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Sharjah

HR Analytics

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Published in: Business | Business Strategy | Business Studies
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HR analytics is defined as the analytics of human resources (employees), which embodies the entire life cycle of an employee such as recruitment, managing performance, incentives and employee engagement.

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  1. Module 3 Satisfactjon Decisiorv lmwati0? ?cv;bmlogy
  2. Course Plan Recruitment Analytics, On Boarding Analytics, Staffing Analytics, Performance & Skill Gap Analytics, Compensation & Benefit Analytics, Training & Learning Analytics, Promotion and Succession Planning Analytics, Compliance Analytics, Attrition & Retention Analytics
  3. What is HR Analytics HR analytics is defined as the analytics of human resources (employees), which embodies the entire life cycle of an employee such as recruitment, managing performance, incentives and employee engagement. THE HR ANALYTICS PROCESS Understanding the organization's business goals Identifying the rnetrics to be analyzed to achieve those goals Collecting and analyzing the relevant data Obtaining insights into this data Cornrnunicating how' this data irnpacts the organization
  4. 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. Purpose of HR Analytics To identify the need for new departments and positions. To determine which departments or positions can be reassigned or eliminated. To identify and quantify physical risks to employees in specific positions. To assign and delegate responsibility for tasks and goals. To investigate the effectiveness of performance management or performance-related pay in improving performance. To evaluate the effectiveness of learning and development activities. To measure the impact of organizational development interventions. To improve employee retention rates. To reduce absenteeism of employees. To evaluate the effectiveness of different sources of recruits. To provide the guidance on future HR strategy. 4
  5. 1. a. b. c. d. Levels of HR Analytics 3 levels of HR analytics Descriptive Analytics: The use of data to record a particular aspect of 1--IR and provide information on what has been happening to. This include: Basic Workforce Data: Demographic data, working arrangements, absence and sickness, turnover, health and safety, pay. People Development Data: learning programs, performance assessment, skills and qualifications. Perceptual Data: opinion surveys, focus group, exit interviews. Performance Data: financial, operational and customer data's.
  6. 2. 3. Levels of HR Analytics Multi-dimensional Analytics: The combination of different sets of data to establish any relationships between them. E.g. Regression Analysis Predictive Analytics: The most advanced form of HR analytics is to use the data to predict trends and therefore provide guidance on the future HR strategy. E.g. Recruitment tools predict high performers, and increasingly companies are able to predict which employee is likely to leave.
  7. 1. 2. Methods of HR Analytics Clustering: This method helps to investigate hidden group patterns. E.g. which common people characteristics can predict better sales performance ? Which cluster of recruitment sources can predict better people retention ? Driver Analysis: This method helps to understand hidden relationships betweens events or people or business characteristics. E.g. what is the impact of poor engagement on client satisfaction ? What is the impact of sales training on business revenue department?
  8. 3. 4. Methods of HR Analytics Risk Analytics: This method helps to understand probabilities or the likelihood of occurring events. E.g. which high performers are at risk to leave in the next 24 months? Will the reduction of training investments increase the risk of employee turno ver? Forecasting: This method will try to understand the future trend lines based on historical patterns. E.g. what will be the employee turnover in the coming 3, 6 or 12 months? What will be the typical first 6-months time-to-productivity trend line of a call center new comer without call center experience?
  9. 1. Tools for HR Analytics Optimize the interview process with - HireVue: LTE —/-/i/ceTue Heilo Awesome Candidate. weACor-ne to Best Job Ever ntervta•w Your Future Caree Ycx-z w" ccnsist 01: Questions About Minutes 171.67 MB Upload in which you useLi reasoning skills to handle)
  10. 2. Tools for HR Analytics - Bersin by Define clearly your benchmarks with Deloitte: Recogn ize the issues Advance HR capabilities Implement the solution Identify the plan Influence mindsets 10
  11. Tools for HR Analytics 3. Increase retention of Staff learning initiatives with - Skillport: A variety of learning modalities to match individual learning styles. Analytics, reporting, measurement. Extensive search and discovery. Personalized learning recommendations. Social and collaborative learning Mobile access through Skillsoft Learning App. Delivers a full complement of learning administration features. options and
  12. Tools for HR Analytics 4. Intelligently manage the talent with — Saba: • Saba provides companies across the globe with a cloud-based learning and talent management application designed to drive employee engagement, elevate skills and improve business productivity. • Saba provides traditional talent management features that include course building, learning management, performance management, goal tracking, succession planning, and recruiting. 12
  13. 1. 2. 3. 4. 5. Importance of HR Analytics Improved Hiring Decisions Good Training Better Insights Stable Retention Tracking Company Profitability
  14. RECRUITMENT ANALYTICS Recruitment Analytics is tracking, evaluating, gathering and analyzing employee and candidate statistics which help in making better hiring decisions.
  15. 1. 2. 3. 4. 5. 6. 7. Importance of Recruitment Analytics Finding the right candidate Refining sourcing Gathering performance data Analyze overall recruitment experience Help with profile tuning Identify best candidate sources Analyze market trends
  16. 1. 2. 3. 4. 5. 6. 7. 8. Metrics Used for Recruitment Analytics Qualified Candidates Time to Fill Offer Acceptance Rate Hires to Goal Quality of Hire Cost per Hire Diversity Hiring Metrics Retention Rates 16
  17. Metrics Used for Recruitment Analytics 1. Qualified Candidates: A candidate who is determined to be a good fit for a job after a phone interview can be labeled a qualified candidate. Qualified Candidates = Total Candidates Per Opening Who Move Past the Phone Screen Stage 2. Time to Fill: • Your time to fill metric simply adds up the total number of days an open job goes unfilled, and your average time to fill looks at all unfilled positions over a set time period. Time to Fill = Total Number of Days Job Is Available and Unfilled Average Time to Fill = Total Number of Days of Open Jobs I Total Number of Jobs Open 17
  18. Metrics Used for Recruitment Analytics 3. Offer Acceptance Rate: This recruitment metric tracks just how many of the offers you extend to candidates are accepted, and it usually kicks in after the application and interview processes have finished. Offer Acceptance Rate (%) = ( Number of Acceptances / Number of Offers ) x 10() (or) Offer-to-Acceptance Ratio Number of Acceptances 4. Hires to Goal: Number of Offers I • it's the total hires you need within a set time period to reach a predetermined hiring goal. Hires to Goal = Total New 1--lires / Hiring Goal 18
  19. Metrics Used for Recruitment Analytics 5. Quality to 1--lire: • Your quality of hire results should tell you the value that new hires bring to your firm. Quality of 1--lire (%) = (Job Performance + Ramp-up Time + Engagement + Cultural Fit) / N (All scored out of 100, N = number of indicators) Overall Quality of Hire (%) = [Avg. Quality of Hire score + (10() — Turnover Rate)] / 2 6. Cost Per Hire: The cost per hire recruitment metric adds up all the expenses that go towards hiring a new employee, and demonstrates the value of your recruitment methods. Cost per Hire ($) = [Total External Costs] + [Total Internal Costs] / Total Number of Hires 19
  20. Metrics Used for Recruitment Analytics 7. Diversity Hiring Metrics: Diversity metrics are important, and not just from a legal standpoint. Equal opportunity regulations prohibit discrimination in hiring based on race, color, religion, sex, pregnancy, national origin, age, disability or genetic information. 8. Retention Rates: Retention rate tracks the total employees who stay with your firm over a given time frame, out of the total number of employees you had when that period began. Retention Rate (%) = (Total Employees Still Employed at End of Period / Total Employees at Start of Period) x 10() 20
  21. ANALYTICS On-boarding Analytics Can be defined as the technique through which the new employee acquire knowledge, skills etc to become effective organizational member.
  22. 4 C's of On-Boarding Analytics Compliance Clarification Employee Selection Culture Connection Successful Onboarding 22
  23. 1. 2. 3. 4. 5. 6. 7. Metrics of On-Boarding Analytics Yield Ratios Orientation Costs New Hire Survey New Hire Separation Speed to Performance New Hire Engagement Program Effectiveness 23
  24. Metrics of On-Boarding Analytics 1. Yield Ratios: Yield ratios are usually used to measure how many candidates were hired from a total number of applications. Yield ratios show what percentage of candidates pass from one stage of the hiring process to another. Number of hirable candidates resultingfrom stage n Yield ratio of stage n = Total number of candidates who came in stage n
  25. Metrics of On-Boarding Analytics 2. Orientation Costs: Knowing the cost of orientation allows the company to make sure their resources are being used in the best way possible. Average orientation cost per employee = [(Time*Pay*Number)+Departmentl/Number Time = Amount of time spend in orientation Pay = Average hourly rate per employee Number = Total number of employees in orientation Department = Average HR department cost 25
  26. Metrics of On-Boarding Analytics 3. New 1--lire Survey: • In this process, a survey can be sent to employees at different times during the on-boarding process to gauge feedback. Below are 3 sample questions that can be asked. They could be formatted for a "yes or no" response or on a likert scale. 1. 2. 3. The manager was well prepared for the arrival on the first day at work. The work done today is the role that was explained during the recruitment process The materials provided at orientation, easy to follow or not? If not, what materials were not clear? 26
  27. Metrics of On-Boarding Analytics 4. New 1--lire Separation: Employee separation happens with all staff at some time. Whether it is through resignation or termination, it is critical HR staff effectively follow their organizations employee termination processes. 5. Speed to Performance: Managers should take care the following steps to get their new employees up to speed l. Make the experience personal 2. Expose them to company culture 3. Outline expectations 4. Provide feedback Check in regularly 5. 27
  28. Metrics of On-Boarding Analytics 6. New 1--lire Engagement: • On-boarding is all about getting new hires engaged. • Satisfied employees will keep the company afloat, but engaged employees will help the company grow. 7. Program Effectiveness: An effective on-boarding program goes way beyond the initial classroom training. • Running an extended program that integrates classroom learning with informal, extended on the job training takes effort, resources, and know-how. By utilizing these three measurements together one will gain a lot of information about the company's on-boarding process. 28
  29. Key steps to effective employee on-boarding 1. Have a clear on boarding process in place Preparation for on boarding a new employee needs to start well before they walk through the door. Be sure to: Help new employees prepare Provide a functioning workstation Arrange orientation Organize the necessary paperwork 29
  30. Key steps to effective employee on-boarding 2. Schedule the first day Help a new recruit to settle in quickly by making them feel welcome and relaxed with these tips: Announce the new hire with a welcome email to the team and/or company at the start of the day. Introduce the team to your new employee and guide them around the workplace to meet key people throughout the business. Show them around the workplace. 30
  31. Key steps to effective employee on-boarding 3. Organize training and mentoring Revisit goals and responsibilities • Schedule training Review mentoring opportunities 4. Help them settle into their role: • Successfully on boarding a new employee is not an overnight process • Take the time to observe them and ask questions - do they understand the business and their role? Facilitate any additional training that may be needed. • Don't overlook recognition. Keep the employee motivated and engaged by celebrating success.
  32. Staffing Analytics Analytics enable staffing firm to measure ROI, track the effectiveness of marketing campaigns, and make important business decisions.
  33. 1. 2. 3. 4. Role of Predictive Analytics in Staffing Talent Acquisition Talent Pipeline planning Job Response Optimization Customer Acquisition
  34. performance analytics Performance Analytics enables you to track, aggregate, and visualize key performance indicators over time, rather than reporting on a point in time.
  35. 1. 2. 3. 4. 5. 6. Metrics used for Performance Analytics Indicators Breakdowns Scorecards Dashboards Widgets Data collector 35
  36. Metrics used for Performance Analytics 1. Indicators: Indicators define a performance measurement taken at regular intervals of a business service, an activity, or organizational behavior. These performance measurements result in a series of indicator scores over time. 2. Breakdowns: Breakdowns enable you to group or filter indicator scores for more detailed analysis, such as to show separate scores for each assignment group. The values for each breakdown are called breakdown elements. Breakdowns are automated, manual, or external, depending on where these elements come from. 36
  37. Metrics used for Performance Analytics 3. Scorecards: Scorecards display data for a single indicator and enable you to perform detailed analysis of the indicator data. • Each indicator has an associated scorecard created automatically. 4. Dashboards: A dashboard can have multiple tabs and each tab can hold one or more widgets. 5. Widgets: A Performance Analytics widget ties an indicator to a visualization, such as a trend line, a set of columns, or a pie chart. Within the widget, you can filter or group indicator scores by breakdowns. 6. Data Collector: Performance Analytics uses scheduled jobs to collect and clean scores and snapshots, and enables you to manually set or import scores. 37
  38. 1. 2. 3. 4. 5. Importance of Performance Analytics Drive Performance Establish a single version of truth Realize fast time to value Align the organization with company goals Services quality 38
  39. N/A
  40. l. 2. 3. 4. Steps to develop a Skill Gap Analytics Identify Business Goals Collect data Interpret the data and make recommendations Prepare a training plan to address identified skill gaps in the current environment 40
  41. vvvvvvvvvvvvvvvvvv Compensation Analytics Compensation analytics focuses on optimizing the cost of a workforce to drive bottom-line growth.
  42. Compensation Analytics This branch of analytics helps organizations craft an employer brand that effectively communicates a winning employee value proposition. A value proposition that includes both financial and non- financial rewards. • In effect, compensation analytics enables HR leaders to reward high-performers adequately, to boost workplace morale, engagement, and retention.
  43. Methods used in Compensation Analytics 1. 2. 3. 4. 5. 6. 7. Market Data Comparison Labor Cost Analysis People Count Analysis Retention Analysis High Performer Analysis Sales Compensation Analysis Geographic Pay Analysis 43
  44. Training Analytics: Metrics to start with Analytics used to determine the extend to which the goals of training programs have been achieved
  45. Methods used for Training Analytics 1. Kirkpatrick Model: Level Results Impact Learning Reaction Did the training influence performance? Did the training change behaviour? Did learning transfer occur? Did the learners enjoy the training? 45
  46. Methods used for Training Analytics 2. CIRO Model: The Focus is on: 1. Content Evaluation If problem has learning solution. What would be objectives? 2. Input Evaluation Learning structure, media, & methods used 3. Reaction Evaluation Reactions of participants on training event 4. Outcome evaluation To which extent objectives achieved
  47. Methods used for Training Analytics 3. Cost-Benefit Analysis: 1 g 2 St g 3 g 4 • Determining Training Cost • Identify Potential Saving Results • Compute Potential Savings • Conduct Cost & Savings Benefits Comparison
  48. Methods used for Training Analytics 4. ROI in Training: collect Isolate the Effects of Training Identify Intangible Benefits Convert Data to Monetary Values Calculate ROI of Training Tabulate Program Costs 48
  49. Learning Analytics Learning analytics Ftudies the !mpact of training on trainees,
  50. 1. 2. 3. 4. 5. 6. 7. Importance of Learning Analytics Quality Assurance Intervention Identify At-risk Sub-groups Enable for the development and introduction of Adaptive Learning Foster a Data-Driven Mindset Increase Employee Motivation Hurdles and Opportunities 50
  51. Promotion Analytics It is used to determine whether a given employee will be successful if he is promoted to a higher level position.
  52. 1. 2. 3. Basis For Promotion On merit basis: Based on employee's skill, knowledge, ability, efficiency etc. On seniority basis: Based on the duration of service or experience at the same post. On merit-cum-seniority basis: Consider both employee's skills & experience. 52
  53. Metrics Used For Promotion Analytics 1. Revenue per employee = Total revenue Full time equivalent(FTE) [FTE equivalent to one employee working full time.] 2. Profit per FTE = Total profit FTE 3. Overtime per employee = Total hours of overtime FTE 4. Human capital ROI: Value of human capital i.e., knowledge, habits etc. 5. Absenteeism rate. 53
  54. Skills Required for Promotion analytics Technical Skills General Promotion knowledge • Statistics • Campaign Measurement • Online Analytics • Database Technology • Promotional Strategy, Targeting and Segmentation • Campaign Design and Management • Experience-Based Knowledge
  55. Succession Planning Analytics Predicting who is capable of succeeding an important position in the organization.
  56. Steps of Succession Planning Pre-planning Assessment One-on-one & group meeting CEO discussion Ongoing review 56
  57. l. 2. 3. 4. Importance of Succession Planning Analytics Understand the risk associated with probable successors identified for key high potential workers. Analyze the turnover details of portable successors. Track key high potential workers with and without succession plans. Evaluate effectiveness of the succession planning and management process based on the number of plans filled by successors identified for succession plans. 57
  58. Compliance Analytics Monitoring whether the company is obeying the rules & regulations outside the organization
  59. 1. 2. 3. 4. 5. Methods for Compliance Analytics Rules based monitoring: To identify the known frauds & compliance risks. Anomaly detection: Recognize new fraud & compliance risks. Network analysis: To identify potentially illegal activities inside the organization. Text analysis: To sense written documents for analysis. Visual analysis: To summarize the results for the stakeholders. 59
  60. Attrition Analytics Employees leaving an organization is called attrition 60
  61. Reasons For Employee Attrition Bad relationship with the employers. Bad relationships with coworkers. Less salary. • Unfair working times. The job did not meet expectations. • Feeling undervalued. Lack of proper coaching & feedback. Lack of growth opportunities. Bad company culture.
  62. How To Minimize Employee Attrition Hire the right people. Offer competitive pay & benefits. Motivate & praise the employees. Allow flexible timings. Give opportunities to learn new skills & knowledge.
  63. Retention Analytics Retention refers to how many employees stick around over a given period of time.
  64. Steps For Employee Retention Step l: Churn prediction: Create models to identify the employees at risk of leaving. Step 2: Attrition root cause: Identify the reason for attrition Step 3: Resignation segments: Compare how the resignation rate varies with respect to location, age groups, function etc.

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