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Talnt analytics

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HOW TALENT ANALYTICS CAN BE USED INii Human resource

Published in: Data & Analytics
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Talnt analytics

  1. 1. Big Data Analytics in HRM (Big Data Big Win)
  2. 2. INTRODUCTION TALENT ANAYLTICS Questions to Actions Talent Analytics is the application of statistics, technology, and expertise to large sets of people data which results in better decisions for an organization.
  3. 3. Need of Talent Analytics • It consider all data rather than limited to samples • Achieve better time to hire • Substantially improving Source of hire and quality of hire
  4. 4. Traditional method follow by the HR for hiring process • Examine the data collected on those high-performing incumbents • Hiring is done on the basics of sample data • Organizations typically source their hires based on highly subjective factors, such as evidence and the personal preferences of hiring managers
  5. 5. How talent analytics improves hiring Hire data for every current employee to get most accurate result Uses the whole of the data to discover insights Helps weed out questions that are not relevant to workplace Integrate the hiring tools to a far greater degree
  6. 6. • Searches for patterns in source of hire, identifying the common denominators in an entire group of successful employees • Talent analytics makes it possible for organizations to immediately begin hiring potential high performers without the need to rebuild the hiring tools
  7. 7. Hiring Questions That Should Be Addressed Through Talent Analytics • How effective is our selection process? • What new hire capabilities are we hiring that lead to early leadership success? • Will “new hire” be able to achieve “X” goals? •What assessment tool is the most valid predictor for potential? • What component of our selection process is reducing early career turnover? • What is the time to productivity? • Does performance on the assessment predict employee engagement? •What assessment results can we use in onboarding to ensure new hire success?
  8. 8. Six Uses of Talent Analytics • Human-capital facts are a single version of the truth regarding individual performance and enterprise-level data such as head count, contingent labor use, turnover, and recruiting. • Analytical HR collects or segments HR data to gain insights into specific departments or functions. • Workforce forecasts analyze turnover, succession planning, and business opportunity data to identify potential shortages or excesses of key capabilities long before they happen.
  9. 9. 4- Human-capital investment analysis helps an organization understand which actions have the greatest impact on business performance. 5- The talent value model addresses questions like “Why do employees choose to stay with our company?” A company can use analytics to calculate what employees value most and then create a model that will boost retention rates. 6- The talent supply chain helps companies make decisions in real time about talent-related demands—from optimizing a retail store’s next-day work schedules, on the basis of predicted receipts and individuals’ sales performance patterns, to forecasting inbound call-center volume and allowing hourly staff members to leave early if it’s expected to drop.
  10. 10. Why Do We Need To Embrace The Big Data Trend In HR
  11. 11. 1.Better Insight  Serves as a window to employees professional lives. Not only gain more insights on employees, but boost individual motivation and overall engagement 2.Better Retention  Opportunity to learn why employees leave or they stay  Tools like employee statisfaction survey , team assessment , social media , etc  Lower employee engagement as well as opportunities to boost engagement
  12. 12. 3.Better Training  Measuring the potential and effectiveness of training initiatives  Should focus on obtaining data releated to training program  Conducting regular performance appraisal 4.Better Hires  More analytical and strategical  Don’t rely on repetitive resume  Learn more about potential hires
  13. 13. Conclusion • Big data is imperative for business • Uses of HR analytics: i. HR predictive analysis ii. HR supply management iii. Employee satisfaction iv. Finding HR time and sources v. Integration of all departments vi. Updating with latest HR tools
  14. 14. • HR analytics should focus on solving current business problems , and then on improvement of HR processes • Integration of HR analytics team with other functional teams is important • HR analytics is a journey
  15. 15. THANK YOU By Manish Bisht RollNo.217 Kajal Pradhan Roll No.232 Tania Kaul Roll No.234 Mona Prakash Roll No.182 Kyondo Samuel Roll No.226 Madhumita Saha Roll No.185

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