HR Analytics Courses Online

Human resources metrics help a company to understand how effective its HR activities are. HR metrics form the mainstay of HR analytics as the performance in these metrics decides the HR analytics strategy - whether to change, improvise or maintain the same strategies.

The key HR metrics are

1. Training for skills acquisition and development:

• This metric includes several factors like training expenses, that is, how much your company has to spend for training each employee.
• The training completion rate measures how many employees could complete specific training, divided by the aggregate of employees and multiplied by 100.

2. Training time completion:

• It is another vital factor that evaluates the time one employee takes to complete a training programme.
• Then comes training effectiveness, which tests can measure to see the pass-fail outcome.
• Finally, there is the question of training efficiency, evaluated by dividing training expenses per employee by training effectiveness.

3. Engaging with employees and retaining them:

• Due to the high competition among companies for recruiting fresh talents, HR analytics are increasingly concerned about retaining employees.
• Employee satisfaction is the most valuable sub-metric here. The number of employees who will give good feedback about your company contrasted with the ones who give negative feedback will ultimately determine your employee satisfaction rate.
• Net Promoter systems are practical tools for determining employee feedback.

4. Turnover Factor:

• The turnover factor determines how many employees resign from your enterprise within a given period.
• The total turnover rate is calculated by the ratio of the number of employees who have left with the total number of employees.
• The voluntary turnover rate involves only those staff who have resigned of their own accord.
• In contrast, the talent turnover rate comprises the number of high-performing workers who have left your company.
• As is evident, the talent turnover rate should ideally be very low for a company to be run excellently.

5. Recruitment:

• Under the umbrella of recruitment analytics falls the headcount of the total number of employees, the demographic quantifiers- age, gender, level of education, experience, etc. As an HR analyst, you also have to consider the time taken to hire a new staff member, the acceptance rates, average expenses per hiring process, and the new-hire turnover rates.
• Quality of hires, candidate lifecycle throughout the recruitment process/ funnel, recruitment processes’ success rate is also considered.

6. Employee performance:This includes the revenue earned per employee, categorisation of employees according to their potential and performance levels by a nine-box matrix which is one of the assessment tools, and tracking the employee’s personal goals and whether those align with the company’s.

7. Time tracking of absence:

HR analytics software comes with time trackers for the number of days the employees are absent apart from the pre-approved paid time-offs. Thus, helping in improving pay roll out, better transparency, and adhering to the labour laws.

The data collected by human resource analytics can be broadly classified into two categories- internal and external data. Internal data is the information an HR gets from their department regarding employee experience, tenure, records of their training, compensation and performance appraisal records. It also includes information on high-performing workers and disciplinary action(s) taken against any employee.

External data is what HR derives from other departments, as well as from outside the company’s domains, for gaining an international perspective. These include financial data from the organisation, data specific to your organisation's core objectives in terms of service, passive data from employees’ non-official activities, and employees’ socio-political or environmental situations and backgrounds.

Before collecting data for HR analytics, it is imperative to formulate a plan that not only chalks out the objectives but also outlines the best procedures for data collection. At first, you need to articulate your problem clearly; that is the target objective for which you are collecting data. Then you have to list the quantifiers or the criteria defining the data.

After clarifying the data's objectives, the right measurement method has to be selected, and a data collection format has to be prepared. Then you have to decide the method of sampling the data and divide the data analysis into numerous co-researchers with HR analytics training, one who will collect data, one who will analyse and interpret it, and another who will report the findings.

The purpose of HR analytics showcases its benefits, which are discussed in detail in the Benefits section. Here, we have provided a concise summary of its purposes.

• Enhance the company’s hiring process
• Minimising the turnover rate of the company’s employees' resignations
• Giving the employees a better work experience
• Enhancing the productivity of the talent pool
• Improvising the process of recruitment
• Most importantly, gaining the trust of the employees by bringing more transparency.

The data used in HR analytics help understand past events and draw conclusions from them. Cause-effect models are developed as part of the HR analytics strategy and how the variables in data samples affect the results. The final step is to use the analysed data to predict future trends and plan for them. For instance, market data aligned with turnover and appraisal data can be interpreted and analysed to create ideal workplace scenarios which foster employee satisfaction and efficiency.

We have outlined a detailed 7-step process for executing HR analytics in the smoothest way possible.

Determine the stakeholders' objectives: For any kind of HR analytics initiative, one should always clarify the perspective of the stakeholders, ranging from investors to workers and even technology vendors. Once you know their priorities and needs, you can start formulating your data research questions.

Outline your HR analytics agenda: It can be either long-term or short-term, depending upon the dynamics of your business and the “future of work”. Now that we have algorithms and automated technology, the timeline of HR analytics spans a maximum of 5 years, and one year is standard for most businesses.

Pinpoint the sources of your data: Now, you have to identify the type of data you are gathering- whether it is public or private, and review their credibility.

Collect the data: Now comes the actual research part, where you have to gather data from primary or secondary sources or from the company’s internal information, which you can feed into Human Resources Information System(HRIS).

Modify data: HR analytics helps in acquiring data from the employees that helps in reaching goals faster and efficiently managing the teams better. The accurate data can help in identifying the hidden patterns.

Communicating the outcomes: Dedicated HR analytics researchers emphasise how they communicate the findings to the public and the stakeholders. Storytelling is a powerful tool in this regard. As a result, it can not only be manipulated through emotions but there is also the risk of skewering HR analytics outcomes for some biased agenda. Hence, unbiased strategic communication is fundamental to HR analytics. The obtained data helps in managing the best talent, prioritising employee’s morale and motivation, increasing retention, and more.

Build a reliable HR analytics strategy and implement a decision-making process: HR analytics can be instrumental in helping the company revise, strengthen and redirect its objectives. It can also help the company align its data-driven decisions with public policies.

HR analytics can be successfully implemented for performance forecasting and management by tracking performance trends over a certain window. You need to consider specific metrics like revenue earned per employee. Sometimes HR professionals use a nine-box matrix to classify employees as per their performance levels and efficiency potential to plan for better leadership for group projects.

Your HR analytics software can also analyse the collected data to monitor whether the company goals are aligned with individual employee aims and track company performance in maintaining employee satisfaction.

Human resource Analytics collects data about employee turnover by focusing on the factors that lead to employee turnover and which employees pose a high risk of leaving companies in a relatively short time. Since employee turnover leads to direct and indirect financial losses for the company, aiming to decrease employee turnover can save some unnecessary expenditures.

To forecast employee turnover, HR analytics asks the following questions:

• How many employees leave the company each year?
• Which sections of employees resign most frequently?
• Is the current turnover percentage of high risk for the company?
• Which kinds of employees require special attention to prevent turnover?
• What are the general causes behind people leaving their jobs

As decision-making procedures change in the department of HR, increasingly shifting the focus on data-driven outcomes, data analytics has become vital for HR. After 2020, HR analytics has been the primary solution to combat the challenges of labour as well as skill shortage. The global market for HR Analytics is expected to grow at the rate of 14.3% and is expected to reach USD 8.59 billion by 2030 (Source).

As workforce gets competitive, the only way to retain employees and reduce turnover is to implement the HR metrics provided by HR analytics and provide employees with worker satisfaction. A global programme dealing with data analytics, Startup Focus noted that using HR metrics for employee recruitment and compensation can help understand the employees better and improve the business outcomes, thus minimising costs.

• Better decisions are taken while recruiting new talents: The right HR analytics tool helps the employer choose the right candidates based on data-driven proof and hire them.
• Minimises scarcity of efficient workers: When your recruitment strategy is backed by HR analytics, you can restructure your hiring net to convince talented candidates to join your firm. Knowing the right person to target for hiring when the need arises will always keep you a step ahead of your competitors. Since HR analytics gives an idea of the best talents to hire for your workforce, optimising company performance becomes easier.
• Better training: No company can expand without constantly training itself for new challenges and demands. Uneven administration of training can cause losses to the company. Using Human resources analytics, you can choose the correct training programs for the workers and even evaluate the impact of the training on them.
• Reduced turnover rate: There are many reasons employees would quit a job at a massive rate. It can range from overworking without adequate compensation to an unsuitable workplace atmosphere. HR analytics uses surveys and team assessments, among many other data sources, to identify the causes of the turnover rate and accordingly suggest solutions.
• Better experience for the candidates: HR analytics help minimise the tedium of long hiring processes and help companies recruit talents as fast as possible while adhering to all decorum. This creates a favourable impression on candidates and boosts brand image.

Here is a detailed guide on applying HR analytics to your company’s proceedings.

First, you must select certain metrics and key performance indicators to predict certain business outcomes. For instance, you can predict employee engagement by using indicators and metrics like social engagement, communication in work chats, compensations, team sizes, or even net promoter scores.

Once you decide on the metrics, you have to identify the sources from which you can obtain data. These are not limited to social media engagements but can be as vast as recruiting software and talent management software.

Focus on a tool to implement the data. You can choose from off-the-shelf HR analytics software like Namely or Cezanne HR to help you with recruitment, onboarding and predictive tasks. Or, you can use a customised HR analytics system provided by your organisation specifically for collecting data that pertains to your company’s objectives.

Create a team of data analysts, HR managers, data warehouse developers and database overseers for smooth execution of each step of the HR analytics process. Then you have to build a data warehouse cloud storage where you can consolidate and analyse the structured data in sizeable amounts.

Often, HR departments have to face certain challenges while implementing HR analytics information. Some of these challenges have been listed below:

• Problems in data cleansing:Sourcing, sorting and merging data from different sources often poses a problem when the scope is huge. Not only does HR have to collect data from all departments Furthermore, but the data is also usually unstructured, which requires highly skilled HR personnel to correctly assess the data, which brings us to our next challenge:

• The absence of HR data analytics skillset: Often, the right kind of person who can handle big data of HR analytics is very rare. The reason is that most HR managers have an MBA degree instead of an HR management degree, and the company also does not hire specific HR personnel to work with data analytics in Human resources. Inability to filter out excess data can often affect the results, leading to a loss of clarity.

• Challenges in maintaining privacy and compliance regarding the data collected. Employee privacy is paramount for HR analytics, and sensitive information can often put HR in a fix as to how it can be implemented.

• Inadequate resources: For data analytics, you need access to specific tools, and programs like Apache Hadoop might not be affordable for companies with small infrastructure and limited capital.

Using Artificial Intelligence for HR decisions, companies can develop a foolproof plan to keep them ahead of the competition in a rapidly changing world. Earlier, HR authorities learned about employee feedback only after the turnover. Nowadays, HR analytics can make the most of their talent pool by predicting employee behaviours, gaining workplace insights, and analysing them to recognise the employee’s contributions more rewardingly.

Because despite the acknowledgement of the utility of HR analytics, many companies have not started implementing it. It only highlights their inability to keep up with dynamic markets and prevent employee turnover. Josh Bersin of Deloitte reported in 2017 that 78% of the industries acknowledged the importance of HR analytics in maintaining diversity and inclusivity within the workforce.

1. Organisational Goals

HR analytics operations should be attuned to reflect your organisational goals practically. The workplace culture has to be analysed as valuable HR analytics data to determine that employees are committed to the company and its organisational goals. If employees are majorly erratic and inconsistent, it indicates an unhealthy workplace culture- a gap that the HR team needs to address. It enables the HR to oversee the affect of HR metrics at the organisation level and thus improving the decision making process.

2. HR analytics Strategy

Here are the four basic steps essential for planning an HR analytics strategy:

• Evaluating the present management capacity of HR.
• Predicting the requirements of HR, especially the demand and the supply.
• Developing strategies for recruiting, selecting and hiring new talents and ensuring their training.
• Reviewing the company’s performance, especially how much time has been taken to meet its organisational goals.

3. Key HR Metrics

Covered under section 5: “What metrics should you track for HR analytics?”

4. People Analytics

For more efficient management of the human workforce, it is essential to have people analytics training. Nowadays, hr team leaders take specifically people analytics courses for making decisions based on factual data rather than relying upon personal equations' uncertainty. People with HR analytics skills analyse the data on employee experience and behavioural patterns to help a company manage its talent pool.

5. HR Channels used or HR analytics

Using HR channels for HR analytics falls under recruitment analytics. As an HR analyst, one has to check from which HR channel you can get the most promising candidates, thereby determining their effectiveness. Nowadays, talent acquisition methods are mostly online due to the faster and wider exchange of information.

HR channels online use their talent recruitment strategy to connect potential employers and potential employees. Hence, HR analytics specialists need to know which HR channel they should invest their time and money in to recruit employees. These can range from posting advertisements on Job Boards to creating a sub-section on the company website for inviting applications from candidates, asking former employees for referrals to potential hires, and even posting on social media channels like LinkedIn.

Although HR analytics courses online are remote and might pose a challenge for student-instructor interaction, the benefits outdo the drawbacks. You can learn from the best HR analytic ed-tech platforms from any location, provided you have a stable internet connection. Furthermore, the class timings are usually flexible, allowing you to learn at your own pace.

Nowadays, HR analytics certification online courses are provided by the topmost faculty from the world’s most renowned universities, thus expanding your learning opportunities. Furthermore, there are many free online HR analytics courses available.

The best HR analytics certification course will teach you to gather, analyse and map HR data to implement it in making decisions and recommendations. The first module usually consists of an introduction to HR analytics, where learners are taught why hr analyst skills are vital for business, such as to minimise human bias in HR decisions. They will also be provided examples from practical, real-life situations to familiarise them with the concepts and their utility.

The next module of the HR analytics course content comprises data and hr metrics evaluation. The concepts taught in this module include data tracking, categorising and connecting HR decisions with business outcomes.

The third module will comprise a sample HR analytics project on how to start collecting data by asking the right questions, the requirements of this project, data cleaning and analysis, and finally, implementation of the hr data analytics results.

There are several HR data analytic courses available, be they HR analytics courses online or offline. Some of them are HR analytics courses with placements like the one by Cornell University.

An HR analytics research company, Persistence Market Research, has demonstrated that the HR analytics industry is currently rated at 2.8 billion us dollars in 2022. By 2030, it will become 9 billion us dollars worth. The compound annual growth rate is estimated at 12.4% by this company. On the other hand, Grand View Research claims that the CAGR for the HR analytics industry will be 14.3% from 2022 to 2030.

As early as 2017, human resource analytics became the buzzword for finance, health, retail and cutting-edge technology industries. At that time, more than 50% of the industries were willing to adopt HR analytics in their business strategy, leading to a demand for HR analytics courses. By 2025 it is predicted that HR analytics courses will become as established a discipline as other business degrees.

The average salary for an HR analytics specialist is 484,562 INR per annum. The minimum is 246,000 INR, and the maximum limit is 775,000 INR per annum. The bonus can range from 20,000 INR to 129,000 INR per annum. Profit sharing, if any, can be as much as 18,000 INR per annum. Hence, the total pay varies from 248,000 INR to 833,000 INR.

The HR analytics specialist salary in India varies based on experience and corresponding HR analytics skills. We have prepared a chart here about the levels of experience for a human resource analytics specialist and the corresponding salary increments on average.

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Note: The numbers are subject to vary owing to the economic climate of the country.

The starting salary for an HR analytics specialist is an average of 2.5 lacs INR per annum, which means roughly 20.8 thousand INR per month.

The average salary for an HR analytics specialist abroad, for instance, in Europe, is £ 32,499. The minimum salary is £ 24,999, and the maximum is £ 42,999. In the UK, for instance, the average salary for someone with HR analytics skills is £ 29,966 per annum and ranges from a minimum of £ 24,000 to a maximum of £ 38,000. The HR analytics specialist salary in the US is between $54,221 and $67,775.