companies use LMSs to:
Create informational content
Organize it in a centralized digital location
Deliver it directly to the targeted audience
Monitor learning progress
Facilitate learning collaboration
Why should HR leaders care about a learning management system?
Learning management system software provides customized, informative content to engage, motivate, and develop the workforce while boosting productivity and retention. An LMS promotes professional growth in the workforce—propelling the company forward toward reaching its business goals. LMSs can optimize HR functions such as:
Job and compliance training
Onboarding
Skills gap analysis
Learning and development
Common learning management system features and components
LMSs vary depending on the needs of the organization. They offer a wide range of features designed to enhance the learning experience and streamline administrative tasks.
Some common features and components include:
User management. Administrators can manage user profiles, roles, and permissions so that learners have access to the appropriate courses and materials.
Course creation. Instructors can create, organize, and deliver courses. They can upload different types of content, set assignments, and manage grading.
Reporting and analytics. An LMS provides data on learner progress, completion rates, and assessment results, helping administrators make informed decisions.
Device compatibility. Many LMSs are mobile-friendly, allowing learners to access content and participate in courses using smartphones and tablets.
Types of learning management systems
There are a number of different types of LMS:
Corporate LMSs. Tailored for employee training and development, they include features like compliance tracking, skills gap analysis, and performance management.
Open-source LMSs. These platforms are customizable and free to use, providing flexibility for organizations that want to tailor the system to their specific needs.
Cloud-based LMSs. The cloud hosts these online learning management systems, offering scalability and accessibility from anywhere with an internet connection.
Hosted LMSs. Organizations can install these LMS platforms on local servers or hardware, giving them full control.
How do learning management systems work?
Learners and instructors can access an enterprise’s learning management system by creating user accounts.
These platforms may have pre-built courses or may allow organizations to easily build their own. Instructors upload course materials for learners on the platform, such as text, videos, quizzes, and assignments.
An LMS usually generates reports on learner performance and course effectiveness, so management can track progress. Administrators can use this data to make improvements.
How to choose the best learning management system
Define your objectives. Clearly outline your learning objectives and the desired outcomes.
Assess scalability. Consider whether the LMS can accommodate your current and future needs.
Consider your budget. Determine your budget for the LMS, including initial setup costs and ongoing maintenance fees.
Ensure a user-friendly interface. Ensure that the LMS has an intuitive interface for both administrators and learners. Usability is crucial for adoption.
Check content compatibility. Check that the LMS supports the types of content you plan to deliver, such as multimedia and interactive elements.
Test integration capabilities. If you plan to integrate the LMS with other systems, make sure it’s able to work with them.
Assess LMS training and support. Evaluate the level of training and support provided by different learning management system vendors.
How to successfully implement a learning management system
Choose wisely. Because there are a dizzying number of LMSs, HR leaders must focus on why they want to incorporate an LMS and how it will help them reach their goals. What’s more, understanding different learning styles helps leaders select a program that will promote growth and higher performance among the workforce.
Promote the LMS internally. To reap the benefits of an LMS, everyone must be on board. HR professionals can incorporate different methods to motivate professionals to use the LMS, such as gamification, incentives, and preparing them for the new LMS a few months ahead of time.
Gather feedback. Employee feedback is crucial, as understanding what team members like and dislike about the LMS enables HR leaders to adjust the LMS to be more personalized and user-friendly.
Check in with managers. To encourage a smooth transition into the LMS, maintain regular communication with managers. Supporting their adaptation and adjustment to the new LMS will help them lead their teams to embrace the new system.
Fuse the LMS with traditional learning. Standard, in-person training shouldn’t be disregarded. For example, interactive group workshops and on-the-job training are still worthwhile and may be just the learning style team members need. HR leaders can use an LMS to complement traditional learning methods and monitor the progress of professionals.
How can a learning management system improve company culture?
Enabling professionals to develop their knowledge and skills can nurture meaning in the workplace, improve their performance, and boost their value to the company. Supporting employee development allows companies to build a learning culture that facilitates business growth while keeping up with the rapidly changing world of work.
Learning management system examples and use cases
An HR learning management system can have a wide range of uses. Below are some examples of platforms that integrate with HiBob and some of their capabilities:
360learning. A collaborative learning platform that can help with creating a personalized onboarding experience.
Learnster. An LMS with a variety of uses including compliance training that keeps team members up to date with legal requirements and industry standards.
Learn Amp. A platform that supports learning and development. It’s helped organizations retain top talent by offering development programs with clear routes for progression.
Auzmor. An LMS that specializes in upskilling an organization’s professionals with both pre-built and custom courses.
eloomi. A platform that has helped businesses create online training academies that improve employee engagement and customer satisfaction.
Future trends in learning management systems
When it comes to LMSs, there are several future trends that will reshape learning and development for professionals:
AI and personalization. AI in LMSs will offer personalized learning paths, recommendations, and instant assessments—saving instructors time.
Microlearning. Attention spans are only getting shorter. Brief, focused content modules will become the norm, catering to learners’ busy schedules.
Augmented Reality (AR) and Virtual Reality (VR). AR and VR technologies will enhance immersive learning experiences.
Social learning. Social features within LMSs, such as integration with social media, chat functions, and forums will make it easier for team members to collaborate and share knowledge.
Reap the benefits of a learning management system
LMSs can play a pivotal role in training an organization’s professionals as well as its customers and business partners. By understanding selection criteria and emerging trends, along with common types of LMSs and their features, organizations will be able to fully reap the benefits of learning and development.
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