HR-Analytics is the process of analyzing the available people-related data to measure the effectiveness of the HR programs and identify patterns in order to make meaningful business decisions.
The advent in analytics has helped HR grow from being transactional and reactive to strategic and proactive, by helping to grow from basic reporting to Business Intelligence tools that include dashboards, data warehouses, and advanced analytics.
HR-Analytics gained prominence as software providers like SAP, Workday, Oracle and UltiPro offered the HR Analytical tools with their HRIS offerings. The terms talent analytics and workforce analytics are often used synonymously. HR-Analytics uses mostly people-related data i.e.., payroll, HR etc., and encompasses people-related data and the business operational data.
There are four broadly defined types of analytics as described-
Descriptive Analytics: Considered as the foundation of the business intelligence, primarily focused on what happened for i.e., employee turnover, new hire report, time to hire, number of openings etc.
Diagnostic Analytics: Focuses on why did it happen? It takes a deep dive at the data to understand the causes of events and behaviours: i.e. For employee turnover, the diagnostic analysis would help identify the type of separations voluntary vs Involuntary and/or the regions or the business units tied to the actual location or by managers, to review the hiring process or onboarding process or even training the managers.
Predictive Analytics: Are the advanced stage of the analytics model and the basis of Big Data. The predictive analytics focuses on statistical analysis, forecasting, co-relations and build predictive models based on the historical people-related data. In essence, it’s a future-focused analysis that predicts the future patterns based on the historical data: i.e., For identifying the flight risk employees helps to reduce employee turnover and improve the bottom line. The other example is in hiring, identifying applicants with a propensity to join or who can be successful at the organizations, thus helping the talent acquisition team to fill the position quickly.
Prescriptive Analytics: Considered as the future of the Big Data, prescriptive analytics focuses on prescribing potential actions to guide towards a solution. Prescriptive analytics uses machine learning and artificial intelligence to understand future events and determine the best outcomes based on various scenarios, helping organizations to mitigate future risks.
This digibook is a roadmap to insight from analytics and essential advice for working with IT, management, and employees to lay the foundations for the future of HR.
Who will find this digibook useful?
HR leaders. The technology to understand data is developing fast. As sources of data proliferate—from enterprise systems to social media—our ability to understand people is moving into new dimensions. Analytics can put you ahead of this wave—riding it, not being submerged. C-level execs.
The new generation of database tools, data-gathering systems, and analytics, underpinned by emerging artificial intelligence technology, is going to give you more visibility of, and more insight into, your people than ever before. If you need to act fast, HR analytics will tell you where, how, and what the effect will be.
Line management. No technology is going to replace the judgment of a good manager. But the more you know about your teams, how they rate against benchmarks, how they feel, and what they care about, the better you can guide them to new territory.
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