HR Analytics, Done Right


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A brief overview of the HR Analysis methods of Trendwise Analytics.

Published in: Technology, Business

HR Analytics, Done Right

  1. 1. Trendwise Analytics HR Analytics & Reporting Trendwise Analytics
  2. 2. Trendwise Analytics Contents  About Trendwise analytics  Background and objectives  Need of HR analytics & reporting  Trendwise Analytics – HR analytics capabilities  HR Reporting & Analytics Level-1  Dashboards & Descriptive analysis  How to use Level -1 analysis for making business decisions  HR Reporting & Analytics Level-2  Derived Metrics & Ratios  How to use Level -2 analysis for making business decisions  HR Reporting & Analytics Level-3  Attrition forecasting  Attrition segmentation & Hotspot identification  Top performer segmentation  Compensation analysis & Fair compensation tool  Voice of employee analysis & drivers of employee satisfaction
  3. 3. Trendwise Analytics About Trendwise analytics • Trendwise is formed by a group of technocrats whose experiences from the industry forms a strong foundation of the company. The founder members of Trendwise had been a part of early CRM evolution and hence establishes an authority over CRM analytics. Our focus would be set on the newer aspects of analytics which is yet to come of age. While Hadoop, Cloud Computing, BigData analytics for the technological basis for us, our domain focus is on predictive aspect of analytics which would create insights for our customers like never before. Overview • To be one of the most valuable companies in the area of advanced analytics with a strong global presence with a wide client base for our products and solutions. Vision • To develop analytics tools and solutions for handling big, unstructured data for creating business insights. The offerings would be targeted to specific business areas and industry streams. Also to provide support and services to our customers on our products and solutions. Mission
  4. 4. Trendwise Analytics Services and Technology • CRM Analytics • HR Analytics • Big Data Analysis (leveraging Hadoop) • Social Media Analytics • Verbatim Analysis/Text analyzer • Advanced Analytics and Predictive modeling • Mobility and Mobile Analytics Services • SAS • R • Tableau • Jasper soft • Mysql PHP • Hadoop Technology and Tools
  5. 5. Trendwise Analytics Background and objectives Need of HR analytics & reporting  Many organizations have high quality HR data (residing with a multitude of systems, such as the HRMS, performance management, learning, compensation, survey, etc.) but still struggle to use it effectively to predict workforce trends, minimize risks and maximize returns.  The costs of attrition, poor hiring, sub-optimal compensation, keeping below par employees, bad training & learning strategies are just too high  Data-driven insights to make decisions are always better than judgmental (subjective) HR practices in terms of  how to recruit  whom to hire  how to onboard and train employees  how they keep employees informed and engaged through their tenure with the organization Hence regular tracking and prediction of crucial HR metrics is indispensable Objectives  Predict attrition especially amongst high performers.  Forecast the right fitment for aspiring employee  Predict how compensation values will pan out.  Establish linkages between Employee engagement score and C-Sat scores(Work in progress)
  6. 6. Trendwise Analytics Trendwise Analytics – HR analytics capabilities • Reporting of basic metrics, their frequencies & percentages by various cuts followed by key highlights. These can be monthly, quarterly, half yearly tracking reports • Tool: SAS/REPORT • Techniques: frequencies , means, percentages etc., Level-1 Descriptive analysis • Derivation of some HR operational metrics which will help us in tracking the efficiency of HR functions • Tool: SAS • Techniques: means, variance, control limits, ratios, percentages etc., Level-2 Operational metrics • Predictive analysis based on historical HR data. Attrition forecasting, performance management, compensation analysis, survey analytics, new hire strategies etc., • Tool: SAS BASE, SAS E-miner, Excel • Techniques: Regression analysis, Time series analysis, cluster analysis, CHAID etc., Level-3 Predictive analysis Three levels of HR analytics and reporting
  7. 7. Trendwise Analytics HR Reporting and Analytics: Level-1 HR Dashboards & Descriptive analysis – Basic frequencies & percentages of some HR related variables Head count and Attrition numbers by Region ,Country, Business, Process, Service centers, Grade of service ,Age ,Gender , Ethnicity, Tenure and Special segment (e.g. Ratings/Talents) Training and learning dashboards, Program Enrollment / Registration & Completion Performance tracking reports , Absences ,Event Grievances / Disciplinary Actions Employee Appraisal / Review / Accomplishments Requisition tracking, Vacancy / skills matching / competencies Payroll related reports, Injury illness, Time and labor All the above reports will generated using SAS procedures like PROC FREQ, UNIVARAITE, MEANS etc.,. Automation of all these reports using SAS/REPORT to generate monthly dashboards in desired format
  8. 8. Trendwise Analytics How to use Level-1 analysis? Reports 2010 Q1 2010 Q2 2010 Q3 2010 Q4 2011 Q1 2011 Q2 2011 Q3 Involuntary Turnover Voluntary Turnover Better Compensation Higher Education Unsatisfactory performance Company HR policies Shifting location Retirement Voluntary Turnover Involuntary Turnover Insights Action points Turnover rates are above acceptable levels in last two quarters Compensation and location shift are two main reasons Revise compensation strategies, time to concentrate on incentives and employee retention strategies
  9. 9. Trendwise Analytics HR Reporting and Analytics: Level-2 HR metrics and ratios–HR operational metrics will help us tracking the efficiency of various functions in HR department. We can define control limits to each of these metrics and track them on regular basis Turnover ratio (Number of attritions in a year)/ (Average head count in a year) Joiners rate(Accession ratio) (Number of joiners in a year)/ (Average head count in a year) Stability index (Number of FTE with >3 years tenure in current organization)/ (Current head count) Low performer management Denominator : Employees with low performance rating in last year Numerator: Distribution of above employees across Improved performance rating in current year Same performance rating in current year Leavers in current year Promotion ratio (Number of promotions in a period of time)/ (Average head count over same period) A high number indicates hidden costs and delays, which damage productivity Joiners Rate: The ratio of new and replacement hires as the percentage of total employment Metric Insights Action points Focus on new hire and employee retention strategies How to use Level-2 analysis?
  10. 10. Trendwise Analytics  Availability historical HR data gives us lot of scope to analyze past patterns and predict future behaviors  Attrition forecasting : Given historical attrition trends, we can estimate future attrition percentages up to a certain confidence level  Attrition Segmentation : Segmentation will be done based on employee profiles & attrition rates. Most impacting employee characteristics on attrition will be identified  Top performer segmentation: Segmentation of employees based on their profile data and performance indices. This will help us to identify top performing employees and their characteristics  Compensation Analysis and compensation tool: A tool that predicts optimal compensation for a given employee based on his capabilities, company policies, market conditions.  New hire strategies: New hire strategies will be build by performing attrition segmentation in combination with top performer analysis  Voice of employee analysis & drivers of employee satisfaction HR Reporting and Analytics: Level-3
  11. 11. Trendwise Analytics HR Reporting and Analytics: Level-3 Attrition forecasting Predicting/forecasting near future attrition numbers by identifying patterns in historical attrition data 4.3% 2.5% 3.5% 4.5% 4.1% 4.3% 4.4% 4.6% 4.8% 4.9%5.1% 0.0% 2.0% 4.0% 6.0% Attrition% illustration
  12. 12. Trendwise Analytics HR Reporting and Analytics: Level-3 Attrition segmentation Identifying segments with high/low attrition rates and employee characteristics in each segment Over all Head count (Attrition 15%) Age <28(Attrition20%) Tenure with the company <1.5 years(30%) Tier-1 University/college( 35%) Other than tier- 1(28%) Tenure with company 1.5-3 years(20%) Tenure with company >3 years(10%) Age >28(Attrition9%) Tenure with company < 3 years(14%) Tenure with company >3 years(6%) Tier-1 University/College( 10%) Other than tier-1 college(5%)  FTE Segment with highest Attrition % FTE Segment with least Attrition % illustration
  13. 13. Trendwise Analytics HR Reporting and Analytics: Level-3 Top performer segmentation Identifying High /Low performing employee segments and their characteristics (subjected to availability of necessary performance measures) Over all FTE population (20% high performers) Age <28(30% high performers) Tenure with the company >3 years(40%) Tier-1 University/college( 55%) Other than tier- 1(25%) Tenure with company 1.5-3 years(30%) Tenure with company < 1.5 years(20%) Age >28(18% high performers) Tenure with company > 3 years(22%) Tenure with company < 3 years(14%) Tier-1 University/College( 18%) Other than tier-1 college(10%)  FTE Segment with High % of top performers FTE Segment with least % top performers illustration
  14. 14. Trendwise Analytics HR Reporting and Analytics: Level-3 Fair compensation tool Project Stage Description Stage-1 Divide overall compensation into four major components; Company, Employee, Market and general followed by identification of top drivers in each quadrant Stage-2 Study historical data to find the relation between compensation and attributes in each quadrant , using SAS Stage-3 Use predictive analysis in SAS(multiple linear regression) to quantify the relation between compensation and attributes Stage-4 Using above models, build a fair compensation prediction tool that covers all the relevant attributes from each quadrant Stage-5 Use the results obtained from predictive analysis to estimate the optimal compensation for a given employee Approach List main drivers of compensation, find the impact of each of these on compensation using historical data, use these models and build a tool that predicts compensation
  15. 15. Trendwise Analytics HR Reporting and Analytics: Level-3 Fair compensation tool & algorithm gap between Maximum and minimum salary Company 30% Employee 35% Market 25% Others 10% Divided into four quadrants based on weights Budget Urgency Impact Identifying top attributes in each quadrants Company component in final compensation Assign weights to each of these components based on statistical analysis of historical data Final Compensation Do the same excessive for four quadrants
  16. 16. Trendwise Analytics HR Reporting and Analytics: Level-3 Voice of employee survey analysis & drivers of satisfaction  Reporting: Descriptive statistics like overall satisfaction, satisfaction by various cuts(regions, processes etc.,)  Driver Analysis (part-1): Identification of main drivers of employee satisfaction based on survey data  E.g: If we have five sub questions in survey, we try to identify the top two factors which are impacting overall employee satisfaction. We find out these by using multivariate logistics regression  Driver Analysis (part-2): Merging of survey responders data with employee profile and performance data. Identification of main drivers of satisfaction from non surveyed variables  E.g ; We consider variables like employee tenure with the company, employee performance, skill sets & some other demographic variables to see weather one or more of these are impacting on overall employee satisfaction  Analysis of verbatim comments:  Descriptive analysis of positive , negative and neutral comments  Identification of frequently mentioned topics and their positive negative frequencies
  17. 17. Trendwise Analytics Appendix
  18. 18. Trendwise Analytics Predictive Analysis using SAS- Examples with dummy data Attrition forecasting using SAS Attrition segmentation using SAS
  19. 19. Trendwise Analytics