CONSULTING & HR ANALYTICS 2012 HR ACADEMY: THE ROLE OF A BUSINESS ADVISOR

Transcription

1 CONSULTING & HR ANALYTICS

2 CONSULTING MODEL

3 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.

4 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

5 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? Reporting 4 Descriptive Metrics Scorecards Causal & Predictive Analytics Strategic Workforce Planning Low Utilization of HR Data & Intelligence High PG page 14

6 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

7 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

8 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

9 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

10 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

11 REPORTING ACTIVITY Reference the COE Data and Reporting Guide

12 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

13 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

14 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

15 HR SCORECARDS

16 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

17 CONNECTING HR DATA More than data is required; analytics must include stories and insights. PG page 20

18 CAUSAL & PREDICTIVE ANALYSIS PRACTICE Associate Engagement Dept A B C Customer Retention Dept A 74% 75% 75% 74% B 85% 74% 73% 65% C 80% 81% 82% 84% Associate Retention Dept A 90% 91% 89% 88% B 93% 88% 85% 80% C 88% 90% 92% 94% Associate Performance Dept A B C PG page 21

19 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

20 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

21 ANALYSIS PLAN Issue An unresolved question phrased so that it can be answered yes or no Is engagement correlated with revenue? PG page 22

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

23 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

24 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

25 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

26 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

27 ANALYSIS PLAN: PRACTICE ISSUE HYPOTHESIS ANALYSIS INFORMATION REQUIRED INFORMATION SOURCE END PRODUCT PROTOTYPE PG page 22

28 ANALYTICS PRACTICE ACTIVITY Practice using an Analysis Plan. PG page 22

29 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

30 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

31 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

32 STRATEGIC WORKFORCE PLANNING EXAMPLE DEPT YE HEADCOUNT TURNOVER LESS RETIREMENT LESS ATTRITION (OTHER TERMS) LESS TRANSFERS OUT PLUS HIRES PLUS TRANSFERS IN 2012 YE HEADCOUNT A B C Total PG page 26

33 STRATEGIC WORKFORCE PLANNING EXAMPLE DEPT YE HEADCOUNT TURNOVER LESS RETIREMENT LESS ATTRITION (OTHER TERMS) LESS TRANSFERS OUT PLUS HIRES PLUS TRANSFERS IN 2012 YE HEADCOUNT A B C Total PG page 26

34 STRATEGIC WORKFORCE PLANNING EXAMPLE DEPT YE HEADCOUNT TURNOVER LESS RETIREMENT LESS ATTRITION (OTHER TERMS) LESS TRANSFERS OUT PLUS HIRES PLUS TRANSFERS IN 2012 YE HEADCOUNT A B C Total PG page 26

35 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

36 STRATEGIC WORKFORCE PLANNING TURNOVER DEPT 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

37 STRATEGIC WORKFORCE PLANNING APPLICATION Apply what you learned today to the case you brought with you.

38 QUESTIONS & ANSWERS

39 THANK YOU With Academy logo see example from last year