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From HR Metrics to Predictive Analytics

Craig Haas, PhDcut-e USA Inc.345 Park Avenue, 17th Floorc/o Enterprise Ireland NY, NY 10154

Mobile: +1-347-210-3811Craig.Haas@cut-e.com www.cut-e.com

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Agenda

cut-e: Company OverviewWhat is Big DataWhat are HR MetricsWhat are Predictive AnalyticsCase StudyAction StepsQuestions & Answers

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cut-e: global talent assessment

30+ Offices WorldwideAssessments in 40+ Languages

12 Million Candidates per yearAssessments in 70+ Countries

Talent Assessment Talent Development Talent Management Talent Advisory#HireToWin

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What is Big Data?

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What is Big Data?

Structured Data Unstructured Data

Massive volumes of structured and/or unstructured data that we collect through different channels and forms.

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Sources of Big Data in General

Also:- Emails/texts- Credit card

records- CCTV- Public transport

In HR, there has been an explosion of centralized Talent Data now available thanks to HR Systems (ATS, HRIS, LMS, etc.)

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What is HR Metrics?

Measures used to monitor HR activities and performance

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Does your HR Dept. use metrics?

HR Metrics

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Does your organization's HR department use metrics to keep track of how HR contributes to business objectives?

39%

53%

8%

0%

10%

20%

30%

40%

50%

60%

Yes No Not sure

SHRM.org Survey of 357 Randomly Selected HR Pros

SHRM Survey Says…

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Myths (Excuses) Against Metrics

“You can’t measure what we do…”Lack of clear purpose for measuringLack of cooperation between departmentsDifficulty extracting data from multiple systemsDifficulty understanding and analyzing metricsNumbers used to draw inaccurate conclusions

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Importance of HR Metrics

Feedback is required for continuous learningAccountability ‘What gets measured gets done’Quantify the value of HR Guide workforce strategies Maximize HR’s return on investmentsShow what HR contributes to business resultsMake the business case for HR’s objectives

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Question

What Metrics do you track?

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Does your organization use metrics/measurements to keep track of the following? (Check all that apply.)

6%

13%

24%

29%

29%

29%

36%

45%

50%

61%

63%

0% 10% 20% 30% 40% 50% 60% 70%

Other

Training return on investment

Turnover costs

Time to fill

Promotions

Cost per hire

Retention rate

Absenteeism

Turnover rate

Cost of benefits

Health care costs per employee

SHRM.org Survey of 357 Randomly Selected HR Pros

SHRM Survey Says…

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Typical Approach w/ Metrics

Choose a core HR

Processes to Track

Monitor with Metrics

Show HR’s Performanc

e

Is this a good approach? Why or why not?#HireToWin

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Formula: The number of business days to fill a vacantposition. This is counted from the day theposition becomes vacant to the date a newemployee starts in the job.Purpose:

Time to Hire shows length of time it takes to fill vacant positions.This metric is an indicator of organization's ability to recruit and hire new employees.

Time to Fill?

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Pros – What are some benefits of it?

Cons - What are some problems with it?

Examples Any one have a Pro/Con example?Here are two examples

Time to Fill?

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What metrics should you track?

Question

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Levels of HR Metrics

HR Metric Levels

Recruiting Metric Examples

Impact Date Needed - Date opening must be filled to prevent loss of revenue generation

Results – Potential Gain/Loss in revenue if opening is/isn’t filled by date needed

EffectivenessQuality of Hire Rating (90-days later)

Efficiency Time to fill – # of days from posting of job until hired person starts

Activities Number of people hired last quarter

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Planning for More of the Same

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Predictive Analytics uses statistics to help firms address problems and make talent decisions.

While ~50% of companies are using Online Assessments…just 14% of HR organizations in the U.S are using predictive analytics to make talent decisions.*

Most HR organizations have been slow to adopt analytics – too slow, in fact, in the minds of many impatient business leaders.

* Bersin by Deloitte’s study (2013)

What Are Predictive Analytics

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Can be used to Help Your Internal clients’ solve critical problems and

answer burning questions

It is not a complex as it seems…

Predictive Analytics

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what happens when we look at a metric for one thousand candidates?

22

Big Data Meets Predictive Analytics

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23

23

Predictive Analytics

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24

Bell Curve

Average

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Correlations (r)

0123456789

10

0 1 2 3 4 5 6 7 8 9 10weight

height

Correlations(r) from +1.0 to -1.0

r = + 0.44n = 16,948US pop.

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Negative Correlation Example Use of Umbrellas

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Correlations of common medical procedures & outcomes

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Prediction by different selection methods

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Start Small…Baby Steps

Predictive Analytics

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Analyzing Data

Microsoft ExcelFormulasSumAverage & MedianTime CalculationsCorrelations Regressions

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Simple Predictive Analyticswith MS Excel

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Select a Column or Row: Left click on very top of column (or far left end of row) and it will highlight the whole column (or row).

Average Formula: = average(A1, A2, A3) Correlation Formula: =CORREL(array1, array2)Note: an Array is any column (or a row) you select.

Formulas can be copied/pasted but you want to use ‘$’ to lock down certain columns.

Excel Tips

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How To Use Excel

Practice Data Set

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Online Application & Qualifying Q’s (via ATS)

Online Assessments(via ATS)

Phone/Video InterviewInterviews

& ACsHire

Predictive Analytics to Maximize ROI of Recruiting

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Simple Reporting

Microsoft Excel (or equivalent)Reports Tables Bar Graphs Pie Charts Scatter Plots

Warning:Do not show your internal client a big Excel file spread sheet with lots of data!

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Execs Like Dashboards !

If you can visually present in an intuitive way the impact that multiple variables have on a key outcome, you will more easily make your point to the Executive Leadership Team.

Remember they are accustom to looking at Dashboards for the business.

MS Office or equivalent are fine…..there are also some really “Geeky Cool” Data Visualization tools available these days.

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Example of Using MS Office for Dashboard:

A Business Case on Selecting Salespeople

EXCEL & PPT

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New Sales Goal AchievementAn Excel Bar Graph

Percentage of New Sales Target Achievement High match score candidates achieved 98% of their sales targetModerate match score candidates achieved 63% of their sales target Low match score candidates only achieved 32% of their sales target

High Match Score Group

Moderate Match Score Group

Low Match Score Group0%20%40%60%80%

100%

(averaged over 6 months)

High Match Moderate Match Low Match

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Closed Sales From ReferralsAn Excel Pie Chart

Number of New Sales from Salesperson’s Registered Referral Sources

High match score candidates closed 63% of all the referrals salesModerate match score candidates closed 32% of all the referral salesLow match score candidates only closed 5% of all the referral sales

5%

32%

63%

Low Match Score Group

Moderate Match Score Group

High Match Score Group

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Difference in TenurePPT Special Font for Emphasis

The average tenure for both High and Moderate match score

candidates was at least

that of the Low match score candidates

Double

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Sunburst of Engagement Scores by Team Hierarchy

Source: OrgVue

Dashboards – Cool Software

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Start Small…Baby Steps

Predictive Analytics

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Get Started Now – Easy Steps

Find a leader with a problem

Persuade him/her to let you use analytics to help solve it

Figure out what metrics/outcomes may be relevant predictors & then collect the data

Create a combined score (regression formula) that predicts the desired outcome

Initiate the intervention based on what you have learned and measure change of performance over time

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HR Analytics Team Wanted

Find a business leader who is willing to partner on an analytics project to solve a problem (e.g. reducing turnover or accidents)

Create a project team (e.g. borrow talent from other departments, leverage the local Univ. or a supplier)

Get a small win and then promote its success

Repeat above process a few times to collect some small wins and build credibility with business leaders

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Ask for resources to build an analytics team Process must be owned by Executives, Managers, HR, Finance, and ITReview org strategy, objectives and then discuss the leadership’s burning questions about talent? Select a problem or question to addressFigure out what data be used to predict it

Once You’ve Proven It Works

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Questions? Let’s Chat…

Feel free to contact me to chat about HR Metrics, Predictive Analytics, etc.

I love networking with other HR Pros and talking about this.

Let’s connect via LinkedIn www.linkedin.com/in/craighaas

Craig Haas, PhDcut-e USA Inc.Mobile: +1-347-210-3811Craig.Haas@cut-e.com www.cut-e.com