The concept of HR came into being with the advent of the Industrial revolution. With growing industries and factories, there came a huge demand for various categories of labor. To boost the supply of laborers, monetary benefits were rewarded. To manage this workforce, the need for a supervisor/manager arose which is now termed as Human Resource Management (HRM).
In the early days like when Britishers ruled India, HR’s job was more on the principle of dominance and subordination and during those times it can’t be termed as a profession. But soon with the emergence of modern industrial labor, democratic ideology, the concept of the welfare state, etc., the role of an HR found its place in business as a profession. Though businesses during the early 1950s did not realize the impact of HR decisions on business strategy and with globalization, HRM was considered a part of business management.
Relation with Data
HRM has its roots with data long before it found it found its recognition in the organizations as HR analytics.
HR measurements in real sense and form started with the challenge of finding the right persons in the organization. This is also reflected during world war II when the US army faced an acute shortage of skilled manpower.
US army devised a skill test and used that data to select the right people. Soon, the research in the field of HR analytics grew to find its applications at a large scale in organizations.
Events that led to the evolution of HR analytics
An article titled ‘The measurement imperative’ proposed the idea of measuring the impact of HR activities with collected data on the bottom line of the business. The proposed activities included staff retention, staffing, compensation, competency development, etc.
The idea marks the beginning of the data capturing activity in HRM and its application in organizations.
With growing development in the field of and HR measurement integration with more business dimensions, the predictive and assessment models became a subject of study. But still, the field of HR analytics remained unknown to many organizations and they couldn’t realize its potential.
The developments leading to the concept of ‘Bench-marking’ to compare the HR measurement data in various functions and with other companies. Though companies soon realized that while in theory ‘Bench-marking’ promises to provide strategic business insights, in real business scenario it fails to do the same and Bench-marking lost its recognition by early 2000.
The emergence of HR accounting and utility analysis was witnessed and this added new dimension and measurement data to quantify HR. Researchers not only drew the inference from business firms but from other sources too. One such research is on the metric model adopted by Billy Beane, the general manager of the USA baseball team to select team members.
The study led to a breakthrough metric-based selection model development called as ‘Moneyball’ concept in 2003 and found its adoption at large scale by organizations since 2006.
Though HR Analytics found its growth by late 2000, many organizations were still confused with its adoption and its implementation. Some known MNCs were able to foresee its potential of HR analytics and its benefits to the organization and took initiatives to deep dive into this field.
In 2009, Google started ‘Project Oxygen’ to find the qualities and attributes of an effective manager. The project gained global recognition in 2011 when it published the data-based findings and was found to very relevant and effective across different industries.
The success of the project boosted research regarding the benefits of analytics in workforce management. Around 20 articles were published on topics of Talent and workforce analytics by Harvard Business Review, Wall Street Journal, Forbes, Fortune magazines, etc.
The articles not only supported the application of analytics in workforce management but also found some shortcomings of the ‘Project Oxygen’ like positive co-relation between academic grades and employee performance. But ‘Project Oxygen’ laid the foundation for a dynamic shift from traditional metrics-based HR measurement to Predictive analysis of HR analytics.
IBM acquired an employment and retention service company, Kenexa in 2012. With its cloud-based solutions combined with Oracle, Tableau, and SAP, IBM discovered ways for talent management by analyzing the voluminous big data of HR.
With organizations observing the benefits of HR analytics in business strategic decisions, many have implemented HR analytics within the organization. Some known players in the industry are:
Microsoft found the employee attrition as a major challenge across its various business units. It deployed HR analytics tools to generate a statistical profile of employees who were likely to leave the organizations.
The company found that majority of these profiles were of the direct college hires and those who had not been promoted even after being with the company for 3 years. These insights allowed Microsoft to take several HR interventions like the assignment of mentors, changes in stock vesting, and income hikes to better manage the employee and control attrition.
To observe the effectiveness of these interventions, Microsoft implemented them only in two business units with high attrition rates and observed a significant reduction in attrition rates by more than half in both the business units.
Mindtree is using HR analytics to make strategic decisions about –
- Employee Turnover
- Risk assessment
- Profile management
- Productivity index
With HR analytic tools, Mindtree can predict employee turnover for the next 90 days from employee data. This has enabled them to generate insights from data analysis and fed those insights into forecasting models for employee hiring.
Using analytic tools, HR also manages high-risk employees and uses the data to make better management decisions.
For example – Mindtree concluded from the data analysis that high-risk employee makes the first move for any opportunity within the organization.
3. ConAgra Foods
ConAgra Foods Inc. saw many of its key employees leaving the organization. The company then deployed predictive analytics software to predict the likeliness of an employee leaving the organization. With this data, the company then created a model to identify the factors behind employee attrition, and around 200 factors were fed into the model.
The analysis reflected that pay isn’t among the top 10 significant factors contributing to employee attrition while it is internal recognition that is having a high correlation with employee attrition.
4. Wipro Ltd.
Wipro is using HR analytics to boost employee retention and combined with social media analytics, it is also finding new skills and talent through Human Capital Management. With labor mobility, Wipro has transitioned from a cloud-based oracle system to its own Wipro HR sprinter for augmenting talent management. Using this HR analytics software, Wipro can see the trends of each employee, the data of employees, and their predicted behavior with just a click.
Prevalent Industry Scenario
HR analytics is still a growing field and even with its immense application, the acceptance level is low. When it comes to the IT sector, the software market covers 18% of the HR analytical market in which the company outsourced the analytical tools for data gathering and analysis, whereas presently only 10.9% of companies using advanced analytical solutions for the HR process.
A survey with 3300 HR managers as respondents showed that only 75% of them think analytics is important for strategic decisions and a mere 8% consider their business strong in the field of HR analytics. The survey reflects that even after immense growth in HR analytics and the emergence of Big Data, HR practitioners are still far behind in using analytical tools for competitive decision-making.
While a 2014 report on the use of analytics in India shows that 61% of HR leaders say they use talent and workforce analytics as part of their talent strategy and workforce planning process.
The Road ahead
HR analytics adoption is likely to observe much more rapid growth. The continuous innovation in the field of AI and analytics will expand the horizons of HR as a strategic business unit.
The bottom line is, utilizing HR analytics by tapping into an organization’s existing people data will inevitably lead to more productive and better-connected teams. Everyone within an organization can use data science to find the right people at the right time and match the right people with opportunities and projects that move the needle.
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