- Introduction
- What are the Benefits of Using Data Analytics in HRM?
- HR Data Analytics in Practice
- Data Driven Talent Acquisition
- Applications and Use Cases of HR Data Analytics
- Get rid of the issues that come with turnover.
- Enhance and Accelerate the Hiring Process
- Rethink your retention strategies
- Reduce risk and improve forecasting to stay ahead of the game.
- Never hire toxic people.
- Which candidate would be the most culturally compatible with the company?
- There is a skills shortage: Should we recruit or upskill?
- Which workers are on the verge of quitting the company?
- Do workers contribute to the success of the company in a constructive way?
- Recruiting Metrics in HR Data Analytics
- Using HR Metrics Dashboard
- HR Data Analytics Companies
- Big Data and HR Analytics
- HR Analytics Using Python
- Topics in Data Analytics
Introduction
Data analytics may be seen all over the place. It is, at its core, a system that learns from previous data and forecasts individual behaviour. As a result, forecasts are exact.
So, how exactly do these data analytics function? Data analytics is a collection of statistical methods for analysing past data and results. These methods then attempt to develop a formula or algorithm that most closely resembles these past results. This programme then utilises current data to forecast future events.
What are the Benefits of Using Data Analytics in HRM?
Data analytics in HRM may help to simplify all aspects of recruiting and keeping employees at a company. It may assist in selecting the appropriate personnel based on the organisation’s culture, ethics, and work environment and provide them with a welcoming atmosphere to stay in for a long time.
- to close the skill gap
- to find and recruit the best individuals
- to boost employee efficiency
- employees that are dissatisfied with their jobs are identified
- to keep top performers
HR analytics can be a crucial element for a company’s performance for various reasons. HR analytics may help you enhance your company’s expenditures, operations, and efficiency by collecting valuable data.
HR Data Analytics in Practice
What role does data analytics play in HR now? HR has a lot of information about individuals, typically stored in a Human Resources Information System. HR may become a strategic partner who depends on established and data-driven data analytics models rather than gut feeling and soft science by applying data analysis to this data. HR data analytics allows HR to anticipate the effect of people’s policies on employee well-being, satisfaction, and bottom-line results. The role it may play in avoiding costly staff turnover is one example.
Only a few companies, however, are capable of developing HR data analytics models. Only 17 per cent of companies globally have access to and used HR data, according to Deloitte’s 2018 People Analytics Maturity Model. This is an increase from 8% in 2015 and 4% in 2014.
Only 2% of the 17 per cent in 2018 qualified as having business-integrated data, which means they gather, integrate, and analyse data in real-time using sophisticated AI-aided technologies. The remaining 15% can do ad-hoc data analytics.
Data Driven Talent Acquisition
Obviously, most of the functions haven’t however shifted to the current high business impact approach of HR data analytics, however fortunately, there are some of benchmark corporations like Google, Sodexo, and Netflix that have incontestible the success of this new data-driven high business impact analytical approach.
Before considering this major shift, senior executives ought to absolutely perceive the benefits that result from dynamic to the present new model. They conjointly got to be able to “sell” their company executives on the value of investment throughout this new HR approach.
So as to satisfy each these needs, the most strategic reasons for shifting to a data-driven HR analytics model are presented in the following section. A company simply begin that transition among the highest impact HR area, that is recruiting, and then continue the transformation within following other highest impact areas of HR like retention, learning and manpower productivity, and innovation.
Applications and Use Cases of HR Data Analytics
Get rid of the issues that come with turnover.
You may examine data in terms of geographical regions, particular roles, and so on with HR metrics in hand. Role changes, travel times, engagement rates, performance problems, and other variables may be filtered out using a data analytics model. HR departments can avoid terminations, reduce resignations, and manage recruiting in a panic or desperation with data assistance.
Enhance and Accelerate the Hiring Process
If you’re trying to figure out which of your recruiting tactics is succeeding, Which campaigns have proven to be effective? Which advertising is the most effective? Data analysis is the solution to all of your recruiting problems. It assists you in determining which patterns and methods aid in increasing and improving retention rates.
Rethink your retention strategies
Employers benefit from the data analysis since it reveals which workers are most likely to leave in the coming years. With this critical data in hand, HR teams can evaluate and rethink employee retention tactics and techniques to help keep happy workers happy and maximise retention via improved engagement models.
Reduce risk and improve forecasting to stay ahead of the game.
Organisations can keep risks at bay by using HR metrics and analytics. It aids HR teams in predicting which workers need training, attention from management, and so on. Predicting an adverse scenario and adequately handling it may assist the business to minimise risk, legal problems, and needless expenditures.
Never hire toxic people.
These individuals are not only harmful to the business but also the overall work atmosphere. According to previous studies, just one toxic person in a team may reduce productivity by 30 to 40 per cent. Furthermore, when excellent individuals are forced to work with toxic coworkers, they are more likely to leave.
A dataset of 63,000 workers was utilised by the business. They indicated which workers were involuntarily dismissed due to workplace aggression, document falsification, drug and alcohol misuse, and other policy breaches in this dataset. Based on these criteria, about 4% of all workers can be labelled as “toxic.”
Surprisingly, the research found no evidence of the previously reported high levels of short-term productivity loss. It did, however, discover that harmful conduct is infectious. People who work with toxic coworkers are more likely to leave their jobs. Furthermore, the research predicted that toxic coworkers cause long-term stress and burnout in other employees.
Which candidate would be the most culturally compatible with the company?
HR may utilise data analytics in recruiting to forecast the characteristics of an employee who would be the most excellent match for the company. Furthermore, a mix of data on engagement, growth, success, and attrition rates may aid recruiters in predicting an employee’s future performance. Hence, improving business results by enabling recruiters to identify particular applicants for a job quicker, saving them the time and effort of sifting through hundreds of resumes to fill a single position.
There is a skills shortage: Should we recruit or upskill?
A data analytics system can quickly anticipate what capabilities the company lacks based on the data it has access to. Furthermore, data analytics engines can determine which workers are most suited to upskill in that area based on their experience, skill sets, and education. This implies that instead of recruiting fresh talent as a first choice, companies may turn internally to address skill shortages. One of the most effective ways that data analytics changes HR will generate better positive business results is reduced recruiting expenses and optimum worker utilisation.
Which workers are on the verge of quitting the company?
Employee attrition is one of the most pressing issues confronting businesses today. Data analytics can be used to identify at-risk workers and take preventive measures. Data analytics can show who is most likely to quit the business by evaluating variables like salary, promotions, corporate climate, and connections with managers, acting as a game-changer in customising the engagement process for those workers and their retention.
Do workers contribute to the success of the company in a constructive way?
Is staff productivity translating into profitable company results? What is it that workers are doing that is causing the company to perform better? How can this model be scaled up in the future? Data analytics can quickly evaluate essential data and provide HR departments with insights. The same technique may be used to discover areas that need improvement and the workers who are most likely to do so.
Recruiting Metrics in HR Data Analytics
It refers to the measurement used for tracking hiring potential, success, and optimization during the recruitment process. With the help of these metrics, organizations can evaluate recruitment decisions and processes. Some of the major types of metrics are bifurcated into two phases – pre and post recruitment.
Pre-recruitment metrics
Metric | Description |
Time to Fill | It indicates the time taken by the organization to find and final a new candidate for the role. The metric is influenced by the demand and supply ratios for the specific roles. Ideally, it is measured as the number of days between the job opening date and the closure of the hiring process. |
Time to Hire | The metric represents the period extending from the day when a candidate is approached till the day offer is accepted. It serves as a solid indicator for measuring the performance of the recruitment team and is also referred to as “Time to Accept”. |
Source of Hire | It considers tracking all the sources that bring new hires into the organization and evaluate the effectiveness of the recruiting channels like social media, sourcing agencies, job boards, etc. |
Recruitment Funnel | The effectiveness of the recruitment funnel is measured from the beginning of the sourcing period and ends with signing a contract. It is also termed as yield ratio per step which is calculated by dividing the number of applicants who competed for the stage by the total number of enrolled candidates. |
% of Open Positions | It is calculated as the number of open positions in a specific department divided by the total number of positions in the entire organization. The high rate of open positions indicates higher demand. |
Sourcing Channel Cost | It is the measurement of effectiveness and cost of the sourcing channel which includes cost spent on the advertisement on distinct platforms. Thus, it is calculated by dividing Ad spending per platform by the number of successful applicants per platform. |
Post- recruitment metrics
Metric | Description |
Offer Acceptance Rate | The metric analysis compares the number of candidates who accepted the offer to the number of candidates who received it. It is the measure of compensation potential of the organization which minimizes the impact of refused job offers. |
First- Year Attrition | It is considered as the key recruiting metric which demonstrates the hiring success of the organization. The attrition can be defined as both managed and unmanaged, where the former refers to the contract termination by the employer where in the latter case employee leave the organization on his own accord. |
Success Ratio | The ratio defines the quality of the hire and is calculated by dividing the number of hires who perform well by the total number of hiring. A high success ratio represents that majority of hired candidates are performing well. |
Cost Per Hire | With the calculation of metrics, the organization gets an idea about total cost involvement, both the internal and external ones. Thus, the cost per hire is calculated by dividing recruitment cost by the total number of hires. |
Selection Ratio | It is also termed the submittals to hire ratio and is calculated by dividing the total number of candidates hired by the total number of candidates approach. Moreover, it helps to analyze the value of different assessment and recruitment tools. |
Cost of getting to OPL | Here, OPL refers to the Optimum Productivity Level which indicates the cost involvement in speeding the personnel progress. The major types of cost for calculating OPL are onboarding cost, training cost, and cost of supervisors. |
Using HR Metrics Dashboard
It is a business intelligence tool allowing the Human Resource team to track, measure, and report essential KPIs. Today, HR dashboards are more interactive and leverage deep insights into employee performance, workplace management, and recruitment optimization. The dashboard is based on augmented analytics and facilitates payroll, compliances, recruiting, and learning processes. Based on their functions HR metric dashboard can be defined in the following manner:
Dashboard | Description |
Executive HR | The HR executives use this metric dashboard for reviewing and analyzing all critical KPIs at one platform. As a result, it helps in the effective management of employees and their training and compensation requirements. |
Employee Performance | The dashboard helps HR managers and teams to evaluate the performance of the workforce along with focusing on their satisfaction level. As a result, such a dashboard identifies the training needs for the employees. |
Employee Development | With the proper evaluation of employee performance, the next major concern lies in promoting employee development. Thus, the interactive charts allow department heads to break data into various dimensions and establish suitable training programs. |
Workforce Diversity | The workforce diversity and demographics metric help to create a balance between the workforces and establish ethnic work diversity. Moreover, such metrics help to deeply understand the demographic characteristics of the employee. |
Salary Comparison | HR professionals use the dashboard for evaluating the salary structure of the employees in the organization and draw a required comparative study based on their management positions, country, period of service, etc. |
Women in Workforce | The dashboard is used for analyzing the representation of a particular group in the organization. The data visualization regarding the women in the workforce is the most prominent way to use this dashboard. |
HR Data Analytics Companies
Today, the technical giants are all geared up to serve the world with their core competencies in data analytics. These companies are the key difference makers and have bridged the accessibility gap of the technology making it feasible for everyone to derive to chase the full potential of the emerging technology. Some of the HR data analytics companies that have contributed immensely in streamlining the recruitment and employee maintenance processes are listed below:
Company Name | Description |
Workday | Workday provides core HR reporting software to deliver secure self-service for facilitating data analytics and reporting. The role-based single platform is known for facilitating unparalleled agility and insight into workforce management. Moreover, the workday helps to track predefined HR metrics with the help of configurable dashboards. Thus, the Human Capital Management System of Workday leverage the ease of workforce operations like skill composition, talent acquisition, reward generation, and diversity building. Over the years the company has delivered more than 2000 reports backed by 150 dashboards to configure the data analytics operations. |
Human Resource professionals across the world see Google as their ideal partner for implementing data analytics algorithms in their day-to-day operations. Thus, the platform is suitable for all HR-related functions, be it recruitment, general functions, or others. Google Analytics’ function helps organizations to understand the response, reactions, and behavioral patterns of the potential candidate to establish a healthy recruitment campaign. Moreover, with the powerful predictive insights, the hiring team can delve deeper and understand the needs, interests, and preferences of the employees in advance and enhance their retention rates. | |
SAP | The progressive approach of SAP towards HR data analytics helps organizations to drive healthy performance and training campaigns. The SAP success factors focus on all key metrics and facilitate strategic workforce planning, financial modeling, organizing intelligent meetings, consider trending data and ensure effective headcount planning which leads to better insight development. The collaborative approach of data analytics with HR functionalities in the SAP softwares ensures better planning and process simulations. As a result. SAP softwares and dashboards are becoming the favorite choice of professionals across the world. |
Mckinsey | It is a global data-driven company that focuses on advanced data analytics for easing out the recruitment process and ensuring diversity hiring. With the use of Mckinsey data analytics software, organizations can search, spot, attract, develop and retain talented people. Alongside, it helps entities and professionals to make predictive and research-based decisions rather than relying on instinct and intuitions. As a result, senior talent leaders receive immense strength to increase rigor, improve performance and reduce bias. The technological leader Mckinsey has set the distinct benchmark for creating a healthy HR ecosystem. |
IBM | The approach of IBM technologies towards data science and analytic have restructured the Human Resource ecosystem towards a progressive pathway. With the sincere consideration of workforce analytics, IBM enlightens several organizations to understand the labor market trends, provide a healthy shift towards the strategic direction, and fixing regulatory & compliance issues. The partnership of IBM with several sourcing partners across the world acts as a cherry on the cake because it provides well-researched data and helps to provide accurate pattern study and predictions thereupon. As a result, these predictions play a crucial role in mitigating pressing workforce challenges and gain an edge over the competitor marketplace. |
Deloitte | The company sees data analytics as the key role player in bringing progressive prosperity to HR operations. Deloitte’s workforce planning analytics help to create an instrumental impact in solving workforce-related complexities. The fact-based approach of the company for supporting HR functionalities is reflected well in their applications and softwares. They are competent data analytics service providers and keep their clients way ahead in the analysis and prediction game by tripling leadership development attributes and customizing the employee needs & expectations. Moreover, the proficiency of the corporation in leveraging the potential of data analytics in the world makes it a reliable data source and consulting company. |
PWC | The globally renowned company is known for building stepping stones for client’s better future. Since efficient use of resources is the success mantra for every business entity, therefore it is important to understand and bridge the human resource gaps in the organization. It becomes possible with the PWC HR data analytic softwares that make the job easier. The PWC”s predictive modeling features help to identify and analyze real-time workforce patterns and predictions. Moreover, the PWC technological up-gradation also supports the skill assessment process in the organization using its machine and deep learning tools and algorithms. |
Visier | In recent times Visier is leading the people analytics atmosphere by delivering strategies for measurable and achievable human resource goals. Visier HR analytics has simplified the recruitment processes and formalities by streamlining them into a single data-driven platform. Furthermore, its principle analytics approach focuses on drawing reflection of the employee and labor market scenarios to synchronize organizational strategies with the market opportunities. After the completion of the hiring process, the organization faces stronger challenges like retaining potential employees, meeting their expectations, and organizing training sessions. Thus, Visier data analytics provide a boost to these organizations in identifying employee performance gaps using data-driven AI technology. |
Amazon | It is not just a company but a brand that has proved its supremacy in everything service it offers, the same applies to its technical aspects too. The data-driven advanced analytics approach of Amazon has revolutionized the HR and workforce management ecosystem across the world with its interactive and proficient softwares. Besides, developing predictions, Amazon technologies are equally proficient in generating reliable reports which help to frame suitable HR strategies and roadmap for achieving organizational goals. With the use of Amazon, HR data analytics professionals find it more convenient to address employee grievances and create room for improvement. |
Big Data and HR Analytics
Before, it has been somewhat simple to gather certain employee information, for example, pay rates and arrangement for assistance. In any case, big data HR analytics has made it conceivable to gather and evaluate information previously, during, and after the employment of an employee to help illuminate recruiting choices and foster a more effective employee environment.
Big data HR analytics can enable HR directors to screen and track the effectiveness of enrollment endeavors to attract most proficient candidates than their best competitors in the industry. Big data HR analytics can smooth out recruiting cycles and make it simpler to limit huge pools of candidates to a more modest, more qualified pool of talented professionals.
Likewise, big data HR analytics offers an opportunity to recognize worker talents and foster projects that are intended to further develop skillsets in employees and control dropouts. With big data, HR supervisors can get what is important to hold top quality employees and also keep them satisfied in their jobs.
HR Analytics Using Python
The requirement for further developed factual computations when examining individuals information has seen HR experts moving away from Excel and SPSS and accepting latest technologies like Python and R. All in all, for what reason would it be advisable for you to utilize Python for HR data analytics?
For those that probably won’t be that acquainted with Python, initially it’s an open source programming language with a wide assortment of support and designers. This implies there’s a variety of packages intended to work with Python for a wide range of enterprise needs. At last, it’s utilized for universally useful programming and is notable for its clarity, versatility and the instant information that it offers. Python is glue language implying that it can collaborate well with existing applications and programming languages.
Topics in Data Analytics
- Advanced Data Analytics
- Clinical Analytics
- Credit Risk Analytics
- Cyber Risk Analytics
- Data Analytics for Customer Behavior and Customer Experience
- Data Analytics for Customer Journey
- Data Analytics for Fraud Detection
- Data Analytics for Human Resources
- Data Analytics for Logistics and Supply Management
- Data Analytics for Risk Management
- Data Analytics for Talent Acquisition and Management
- Data Analytics in Asset Management
- Data Analytics in Digital Marketing
- Data Analytics in Healthcare – Use Cases, Metrics, Techniques, Companies and More
- Data Analytics in Manufacturing
- Data Analytics in Pharmaceutical Industry
- Descriptive Analytics – Definition, Types, Examples, and More
- Digital Analytics
- Financial Data Analytics
- Financial Risk Analytics
- HealthCare Claim Analytics
- Insurance Risk Analytics
- Insurance Risk Analytics
- Population Health Analytics
- Portfolio Risk Analytics
- Revenue Cycle Analytics
- Risk Assessment Analytics
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