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HRM Metrics and Analytics

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Human Resources Management (HRM) Metrics and Analytics - best practice principles, process, tools and models

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HRM Metrics and Analytics

  1. 1. HUMAN RESOURCES MANAGEMENT (HRM) METRICS & ANALYTICS CHARLES COTTER Ph.D candidate, MBA, B.A (Hons), B.A CITY LODGE HOTEL, FOURWAYS 22-25 AUGUST 2017 www.slideshare.net/CharlesCotter
  2. 2. 4-DAY, TRAINING PROGRAMME OVERVIEW • Introduction to and the evolution of HRM metrics • Defining the fundamental concepts • Applying a strategic mind-set and –approach to HRM Metrics • Building a business case for HRM Metrics and Analytics – benefits and challenges • Identifying best practice and critical success factors • Applying the 5-step, HRM Analytics process • Case studies and Reading Articles
  3. 3. • What type of HRM Metrics does your organization currently utilize? • Describe the organizational impact, level of maturity and credibility of these HRM Metrics • What does your organizational HRM Metrics architecture look like? • What is the current degree of HRM practitioner competency of HRM metrics/analytics? • Review the benefits of HR Metrics. Is there a business case for applying HR Metrics?
  4. 4. 10-POINT FOUNDATION AND “STARTER-PACK” FOR STRATEGIC HRM METRICS #1: Adopt a strategic mindset #2:Change management must run parallel to HRM Metrics in “business unusual” environment #3: Streamline and systematic HRM metrics process #4: HRM Metrics is not a “desktop” exercise #5: Adopt a measurement culture & build capacity & skills for digital literacy
  5. 5. 10-POINT FOUNDATION AND “STARTER-PACK” FOR STRATEGIC HRM METRICS #6: Re-inject scientific principles, processes and tools & credibility into HRM Metrics e.g. 3 E’s #7: Drill down & segment HRM metrics #8: Apply the 4 C’s to HRM Metrics Reporting #9: Don’t adopt a “Big Bang” approach – start small, think big and scale up #10: Automation - utilize a 4-G digital data analysis solution
  6. 6. THE FUTURE OF HRM METRICS & ANALYTICS? “HRM will have to migrate from the fundamentals of people science to the complexities of data science.”
  7. 7. HRM METRICS/ANALYTICS TASK TEAM – 2017?
  8. 8. INTRODUCTORY ACTIVITY • Individual activity: • Complete the following statement by inserting one word only. As a HR Manager, in order to effectively apply and utilize HRM analytics, I need to/to be……………………………………………… • Jot this word down and find other learners who have written down the same word. • Write this word down on the flip-chart. • Each learner will have the opportunity to explain their choice of word.
  9. 9. PH.D. RESEARCH – STRATEGIC HRM/D FACTORS (COTTER, 2017) • N = 465 (global) • Selected deficient factors (on 4-point scale):  #1: Curating modern learning experience: 2.77  #2: HRM/D Architecture: 2.82  #3: Top management support: 2.83  #4: Enhanced skills set of HRM/D practitioners: 2.89  #5: Future-proofing the organization: 2.91  #6: Strategic mindset of HRM/D: 2.97 • HRM/D Capability gap index (differential between compliance and importance):  #1: Enhanced skills set of HRM/D practitioners: -0.44  #2: Curating modern learning experience: -0.42  #3: HRM/D Architecture: -0.38  #4: Strategic mindset of HRM/D: -0.31  #5: Future-proofing the organization: -0.31
  10. 10. • Metrics are simply measurements. Metrics track activity, but don’t necessarily show a causal relationship. • HRM Metrics - Measurements used to determine the value and effectiveness of HR strategies. • Differentiation between People and HRM Measures • Human capital analytics examine the effect of HRM metrics on organizational performance. • In more general terms, analytics look for patterns of similarity between metrics. By using analytics over time, HRM can become predictive. DEFINING THE FUNDAMENTAL CONCEPTS
  11. 11. STRATEGIC PERSPECTIVE – HRM METRICS/ANALYTICS Strategic HRM and correlation to metrics/analytics The Balanced Business Scorecard Strategy Mapping HRM Scorecard: • Key people measures from the organization’s scorecard • The second class of measures should be the HR measures Linking business strategy to personal objectives
  12. 12. BALANCED SCORECARD
  13. 13. EXAMPLE: STRATEGY MAP
  14. 14. EXAMPLE: STRATEGY MAP
  15. 15. STRATEGIC HRM VALUE CHAIN
  16. 16. LEARNING ACTIVITY 1 • Group discussion: • Evaluate to what extent your current HRM Analytics processes and practices comply with the principles of strategic management i.e. use of Balanced Scorecard and HR Scorecard methodologies and Strategy Mapping etc. • Identify gaps and recommend improvement strategies.
  17. 17. BUILDING A BUSINESS CASE FOR HRM METRICS/ANALYTICS • Introduction to the organizational performance impact of HRM metrics and analytics • Value of HRM M-E-T-R-I-C-S • Strategic business partnering
  18. 18. ORGANIZATIONAL IMPACT OF HRM METRICS/ANALYTICS • According to a HRO Today Institute study (2013), number-crunchers rule the HR roost - companies that use employee-performance data to improve ongoing talent acquisition outperform their competition 58% of the time and by margins of up to 200%. • According to the CIPD, HR analytics enables HR managers and teams to understand more about the people in their organization, how they’re performing and how they’re creating value for the organization. • In turn, this enables HR practitioners and business leaders to make better business decisions. • It’s also the main way that HR teams can demonstrate the impact that HR policies and processes are having on the organization. • Business managers are increasingly interested in how to use HR concepts more effectively, and so HR analytics is an important way in which HR teams can evaluate and improve people and business performance.
  19. 19. THE VALUE OF M-E-T-R-I-C-S • Measure the contribution of employees and predict the quality of performance • Explore evidence-based relationships between employee engagement and learning and development • Tap into new sources of competitive intelligence and stay ahead of the pack • Retain and engage your organization’s top talent by utilizing tools needed to anticipate future success • Implement process mapping across HR for hiring and inducting new employees • Communicate the most relevant and actionable data to top management • Strategize optimal measurement methodologies and marshal resources that create value for customers, investors, executives, and employees
  20. 20. BENEFITS OF HRM METRICS • Metrics help you ensure that you are meeting your goals and customer needs • Metrics help you focus • Metrics tell you where to spend your money • Metrics tell you what to stop doing • Metrics eliminate confusion – “What you measure and reward takes away all doubt about what is important” • They help push continuous improvement
  21. 21. • There is a low degree of awareness of the impact of HRM programs whether, positive or negative, because HR leaders have not been delivering metrics that show the value of their programs or investments. • Quantification issue - metrics enable leaders and decision makers in organizations towards more efficient and better delivery of HR services • “Based on corporate culture, organizational values and strategic business goals and objectives, human capital measures indicate the health of the organization.” (Lockwood, 2006) • If HR professionals don’t measure their function’s effectiveness and providing decision-making leaders the data they need, HR will continue to be undermined and eventually sidelined when it comes to having a seat at the table – strategic business partner. IMPERATIVE OF HRM METRICS
  22. 22. BENEFITS OF HRM METRICS • Metrics allow you to come across as an expert • Distributing metrics can change individual behaviour • Metrics are superior to culture in changing the behaviour of your managers • Metrics can help to improve your relationship with the CFO and CIO • Metrics can build coordination/cooperation • Metrics can help to build self-confidence
  23. 23. BENEFITS OF HRM METRICS • Using metrics sends the message that you are “new school” • Metrics tell you what to reward • Modern ERP and ATS systems make it easier • Metrics can allow HR to provide evidence of its strategic impact • Metrics can demonstrate the rand impact of HR programs • Create a HRM business value chain
  24. 24. LEARNING ACTIVITY 2 • Group discussion: • By means of a cost- benefit analysis, determine if there’s a viable, feasible and sustainable business case for HRM Metrics and Analytics.
  25. 25. CRITICAL SUCCESS FACTORS AND CHALLENGES OF HRM METRICS AND ANALYTICS • Best practice principles • Critical success factors • Top vendors for HRM analytics • Constraints and Criticisms
  26. 26. 10 BEST PRACTICE PRINCIPLES OF HRM METRICS/ANALYTICS • #1: Top performing companies drill down metrics to a deeper level and communicate to decision-makers more effectively. • #2: Data becomes part of a “holistic solution” The data is more accessible and used by more people than with lower-performing companies. • #3: Given that it’s an integrated solution, it has fewer inconsistencies and offers greater reliability of data. • #4: Top performers have a dashboard of Key Performance Indicators KPIs). • #5: They have a centralized, standardized, cloud-based depository that is distributable and searchable by standard key words and search strings.
  27. 27. 10 BEST PRACTICE PRINCIPLES OF HRM METRICS/ANALYTICS • #6: Top performers will have records that include hyperlinks—such as a link to someone’s LinkedIn profile—for real time updating. • #7: They have established a dashboard that summarizes the data into meaningful segments along with overall statistics. • #8: Metrics are most commonly reported on a monthly basis or quarterly basis, and then rolled up into a year-end report. • #9: Top performers had a specific approach to metrics: What separated the top performers from everyone else was not only what the metrics are, but how well the data was segmented or drilled down. • #10: A similar best practice is to deliver metrics that roll up to specific business units and divisions.
  28. 28. CRITICAL SUCCESS FACTORS FOR HRM METRICS/ANALYTICS • Showing HR's real value • Knowing how to interpret the results about the status of human capital in a meaningful manner. • If measurement, assessment and evaluation are to play a part in achieving sustainable organization performance, they should be impact-oriented, forward-looking and focused on the entire HR system, not just on individual HR practices. • The importance of HR capability • Guarding against point-in-time measurements only
  29. 29. HOW DO I MAKE A SUCCESS OF MY HRM METRICS? • A point-in-time measurement very often appears to be meaningless, unless you can compare it to a set standard or benchmark, and/or view its position in a trend that may be emerging. Put it in the right context Asking the right questions Framing of my results Reports the complete story Always strive for improvement
  30. 30. HOW TO USE HRM METRICS EFFECTIVELY? • Measure what is important • Involve Key Stakeholders • Work out the implications • Drill down to meaningful chunks • Convince and Influence • Dig deeper and explore the root causes • Set achievable goals for improvement • Own the goals in partnership with the line • Ensure action takes place as a result • Keep the momentum going
  31. 31. TOP VENDORS FOR HRM METRICS/ANALYTICS • The real leaders in analytics are:  Oracle  SAP • They have the most sophisticated and integrated analytics solutions • In terms of smaller vendors the frontrunners are:  SumTotal Systems  PeopleFluent • The real value is in providing actionable information and recommendations. • Top performers are more likely to ask themselves one vital question: What will the CEO or CFO do as a result of learning this information?
  32. 32. DEFICIENCIES IN HRM METRICS/ANALYTICS Logic Analytics Measures Process
  33. 33. COMMON ERRORS WITH HRM METRICS/ANALYTICS • One of the biggest mistakes that are so often reported is TOO MANY MEASURES - Developing more metrics than it is feasible to maintain and utilize • Developing and implementing HR metrics in a vacuum • The Top 20 Major Faults with Most HR Metric Approaches according to Sullivan (refer to pages 37-45) • “HR teams are not very analytical in their thinking yet. That is holding them back from doing more data-driven decision making.” (Bersin) • Over-reliance on Spreadsheets
  34. 34. Source: The State of Workforce Analytics and Planning 2014 Survey Report for workforce metrics and analytics - With low satisfaction rates
  35. 35. Source: Visier WFA Usage Survey, 2012 SURVEY - AREAS TO IMPROVE TO EXPAND WORKFORCE ANALYTICS CAPABILITIES
  36. 36. Is HRM
  37. 37. LEARNING ACTIVITY 3 • Group discussion: • By referring to the best practice principles, critical success factors and expert criticism, evaluate your organization’s current degree of HRM Analytics maturity/sophistication. • Identify gaps and recommend improvement strategies.
  38. 38. HRM ANALYTICS MATURITY MODEL (BERSIN BY DELOITTE)
  39. 39. Source: The State of Workforce Analytics and Planning 2014 Survey Report
  40. 40. Source: The State of Workforce Analytics and Planning 2014 Survey Report
  41. 41. TRANSFORMING HRM TO A DATA SCIENCE-DRIVEN FUNCTION
  42. 42. HRM ANALYTICS PROCESS
  43. 43. HRM METRICS PROCESS – BASIC MODEL
  44. 44. HRM METRICS AND ANALYTICS PROCESS
  45. 45. 5-STEP HRM ANALYTICS PROCESS • Step 1: Identify where HRM can make a strategic impact in the organization • Step 2: Develop appropriate metrics around these areas • Step 3: Obtain data relating to relevant metrics • Step 4: Draw out insight from the data • Step 5: Project and take action to communicate metrics and related insights information to provide a robust basis for strategic change and improvement
  46. 46. THE 5 E’s OF HRM ANALYTICS • Exploration • Examination • Extraction • Evaluation • Extrapolation
  47. 47. STEP 1: IDENTIFYING WHERE HRM CAN MAKE A STRATEGIC IMPACT (EXPLORATION) • This process step focuses on determining the areas where HRM can make a strategic impact within the organizational context. • It enables HR management team to identify priority areas for measurement which are aligned with organizational goals and strategies. • Identify capability opportunities or problem areas from a business partner perspective. • Sources for information collection, retrieval and analysis.
  48. 48. SOURCES FOR INFORMATION COLLECTION, RETRIEVAL AND ANALYSIS • Employee and management surveys and interviews (for employee contentment, communications, rewards system etc.) • Performance appraisals (to measure productivity, attendance) • HR records (to track communications, turnover, recruiting efficiency, retention, promotions, and succession planning) • Employee files (to research productivity, attendance, training etc.)
  49. 49. STEP 1: EXPLORATION • A critical first step is to ensure that HRM is measuring the right things. • The design and development of relevant HR metrics requires reflection and discussion in order to determine what it takes for the organization to succeed and to understand how HR can add value. • Three issues underpin effective measurement (CIPD, 2011):  Aligning measurement with goals  Take a business partner perspective  Adding value by focusing on building capability • Identify organizational burning issues • Identify industry, market and macro-environment Disruptors, trends and patterns
  50. 50. STEP 2: SELECTING APPROPRIATE METRICS FROM WHICH ORGANIZATIONAL INSIGHTS CAN BE DRAWN (EXAMINATION) • HRM Measures:  Efficiency (10%) – traditional  Effectiveness (20%) – transactional  Impact (70%) – transformational • Categories of HRM Metrics:  First Tier (most valued)  Second Tier (lesser valued) • Commonly used HRM Metrics • Refer to Annexure A: HRM Scorecard Template (page 74); Annexure B: Comprehensive HRM Metrics (pages 75- 114) and Annexure B: HRM Effectiveness Metrics (pages 115-123)
  51. 51. STEP 2: EXAMINATION - HRM MEASURES
  52. 52. BROAD CATEGORIES OF HRM MEASURES  Workforce Demographics  HR Efficiency  Remuneration  Skills Development, Training & Education  Productivity  Provisioning and Recruitment  Risk Analysis  Staff Retention
  53. 53. FREQUENTLY USED HRM METRICS (PWC)
  54. 54. 10 TYPICAL STATISTICS OBTAINED IN COMPILING HRM METRICS  Revenue factor, which is company total revenue divided by the amount of full time employees  Human capital value added (revenue minus operating expense and cost of compensation/benefit divided by the total amount of full time employees)  Human capital return on investment: Revenue minus operating expenses and cost of compensation benefit divided by cost of compensation/benefit  Total compensation revenue ratio which is cost of compensation/benefit divided by revenue  Labour cost revenue ratio, which is cost of compensation/benefit plus other employee costs (bonuses, mileage paid, incentives) divided by revenue
  55. 55. 10 TYPICAL STATISTICS OBTAINED IN COMPILING HRM METRICS  Training investment factor equals the total cost of training divided by total amount of training attendees  Cost per hire, which includes advertising, agency fees, relocation, and others divided by operating expenses  Health care costs per employee (total health care cost divided by total amount of employees)  Turnover costs, which is equal to hiring costs plus training costs plus other costs (turnover rate during first year of employment is key)  Voluntary separation rate is the total number of people who quit or retired divided by the total amount of employees
  56. 56. Present x Productive  Productivity Q: Are your employees contributing to the success of the organisation. Are you connecting human capital & business measures. ? Productivity measures on an annual and a quarterly basis ? Compare to national averages Specific metrics -  Return on Human Capital Investment  Revenue per Full-Time Equivalent (FTE)  Profit per FTE Critical HR Measures - forTrue Business Impact
  57. 57. Critical HR Measures - forTrue Business Impact Time to fill vacancy x Quality of hire  Recruitment Effectiveness Q: Are you recruiting new talent of a high calibre. Are they staying. Are they performing. ? Business-impact shortfalls in capacity ? Consistently increasing organization’s performance through improved talent Specific metrics -  Vacancy Rate  FirstYearTurnover Rate  New Hire Performance  Time to Fill
  58. 58. RECRUITMENT METRICS
  59. 59. Critical HR Measures - forTrue Business Impact Rate ofTurnover x Retention of critical top talent  Critical Talent Retention Q: Is your top talent / your vitally important workers / your competitive advantage – resigning, or at risk of resigning, at a greater rate than your less crucial employees. ? Overall tenure trends ? Career development Specific metrics -  Resignation Rate  Resignation Rate ofTop Performers  Promotion Rate and PromotionWaitTime  Engagement Index  Market Compensation Ratio
  60. 60. ENGAGEMENT’S EFFECT ON 9 KEY PERFORMANCE INDICATORS
  61. 61. 5 STEPS TO FIND THE RIGHT MEASURES
  62. 62. LEARNING ACTIVITY 4 • Group discussion: • Apply step 1 (Exploration) and step 2 (Examination) of the HRM Analytics process to a defined organization. • With step 2, refer to Annexures A, B and C for guidelines.
  63. 63. AGREE OR DISAGREE? WHY?
  64. 64. STEP 3: DATA COLLECTION CRITERIA – 3 E’s • Data collection is the process of gathering and measuring information on targeted variables in an established systematic fashion, which then enables one to answer relevant questions and evaluate outcomes.  Evidentiary  Empirical  Ethical
  65. 65. HindSIGHT InSIGHT ForeSIGHT Gather Data and Report Make sense of data by Monitoring and Analysis Develop Predictive Models Akshay Raje, Director, Fab.com
  66. 66. STEP 3: OBTAIN DATA RELATING TO RELEVANT METRICS (EXTRACTION) The top performing companies were using a variety of drilled-down metrics, having the people to analyze them, and communicating them effectively. This process step focuses on how HRM can most effectively communicate the insights drawn from metrics to inform action and hence enable HRM to deliver maximum strategic impact. Effective decision- making, based on robust measures and metrics, therefore, requires HR professionals to think carefully about the relationships that need to be established to enable appropriate information-sharing of these insights.
  67. 67. STEP 3: EXTRACTION – PROCESS STEPS • #1: There is the initial “harvesting” or gathering of unstructured data from the web. • #2: The normalization stage—preparing harvested data for analysis. Normally, a relational database such as MySQL is used, but NoSQL can also be used. • #3: The data is given additional structure with metadata, or tagging. Analytics can then be presented through a dashboard. • The process of collecting and updating the data from the myriad of internet sources has to be automated. Advanced Programming Interfaces (APIs) can enable different digital platforms to share dynamic data and feed it into other applications, such as a company’s own database.
  68. 68. STEP 3: EXTRACTION – CHALLENGES CONFRONTED • Struggling to use unstructured data • Difficulty tying talent acquisition data to business results • Problems with storing, retrieving and integrating data • There is rarely a systematic approach to integrating disparate systems. Legacy data systems often don’t talk to each other. There are missing links between ATS and HRIS systems. • The data exchange is often clumsy at best, requiring rekeying of data and manual interventions. • The successful transfer of data from multiple sources, such as an ATS, a recruiting site or a social network with an HRIS System is the most problematic part. • Failure to get the most of ATS
  69. 69. Source: The State of Workforce Analytics and Planning 2014 Survey Report
  70. 70. Source: The State of Workforce Analytics and Planning 2014 Survey Report
  71. 71. STEP 4: DRAWING OUT INSIGHTS FROM DATA (EVALUATION) • The HRM function and measurement capability • HR professionals have long been data collectors, amassing and keeping track of employees’ personal information, salary rates and the annual number of retirements. But to grasp the potential of HR analytics, HR managers need to become data interpreters. • Top performing companies invest in personnel who have analytic and process-oriented capabilities, those people who can install the necessary methodological disciplines necessary to use the information effectively. • Identify root causes and cause-effect linkages and -relationships • Action planning – interventions and solutions • Data mining is a process used by companies to turn raw data into useful information.
  72. 72. DATA ANALYSIS • Data analysis involves critical analysis and interpretation of figures and numbers, and attempts to find rationale behind the emergence of main findings. • In data analysis, the researcher is expected to turn raw numbers into meaningful data through the application of rational and critical thinking. The same figure within data set can be interpreted in many different ways; therefore it is important to apply fair and careful judgment. • Three popular quantitative data analysis software, namely: Microsoft Excel, Microsoft Access and SPSS.
  73. 73. DMAIC RCA PROCESS (ILLUSTRATION)
  74. 74. CAUSE EFFECT/FISHBONE DIAGRAM
  75. 75. 5-WHY ANALYSIS
  76. 76. HRM ACTION PLAN (INTERVENTION) TEMPLATE
  77. 77. LEARNING ACTIVITY 5 • Group discussion: • Apply steps 3 (Extraction) and 4 (Evaluation) of the HRM Analytics process to a defined organization.
  78. 78. STEP 5: PROJECT AND TAKE ACTION TO COMMUNICATE METRICS AND RELATED INSIGHTS INFORMATION TO PROVIDE A ROBUST BASIS FOR STRATEGIC CHANGE AND IMPROVEMENT (EXTRAPOLATION) • Projection of data – forecasting (PREDICTIVE ANALYTICS) • To communicate HRM Analytics, tell a story (NARRATIVE) • “Data is abundant, but if you don’t give it context, it’s just a bunch of numbers.” • Internal benchmarks (to compare their business units to others in the organization) • Support comes after results are delivered, not before. “It really comes back to how credible you are. You get buy-in when you show up repeatedly with accurate numbers and you can relate the story to how the company’s performing.”
  79. 79. STEP 5: EXTRAPOLATION - REPORTING • HR analytics reporting • How the information is communicated to the organization, particularly the C-suite, is critically important. • Companies simply produce spreadsheets that offer no easy and timely way to present what is happening in the business. • Like any good research report, it is vital to present meaningful information and identify actionable insight that can be used to make positive change. • Tactically, the best practice organizations, distribute multiple reports to multiple levels. Tailored reporting to address the specific needs, and ideally focuses on very specific business impacts. • If the metrics being shown convey business impact, quarterly reporting of 5-10 of the most critical, agreed-to KPIs is warranted.
  80. 80. DIFFERENT OBJECTIVES, DIFFERENT METHODOLOGIES http://www.inostix.com (Reporting)
  81. 81. Historical metric  “Last year’s corporate turnover rate was 8%.” Predictive analytic  “As a result of a drop in the regional unemployment rate, there is an 86% chance that the turnover rate in this job family will dramatically increase from last year’s 8% up to 12% within the next six months, and up to 16% within 10 months.” Actionable Predictive Analytic  Adds a cost element - “We project that this 100% increase in turnover will reduce your group’s productivity over the next 10 months by 17% resulting in a reduced output value of R812,000.”  Also adds a ‘recommended action’ - “we should implement personalized retention plans for the top performing 20% in this job family; they cost R2,000 each to develop and have a 89% success rate. ACTIONABLE, PREDICTIVE ANALYTICS — THE NEXT BIG THING IN TALENT MANAGEMENT Dr. John Sullivan, Professor, Talent Management Speaker and Advisor
  82. 82. HR METRICS REPORTING – 4 C’S • COSTS • CAUSES • CONSEQUENCES • CURE
  83. 83. LEARNING ACTIVITY 6 • Group discussion: • Apply step 5: Extrapolation and Reporting of the HRM Analytics process to a defined organization.
  84. 84. CASE STUDY • CASE STUDY 1: FOUR BEST PRACTICES AT WORK AT GOOGLE A retention algorithm Predictive modeling Improving diversity An effective hiring algorithm
  85. 85. LEARNING ACTIVITY 7 • Group discussion: • By reviewing case study 1, identify what best practice principles, lessons and insights can be drawn.
  86. 86. CASE STUDY • CASE STUDY 2: BIRMINGHAM CITY COUNCIL The context Metrics Acting on the information Informing decision-making Sharing knowledge
  87. 87. LEARNING ACTIVITY 8 • Group discussion: • By reviewing case study 2, identify what best practice principles, lessons and insights can be drawn.
  88. 88. READING ARTICLE 1 • The Top 10 Strategic HR and TA Metrics That CEOs Want to See (Dr. John Sullivan) • The Top 7 Strategic HR Metrics for Impressing Your CEO: Revenue per employee The improvement in the performance of new hires (quality of hire improvement) Performance turnover in key jobs Dollars of revenue lost due to position vacancy days Track a metric covering the highest impact current “hot” talent problem at your firm A contribution to productivity survey to identify which HR programs helped to increase productivity The percentage of HR strategic goals that were met
  89. 89. READING ARTICLE 1 • Three (3) Additional Strategic Metrics for the Recruiting Function: New hire failure rate Applications per employee Diversity hires in customer-impact positions • Final Thoughts
  90. 90. LEARNING ACTIVITY 9 • Group discussion: • By reviewing Reading Article 1, identify what best practice principles, lessons and insights can be drawn.
  91. 91. READING ARTICLE 2 • READING ARTICLE 2: Here’s What HR Must Do to Have the Business Impact CEOs Want (Dr. John Sullivan) • The 8 action steps for becoming high impact: #1: Accept accountability for improving people-management results #2: Demand a shift to data-based decision-making #3: Measure and increase workforce productivity #4: Make managers accountable for great people management #5: Build a competitive advantage #6: Expect reporting on continuous improvement #7: Measure quality and error rates in people management programs #8: Calculate your ROI • Final thoughts
  92. 92. LEARNING ACTIVITY 10 • Group discussion: • By reviewing Reading Article 2, identify what best practice principles, lessons and insights can be drawn.
  93. 93. CONCLUSION • Key points • Summary • Questions
  94. 94. CONTACT DETAILS • Charles Cotter • (+27) 84 562 9446 • charlescot@polka.co.za • LinkedIn • Twitter: @Charles_Cotter • http://www.slideshare.net/CharlesCotter

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