Quantifying HR: Basics of HR Analytics Carrie L. Riggle David B Turetsky

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1 Quantifying HR: Basics of HR Analytics Carrie L. Riggle David B Turetsky Contact Information David B Turetsky, HCS ADP, LLC. Vice President, Chief Product Officer, ADP DataCloud Cell: +1 (508) Carrie L Riggle EVP/Human Resources Manager First Commonwealth Bank Phone: (724)

2 About Carrie L. Riggle Carrie serves as the EVP/Human Resources Manager for First Commonwealth Bank. In her role, she is responsible for designing and developing programs and services that attract, retain and develop talent. Using Total Rewards approach, she leads HR s contributions to corporate talent planning, compensation and benefits, recruitment and employee relations and employee training and development. Carrie sees the value that data brings to answering business questions and taking action. With over 20 years of experience, Carrie grew up in the staffing and employee relations discipline, then expanded her knowledge to include all facets of HR. She is focused on performance, client service and efficiency for her group and continuously strives to improve the quality of work life for the employees who give their time and talents to her organization. Copyright 2015 ADP, LLC. 3 About David B Turetsky As the Vice President, Chief Product Officer, ADP DataCloud, David is responsible for developing products and services to deliver innovative products and services for ADP clients. He provides vision, leadership and strategy for ADP s efforts around Big Data. David has more than 25 years of experience in HCM, HR, HRIS, Talent Management, Compensation and Big Data as an analyst, manager, executive, consultant and entrepreneur. His passion is manager empowerment and employee engagement through total rewards management. It has been the topic that he often presents to large audiences at national HR conferences such as HR Technology, SHRM, PIHRA, and APA. In addition, David has been published in WorldatWork Journal, HR Executive magazine and other industry publications. Copyright 2015 ADP, LLC. 4

3 $6 billion in assets; community bank with a community focus Headquartered in Indiana, PA and operates throughout 15 counties in western and central PA; approx employees Time To Be First First Commonwealth Bank Our customers are first. We work hard to achieve our mission of helping our neighbors and the businesses within our communities realize their financial goals as a trusted partner and friend. 5 Who is ADP? 610,000 businesses and over 50 million of their people rely on ADP for Human Resources Payroll Benefits Time & Attendance Retirement Administration Tax Payments & Compliance Talent Management Workforce Insights 52,000 ADP people worldwide provide service and support in over 100 countries and more than 30 languages 6

4 Goal for this presentation Understand the business environment we are operating in Common understanding of the problem Quantifying HR today Drive practical examples of how HR can bring value to the business How we can help our organizations prepare for this challenge 7 Agenda Trends affecting HR Small Data/Data/Big Data Strategy Supported by Data Business Intersection with HR Strategy HR Driving Business Value 8

5 Trends affecting HR 9 The Cause for Change Taking Control of Healthcare Reform Will you provide benefits? Will you limit hours? Do you have CDHP and wellness? Will you outsource? Making Smart Investments in People Do managers have the right tools? Are you retaining top talent? What is your comp strategy? Do you have succession plans? Personalization of Employee Experience Do you have the right tools? What is your social media strategy? Can your culture support personalization? Do generations demand differentiation? 10

6 Trends in the Marketplace 11 What have we heard? Business Leaders Sales Data is driving our businesses to differentiate from competitors where margin and cost pressures are forcing innovation from every conceivable direction. Better targeting of sales pursuits to those individuals who search for our products, go to our websites, and participate in our webinars. HR Leaders Clients are no longer satisfied with receiving tables of data or transactional reports showing administrative- focused information. 12

7 Small Data/Data/Big Data 13 Data 14

8 Data Strategy 15 Data Scientist Job Description As a member of a Business Intelligence and Analytics Team, you will analyze customer data and build high-end analytical models for solving business problems, such as customer interaction, behavior, portfolio, etc. The duties will include data preparation & analysis using statistical software. The candidate should be able to interpret the results in a clear and concise format to be presented to the Senior Executives in business terms.! Essential Qualifications At least 5 years of experience such as analyzing data and/or building analytical models using SAS. Master's degree in statistics, mathematics or computer science. Demonstrated ability to apply statistical or data mining techniques to solve business problems. Ability to extract and prep data from relational databases, Excel and text files for use with SAS Software. Thorough knowledge of supervised and unsupervised modeling techniques. Ability to work independently in all aspects of data modeling, from sourcing through final presentation of the findings. Experience with SAS Enterprise Guide. Ability to work with the business users and IT. Excellent verbal and written communication skills. Ability to communicate with people of various technical and business backgrounds, including the ability to explain difficult technical concepts in simple terms to business users. Ability to work independently and with a team environment. 16

9 Business Data Systems Small Data Spreadsheets Word Documents Access Databases Data Order processing CRM General Ledger Big Data Linkages Visualization Tools SAVED LOCALLY SAVED CENTRALLY REFERENCED COLLECTIVELY Integration Value 17 Integration and Value By themselves, the data are transactional receipts from processes and not intended as measurements of the transaction: Business plan Presentation to potential clients Expense reimbursement Sales transaction Cost of Goods Sold 18

10 Human Resource Data Systems Small Data Compensation Spreadsheets Performance Evaluations Succession Planning Data HRIS Payroll Benefits System Big Data Scorecards Dashboards Analytics SAVED LOCALLY SAVED CENTRALLY REFERENCED COLLECTIVELY Integration Value 19 Common HR Processes and Data Recruiting Requisitions Candidates Time to Hire Applications Learning Course Attendance Enrollments Development Plan Progress Performance Goals Goal Percent Completion Evaluation Completion Compensation Budgets Guidelines Spend Red Circles Terminations # of Voluntary/ Involuntary Total Terms Term Reasons Succession Successors Candidate Diversity Successor Readiness 20

11 HR Data Challenges HR Data is a collection of transactions HR, Finance, Supply Chain, and CRM capabilities have specific missions out of sync Financial Tracking Record Keeping Service levels Inconsistent data definitions, vocabulary, and mental models First exposure of data opportunities provides a glimpse into the abyss Global is usually a mess including multiple systems 21 How HR is involved in a Business Crisis/ Change Major HR Projects are often driven by business needs while under severe time pressure integrate 500 acquired associates. reduce our people costs by 5% within six weeks. consolidate sales, marketing, and product teams. reengineer our service delivery model. relocate our plant The value of core HR Programs and Processes are often eroded by, rather than supported by these activities. 22

12 Business Intersection with HR 23 Business Strategy Measurement Scorecard Metrics Earnings Per Share Net Income Earnings Before Interest Tax Depreciation and Amortization Metrics are tracked over time and major changes and/or variances against plan are examined 24

13 Effects of a change in business strategy Communications to groups affected by the change Systems, processes, philosophies and operating plans change Operational Changes Finance changes HR changes 25 HR Strategy Measurement HR Scorecards Turnover Engagement Employee Performance Metrics were tracked over time and major changes examined Did this result in changes to HR Process or Strategy? 26

14 HR Scorecard/Dashboard 27 Moving Away from Reporting Metrics Educate HR on business metrics meaning & impact Review the goals of the organization and stay current on changes to strategy Revisit HR guiding principles and processes to match business strategy, focus on alignment, improvement and measurement Talent Strategy should drive the business forward Provide correlations between HR Metrics and the Business Strategy 28

15 Talent Management Process and Data Issues Recruiting Learning Succession Performance Compensatio n Where are Are employees Do we have the How can Are we successful taking the right right people ratings be compensating employees found?! courses? identified as successors? calibrated across a business/the organization? the right people? What skills does a successful employee exhibit? Can we better leverage our learning investments? What key positions do not have successors identified? Where are concentrations of lowest performers? Do we pay too much for certain roles? 29 Strategy Supported by Data 30

16 Scientific Method Scientific Method Applied to the business world Make a hypothesis Develop a business strategy Observe and measure sample of the population Observe and measure the effect of the strategy Analyze the results Analyze the strategy Infer conclusions from the results Infer the effectiveness of the strategy and potentially change strategy 31 Key Business Metrics INCREASE MARGIN REDUCE COST INCREASE PROFIT 32

17 Measurement Driving Business Strategy Reduce turnover Introduce safety training Increase Margin Reduce skill gaps Measurements: Turnover Year-over-Year Include industry and company benchmarks Safety Incidence Year-over-Year Include industry and company benchmarks Competency Gaps Highest gaps/strengths Organizations with biggest gaps 33 Measurement Driving Business Strategy 34

18 Measurement Skill Improvement 35 Observations Skill Improvement 36

19 Analysis 37 Draw conclusions Our hypothesis was that to increase margins, we should reduce turnover, increase safety training, and reduce skill gaps. Through observation, we can infer that this may work, if we focus our efforts on Improving the skills of our current workers Hiring workers with better skills Using contractors to fill immediate gaps 38

20 Measurement Driving Business Strategy Lower time to hire Hire different skills Reduce Costs Increase manager training Measurements: Time to hire Period-over-period Include industry and company benchmarks Number of New Hire Terms Organizations with losses Average Skill Profile of Loss/ Success Courses attended by Managers Performance Employee and Group Engagement Scores 39 Reducing Costs KPIs Turnover Net Income Methods Safety Incentives Add goal to "Manage Costs" Reduce Merit Budget Increase manager training Measurements Customer Satisfaction Impact of change Lower Higher Higher Medium Medium Higher Medium High Higher Medium Lower Medium Lower Lower Medium Low 40

21 Measurement Driving Business Strategy Retain key staff/hi- Pos Incent Innovation Increase Profits Improve Performance Mgmt Measurements: Turnover of Key Talent/Hi-Pos Period-over-period Include industry and company benchmarks Incentives Earned # of Patents P&L of Business Ratings Distribution Performance Employee and Group Engagement Scores 41 We have a strategy, now we measure it Constantly monitor criteria established during the business case/decision Make course corrections and measure their impact on the goal and strategy Measure again at a future time and reexamine the goal and strategy 42

22 What do I do with this? 43 Start to jot down what you would ask Do happy employees translate to more productive employees? Can compensation growth be slowed without loss of performance growth? Do better managers make for higher employee engagement scores? What leading indicators best predict successful employees in our company? 44

23 Deconstruct the question What leading indicators best predict successful employees in our company? Definition of a successful employee Construct the hypothesis We can predict who is a successful employee by looking at background information we already collect in pre and post employment circumstances. Collect data: Performance scores by employee historically, Warnings or other documented Employee Actions, Promotions, job changes, Schools attended, Skill gaps, Absence/Lateness data, Manager changes, Department profits, etc. Derive the successful employee variable as the dependent variable Find co-linear or data that answers the same question twice Run analyses to show the variables that best predict successful employees Conclude analyses with a model of how a successful employee is predicted Announce the results and test methods of replicating the successes in future hiring and promotion activities 45 Ten Steps to use this information 1. Learn what your business does by reading publicly available information (proxy/10-k/annual Report) or by asking the owner/leaders - partners or mentors 2. Do independent research on your industry 3. Discuss with your leaders current issues 4. Take on-line courses on Data Science, HRIT managers/ leaders get a certificate on Data Science 5. Interdisciplinary internal corporate discussion regarding data with the goal of developing a Big Data corporate model 46

24 Ten Steps to use this information 6. Get on the team and lead discussions of how HR should lead, not just help the Big Data initiatives - settle for being on the team 7. At every chance, rebuild HR processes to consider measurable business outcomes 8. HR data systems should be enhanced with the capabilities to support the business changes 9. Proactively develop models for future growth, change and alternative business scenarios in order to provide appropriate support for business strategies 10. Continually pursue excellence in providing outstanding customer service through data 47 Five easy Steps to successful HR Data Science 1. Wear a lab coat - dress for the job you want 2. Data Science for Dummies 3. Ask deeper questions when a report request comes in Think about how you use data and can make suggestions about structuring an analysis 4. Listen to what is going on in your organization 5. Make suggestions about how you would see data working better based on what you hear/ know 48

25 In Conclusion 49 Summary Educate HR on Business metrics Talent and HR processes are considered Business Processes HR providing Stakeholders with appropriate data to make good BUSINESS DECISIONS Think like a data scientist and finding relationships in data to solve real business problems 50

26 Thank you 51

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