CONSULTING & HR ANALYTICS
CONSULTING MODEL
OBJECTIVES GOAL Provide an analytic framework that uses HR data to help you consult with your business OBJECTIVES At the end of this session, you will be able to: Use HR analytics and strategic workforce planning to consult with your business. Understand the difference between operational reporting and analytics. Identify where and how to access data. Understand the capability of Business Intelligence (BI) Dashboards.
HR ANALYTICS ASSESSMENT Strongly Agree (5) Agree (4) Neutral (3) Disagree (2) Strongly Disagree (1) I am comfortable using data to inform talent decisions. I know where to go to get the data I need to answer talent questions. I possess the research and consulting skills needed to identify and analyze problematic workforce issues. I am able to effectively communicate the results of data analysis, draw conclusions and recommend next steps. My business partners consider HR insights that I offer as critical to achieving their business objectives. TOTAL SCORE Grand Total = PG page 13
HR ANALYTICS MATURITY CURVE Low High Analytics Maturity Is the data accurate? What happened? 1 Data Governance Why did it happen and what will happen in the future? What insights can be drawn by what happened? How will we meet our future human capital needs? 5 2 3 Reporting 4 Descriptive Metrics Scorecards Causal & Predictive Analytics Strategic Workforce Planning Low Utilization of HR Data & Intelligence High PG page 14
BRAINSTORMING 1 What challenges is your business facing that could be addressed with HR analytics? 2 What questions are you being asked by your business partners? 3 What other people-related questions should we be asking and answering? PG page 14
DATA GOVERNANCE Low High Analytics Maturity Data Governance is FOUNDATIONAL Quality of Analytics and Quality of Decisions are dependent on Quality of the Data Is the data accurate? 1 Data Governance Low Utilization of HR Data & Intelligence High PG page 15
DATA GOVERNANCE PROCESS Rules for how an organization conducts specific business functions/decisions DATA Rules for how an organization defines, produces and uses data TECHNOLOGY Rules for how an organization makes/implements technology decisions in support of the business objectives Each of us has some role to play as a steward of HR data PG page 15
REPORTING Low High Analytics Maturity What happened? Is the data accurate? 1 Data Governance 2 Reporting Low Utilization of HR Data & Intelligence High PG page 16
REPORTING OPERATIONAL REPORTING What is it? Measures performance of HR processes (eperf, CED, idrive) What does it do? Helps HR make operational decisions and support managers through HR processes MANAGEMENT REPORTING What is it? Delivers outcomes of HR metrics (e.g. turnover, span of control) What does it do? Helps HR and Business make strategic decisions by providing basis for HR Analytics *See COE Data and Reporting Guide PG page 16
REPORTING ACTIVITY Reference the COE Data and Reporting Guide
DESCRIPTIVE METRICS SCORECARD Low High Analytics Maturity Is the data accurate? 1 What insights can be drawn by what happened? What happened? Data Governance 2 Reporting 3 Descriptive Metrics Scorecards Low Utilization of HR Data & Intelligence High PG page 17
BI DASHBOARD HEADCOUNT What is it? Measures number of active associates Why is it important? Helps ensure we have the right number of associates to deliver on business objectives TURNOVER RATE What is it? Measures the annual rate of terminations relative to associate population Why is it important? Helps ensure that we are retaining our talent, improving engagement, optimizing the value proposition of our people. PG page 18
BI DASHBOARD SPAN OF CONTROL What is it? Measures average number of direct reports of people leaders Why is it important? Helps ensure we have the most efficient and effective management structure DEMOGRAPHICS & DIVERSITY What is it? Provides insight about our associates Why is it important? Helps ensure that we have a diverse workforce and provides insight into predictive analytics, such as retirement, turnover, promotions, etc. PG page 18
HR SCORECARDS
CAUSAL & PREDICTIVE ANALYSIS Low High Analytics Maturity What happened? Is the data accurate? 1 Data Governance Why did it happen and what will happen in the future? What insights can be drawn by what happened? 2 Reporting 3 4 Descriptive Metrics Scorecards Causal & Predictive Analytics Low Utilization of HR Data & Intelligence High PG page 19
CONNECTING HR DATA More than data is required; analytics must include stories and insights. PG page 20
CAUSAL & PREDICTIVE ANALYSIS PRACTICE Associate Engagement Dept 2008 2009 2010 2011 A 4.0 3.9 4.0 3.7 B 3.9 4.1 3.4 2.7 C 4.0 4.1 4.2 4.3 Customer Retention Dept 2008 2009 2010 2011 A 74% 75% 75% 74% B 85% 74% 73% 65% C 80% 81% 82% 84% Associate Retention Dept 2008 2009 2010 2011 A 90% 91% 89% 88% B 93% 88% 85% 80% C 88% 90% 92% 94% Associate Performance Dept 2008 2009 2010 2011 A 3.2 3.4 3.7 3.5 B 3.5 3.5 3.3 3.2 C 3.8 4.1 4.2 4.3 PG page 21
CAUSAL & PREDICTIVE EXAMPLE Associate Engagement Associate Retention High Associate Retention Low Associate Retention Low Engagement High Engagement Observation: Associates with higher engagement had higher retention Prediction: Higher engaged Associates will have higher retention
CAUSAL & PREDICTIVE EXAMPLE Associate Performance Customer Retention High High Associate Customer Retention Retention Low Low Associate Customer Retention Retention Low Low Engagement Associate Performance High Engagement Associate Performance Observation: Associates with higher performance had higher customer retention Prediction: Higher performing Associates will have higher customer retention
ANALYSIS PLAN Issue An unresolved question phrased so that it can be answered yes or no Is engagement correlated with revenue? PG page 22
ANALYSIS PLAN Issue Hypothesis An unresolved question phrased so that it can be answered yes or no Is engagement correlated with revenue? A statement of the likely resolution of the issue Higher engagement leads to increased revenues PG page 22
ANALYSIS PLAN Issue Hypothesis Analysis An unresolved question phrased so that it can be answered yes or no Is engagement correlated with revenue? A statement of the likely resolution of the issue Higher engagement leads to increased revenues The analysis that must be done in order to test the hypothesis Compare engagement results with sales results for several departments PG page 22
ANALYSIS PLAN Issue Hypothesis Analysis Information Required An unresolved question phrased so that it can be answered yes or no A statement of the likely resolution of the issue The analysis that must be done in order to test the hypothesis The information required to perform the analysis Is engagement correlated with revenue? Higher engagement leads to increased revenues Compare engagement results with sales results for several departments Engagement by department; sales dollars and units per department PG page 22
ANALYSIS PLAN Issue Hypothesis Analysis Information Required Information Source An unresolved question phrased so that it can be answered yes or no A statement of the likely resolution of the issue The analysis that must be done in order to test the hypothesis The information required to perform the analysis The source of the information required to perform the analysis Is engagement correlated with revenue? Higher engagement leads to increased revenues Compare engagement results with sales results for several departments Engagement by department; sales dollars and units per department Engagement data from OE; and sales data from the business operations managers PG page 22
ANALYSIS PLAN Issue Hypothesis Analysis Information Required Information Source End Product Prototype An unresolved question phrased so that it can be answered yes or no A statement of the likely resolution of the issue The analysis that must be done in order to test the hypothesis The information required to perform the analysis The source of the information required to perform the analysis A graphic (drawing) representation of the output of the analysis Is engagement correlated with revenue? Higher engagement leads to increased revenues Compare engagement results with sales results for several departments Engagement by department; sales dollars and units per department Engagement data from OE; and sales data from the business operations managers PG page 22
ANALYSIS PLAN: PRACTICE ISSUE HYPOTHESIS ANALYSIS INFORMATION REQUIRED INFORMATION SOURCE END PRODUCT PROTOTYPE PG page 22
ANALYTICS PRACTICE ACTIVITY Practice using an Analysis Plan. PG page 22
STRATEGIC WORKFORCE PLANNING Low High Analytics Maturity What happened? Is the data accurate? 1 Data Governance How will we meet our future human capital needs? 5 Why did it happen and what will happen in the future? What insights can be drawn by what happened? 2 Reporting 3 4 Descriptive Metrics Scorecards Strategic Workforce Planning Causal & Predictive Analytics Low Utilization of HR Data & Intelligence High PG page 23
IMPACT OF HR ACTIVITY KNOWLEDGE ON STRATEGIC ROLE EFFECTIVENESS Workforce Planning is the most effective activity HR can engage in to increase its strategic contribution to the organization, which in turn drives talent and business outcomes. Source: Corporate Leadership Council PG page 24
STRATEGIC WORKFORCE PLANNING Right People with the Right Skills in the Right Place at the Right Time at the Right Cost Workforce Supply GAP: Workforce Strategy and Gap Closure Plans Workforce Demand Hiring Plans Transfers & Promotions Compensation Planning Buy vs. Build Decisions Learning & Development PG page 25
STRATEGIC WORKFORCE PLANNING EXAMPLE DEPT. 2011 YE HEADCOUNT TURNOVER LESS RETIREMENT LESS ATTRITION (OTHER TERMS) LESS TRANSFERS OUT PLUS HIRES PLUS TRANSFERS IN 2012 YE HEADCOUNT A 300 301 B 250 235 C 100 99 Total 650 635 PG page 26
STRATEGIC WORKFORCE PLANNING EXAMPLE DEPT. 2011 YE HEADCOUNT TURNOVER LESS RETIREMENT LESS ATTRITION (OTHER TERMS) LESS TRANSFERS OUT PLUS HIRES PLUS TRANSFERS IN 2012 YE HEADCOUNT A 300-3 -20 301 B 250-1 -20 235 C 100 0-4 99 Total 650-4 -44 635 PG page 26
STRATEGIC WORKFORCE PLANNING EXAMPLE DEPT. 2011 YE HEADCOUNT TURNOVER LESS RETIREMENT LESS ATTRITION (OTHER TERMS) LESS TRANSFERS OUT PLUS HIRES PLUS TRANSFERS IN 2012 YE HEADCOUNT A 300-3 -20-2 +25 +1 301 B 250-1 -20 0 +4 +1 235 C 100 0-4 -1 +3 +1 99 Total 650-4 -44-3 32 4 635 PG page 26
STRATEGIC WORKFORCE PLANNING ACTIVITY MINI-CASE EXERCISE HYPOTHETICAL ASSUMPTIONS DEPARTMENT A DEPARTMENT B DEPARTMENT C 200 sales associates 10% turnover average age of 55 Business - forecasts 25% increase in sales 300 claims associates 5% turnover average age of 35 Business - forecasts a 50% decrease in claims 150 IT associates 10% turnover average age of 25 Business improving productivity 10% PG page 27
STRATEGIC WORKFORCE PLANNING TURNOVER DEPT. 2011 YE HEADCOUNT LESS RETIREMENT LESS ATTRITION (OTHER TERMS) LESS TRANSFERS OUT PLUS HIRES PLUS TRANSFERS IN 2012 YE HEADCOUNT A B C Total Retention strategy/action? Development strategy/action? Hiring strategy/action? Compensation strategy/action? Risks? PG page 27
STRATEGIC WORKFORCE PLANNING APPLICATION Apply what you learned today to the case you brought with you.
QUESTIONS & ANSWERS
THANK YOU With Academy logo see example from last year