The Power Of ANALYTICS: HR’s SECRET WEAPON Steve VanWieren Principal Statistician / Data Scientist October 16, 2013
Agenda • Big Data in HR • A case study • Workforce trends
What is “big data”? V olume • The Big Data Revolution (lots of data) V ariety (many types) V elocity (speed of data in/out) V eracity (conformity to facts)
Gartner’s formal definition Big data is high volume, high velocity, and/or high variety information assets that require new forms of processing to enable enhanced decision making, insight discovery and process optimization.
Business Intelligence vs Big Data Business Intelligence uses descriptive statistics with data with high information density to measure things, detect trends etc.; Big Data uses inductive statistics and concepts from nonlinear system identification to infer laws (regressions, nonlinear relationships, and causal effects) from large data sets to reveal relationships, dependencies, and to perform predictions of outcomes and behaviors Source: Wikipedia
Inflated expectations for Big Data Source: Gartner “Hype Cycle for Emerging Technologies” (July 2013)
My definition of “big data” “Big data” is data, stored and accessed in the most up -to-date technologies Size doesn’t matter. The knowledge gained from the data is what matters “An analytic without action is useless.” – Steve VanWieren
Why not Human Capital? What if companies had the same level of business intelligence on their human capital as they did in other disciplines like Finance, Marketing, Sales & Manufacturing?
The HCM Market Response Source: Gartner “Hype Cycle for Human Capital Management Software” (July 2013)
Internal data Human Capital Management solutions, like UltiPro, collect employee information from Recruitment to Retirement
External data 90% of all the data ever collected has been collected in last two years • Source: ScienceDaily Data collected in 60 seconds (2013) Source: Qmee
Usefulness of internal vs external More Internal data predictive External data Less predictive Pre- During Post- employment Employment Employment
Some stats 74% of people would 76% of younger workers today consider finding plan to find a new job as a new job the economy improves Harris Interactive Poll Harvard Business Review 32% of people are actively looking for a new job Mercer Question to consider: Do you know who the 32% are in your organization?
More stats 2mm people voluntarily leave their job every month US Dept of Labor Statistics 58% would take 15% pay cut in order to work for an organization with values like their own Net Impact Survey 35% of people quit their jobs within the first 6 months Leigh Branham, “The Seven Hidden Reasons Employees Leave” Question to consider: Are you hiring people with values that fit your culture?
And even more stats 69% are more likely to stay >3 years if they experience a well structured onboarding program Aberdeen Group 86% know within the first 6 months if they are going to stay or leave long term Aberdeen Group 55% of millenials say career advancement opportunities are main thing they want in a job Bob Nelson Question to consider: do you have any special programs for new hires?
And still even more stats 70% are disengaged at work Gallup Poll 75% of leaders have no engagement strategy, even though 90% say engagement impacts business success PwC Question to consider: does your organization have an engagement strategy?
It all leads to one question…
Agenda • Big Data in HR • A case study: forecasting employee turnover • Workforce trends
Forecasting at the organization level Total Active vs 12-month Retention 12-mo Retention Rate 4,500 90.0% 4,000 88.0% 3,500 86.0% 3,000 84.0% 2,500 82.0% 2,000 1,500 80.0% 1,000 78.0% 500 76.0% 0 12-mo retention rate Projected 12-mo retention Total Retained Projected Retained To forecast at the macro level, you need macro level data • Ex. Industry Sales, Economy, Monthly company turnover
Forecasting at the employee level With employee level data, you could develop: Predictive Scores Historical Reports Workforce Analytics (BI) / Planning (ex Retention Scores) Organization-level summaries Actual employee level
Developing the Retention Predictor™ Compensation Benefits History History Demographics Job History Retention Predictor™
Retention Predictor Score Retention Predictor is a score between 0 and 100, representing the probability an employee will remain with the organization for the next 12 months. 0 100 Low Scores: High Scores: lower higher probability of probability of employee employee staying staying
Score Distribution Predictions Score Range # of % of All Employees Employees Greater than 9 in 10 90.0 – 99.9 88,500 18.1% chance of staying 75.0 – 89.9 231,915 47.3% 50.0 – 74.9 117,699 24.0% Less than 1 in 2 0.0 – 49.9 51,987 10.6% chance of staying
Model Performance – Gains Chart Predictions Results Score Range # of % of All # Terminated % Terminated Employees Employees 90.0 – 99.9 88,500 18.1% 7,242 8.2 75.0 – 89.9 231,915 47.3% 37,947 16.4 50.0 – 74.9 117,699 24.0% 39,605 33.6 0.0 – 49.9 51,987 10.6% 33,779 65.0 28% of terms On which score range does it make the most sense for managers to focus their attention?
Model Performance – Visualization 70.0 60.0 50.0 40.0 30.0 20.0 10.0 0.0 0.0 – 49.9 50.0 – 74.9 75.0 – 89.9 90.0 – 99.9 Score Range % of All Employees % Terminated
The more you know, the better Predictions Results Score Range # of % of All # of High # Terminated % Terminated Employees Employees Performers* 90.0 – 99.9 88,500 18.1% 12,990 7,242 8.2 75.0 – 89.9 231,915 47.3% 23,498 37,947 16.4 50.0 – 74.9 117,699 24.0% 8,188 39,605 33.6 0.0 – 49.9 51,987 10.6% 2,794 33,779 65.0 * Not actual High Performer results With additional measures, you could identify and focus on those high performers at greatest risk
Big savings! Organizations can experience significant costs to replace an employee. 1 1.5 to 3 times the annual salary for professional salaried employees $5,000 to $20,000 for non-salaried employees 1 – SHRM, NRF, J Douglas Philips, and Bersin studies
Detail the cost savings Includes separation, replacement, and training costs 2 Separation Replacement Training Exit interviews Communication of job availability Informational literature Administrative functions Pre-employment administrative New hire orientation related to the termination functions Separation pay Entry interviews Formal training programs Unemployment tax Skills Testing Instruction by assignment Staff meetings Travel & moving expenses Post-employment acquisition & dissemination of info Employment medical exams 2 – “Investing in People: Financial Impact of Human Resource Initiatives” (2 nd Edition), Cascio and Boudreau
Why do people leave? 31% don’t like their boss 31% do not feel empowered Aberdeen Group Aberdeen Group 35% due to internal politics/turf 43% for lack of recognition Aberdeen Group Aberdeen Group 89% of managers believe that most employees are pulled away by better pay …but 88% of voluntary resignations happen for reasons other than pay Leigh Branham, “The Seven Hidden Reasons Employees Leave” >60% do not feel like they get enough feedback Gallup Poll 75% of people leave because of work relationship issues Saratoga Institute 75% of people who leave voluntarily don’t quit their jobs; they quit their boss Roger Herman #1 reason is lack of recognition Bersin 79% of those who quit their job cite lack of appreciation as primary reason SHRM #1 reason for millennials: not learning enough Business Insider
It is overwhelming! 31% don’t like their boss 31% do not feel empowered Aberdeen Group Aberdeen Group 35% due to internal politics/turf Aberdeen Group 43% for lack of recognition Aberdeen Group 89% of managers believe that most employees are pulled away by better pay …but 88% of voluntary resignations happen for reasons other than pay Leigh Branham, “The Seven Hidden Reasons Employees Leave” >60% do not feel like they get enough feedback Gallup Poll 75% of people leave because of work relationship issues Saratoga Institute 75% of people who leave voluntarily don’t quit their jobs; they quit their boss Roger Herman #1 reason is lack of recognition Bersin 79% of those who quit their job cite lack of appreciation as primary reason SHRM #1 reason for millennials: not learning enough Business Insider
A change in approach To understand what makes people stay, you have to experiment with a population who is supposed to leave Retention scores are a great way to identify this population
CRITICAL – measure the results Set it up like a drug trial • Some people get the treatment • Others do not Compare the turnover for the two populations • This will help you to understand which methods are most effective as well! And then tie the results to $$$ • This will get your executives on board
The 9 Motivators • 99% of people are motivated by at least 1 of these 9 things Achievement Money Teamwork and Growth Power Approval Security Autonomy and Stability Equality Freedom
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