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People Analytics 2016
Evolving:
• HR Leaders are starting to understand the space
• Talented analysts are seeing the potential
• Excitement about advanced technologies
• Move to more pragmatic solutions
People Analytics2016 Trends
Always Trending:
• Attract
• Develop
• Retain
Embarking on the People Analytics “Journey”• It’s a linear progression; start with the basics • Know where you are
DATA METRICS TRENDS ANALYTICS
Operations Generalists HRBPs/Leaders Analysts
“How Many” “Average” “Compared to last year”
“Strategic/Predictive” ?
#
Attract: Determining which colleges to recruit
Use Employee Engagement Survey data
Compare results from those that stayed and those that left regrettably
Row # Employee ID College 1st Performance Rating Months to 1st Promo1 10071 Waterloo 4 - Exceeds 122 10080 Stanford 3 - Meets All 19
3 10115 MIT 4 - Exceeds 144 10138 Harvard 5 - Redefines 115 10225 Waterloo 2 - Meets Most 18
6 10326 Georgia Tech 3 - Meets All 187 10402 MIT 4 - Exceeds 158 10425 Cal Tech 1 - Does Not Meet 209 10495 Waterloo 4 - Exceeds 14
10 10502 Austin 3 - Meets All 1711 10592 Olin 2 - Meets Most 2112 10595 U. Washington 5 - Redefines 10
13 10639 Harvard 5 - Redefines 1314 10650 MIT 3 - Meets All 1815 10688 Stanford 4 - Exceeds 16
16 10714 Olin 3 - Meets All 1517 10914 Georgia Tech 3 - Meets All 1718 10917 UT Austin 4 - Exceeds 14
19 10957 Harvard 5 - Redefines 1220 11012 Georgia Tech 3 - Meets All 1721 11154 Cal Tech 4 - Exceeds 1522 11192 UT Austin 4 - Exceeds 14
23 11309 Harvard 2 - Meets Most 18… … … … …… … … … …
100 15281 Stanford 3 - Meets All 16
Applicant Tracking System
Perf. Mgmt. & Compensation
The university recruiting team hires software engineers from college campuses; they’re looking to be as effective as possible
Rating Avg: 3.3
———— Promo Avg:
17.3
2.9 ————
16.7
3.9 ————
15.5
3.7 ————
15.2
4.3 13.4UT Austin
UC Berkeley
UW Seattle
Georgia Tech
Stanford
4.1 14.5
3.4 18
2.7 21
Olin
Harvard
Row # Offer ID College Accepted1 SF75535 Waterloo Yes2 NY15120 Stanford No3 SF45519 MIT Yes4 SF45621 Harvard No5 NY61352 Waterloo Yes6 SF46467 Georgia Tech Yes7 NY78015 MIT Yes8 SF31276 Cal Tech No9 NY47229 Waterloo Yes10 NY15753 Austin Yes11 SF47664 Olin Yes12 SF31786 U. Washington No13 NY63836 Harvard No14 SF31950 MIT Yes15 SF32064 Stanford No16 SF48213 Olin No17 SF65484 Georgia Tech Yes18 NY32752 UT Austin No19 SF32872 Harvard No20 NY16518 Georgia Tech Yes21 SF83655 Cal Tech Yes22 NY33576 UT Austin No23 NY84820 Harvard Yes… … … …… … … …500 SF54209 Stanford No
Acceptance: 77%
Acceptance: 77%
Acceptance: 58%
Acceptance: 81%
Acceptance: 43%
Acceptance: 60%
Acceptance: 88%
Acceptance: 52%
Attract: Determining which colleges to recruit
Applicant Tracking System
Perf. Mgmt. & Compensation
Carnegie Mellon
2
3
4
5
40 50 60 70 80 90 100
Georgia Tech
UC Berkeley
UW Seattle
Stanford
Olin
UT Austin
Redefines Expectations
Exceeds Expectations
Meets All Expectations
Meets Some Expectations
Acceptance Rate (%)
Step 1: Collect your data • Use two or more data sources • Link them (Employee ID works best)
Step 2: Build a “metric that matters” • Productivity/Performance • Retention
Step 3: Incorporate trend if applicable • Helps complete the picture • Insights hide in data
Step 4: Analyze, then tell a story
Attract: Determining which colleges to recruit
Carnegie Mellon
Harvard
Applicant Tracking System
Perf. Mgmt. & Compensation
Develop: Calculating Learning & Development Effectiveness
Salesforce
The sales enablement team has been tasked with improving the effectiveness of the sales team via Udemy for Business coursework.
Row # Employee ID Udemy Enrollment Q2 Sales ($) Q2 Sales Quota Q2 Attainment (%) Market1 10009 Prospecting 317,060 259,989 122.0 Mid-Market2 10102 Body Language 350,947 291,286 120.5 Mid-Market
3 10166 180,176 136,934 131.6 SMB4 10170 Body Language 417,359 425,706 98.0 Mid-Market5 10178 Prospecting 1,003,426 1,063,632 94.3 Enterprise
6 10369 887,804 1,056,487 84.0 Enterprise7 10421 983,699 983,699 100.0 Enterprise8 10505 Prospecting 410,987 337,009 122.0 Mid-Market9 10511 87,918 100,227 87.7 SMB
10 10590 133,087 159,704 83.3 SMB11 10593 Prospecting 359,960 359,960 100.0 Mid-Market12 10707 Body Language 951,456 856,310 111.1 Enterprise
13 10832 688,462 640,270 107.5 Enterprise14 10854 Prospecting 328,986 236,870 138.9 Mid-Market15 10865 254,746 277,673 91.7 SMB
16 10911 Prospecting 134,818 141,559 95.2 SMB17 10951 Body Language 511,224 475,438 107.5 Mid-Market18 10985 153,311 168,642 90.9 SMB
19 11045 Prospecting 548,828 554,316 99.0 Enterprise20 11186 Body Language 1,038,330 1,018,330 102.0 Enterprise21 11333 931,059 726,226 128.2 Enterprise22 11380 Prospecting 626,781 714,530 87.7 Enterprise
23 11400 Body Language 410,215 340,478 120.5 Mid-Market… … … … … … …… … … … … … …
100 14992 Body Language 210,634 240,478 87.6 SMB
Develop: Calculating Learning & Development Effectiveness
Learning & Development
DataSalesforce
The sales enablement team has been tasked with improving the effectiveness of the sales team via Udemy for Business coursework.
Sale
s Att
ainm
ent (
%)
0
20
40
60
80
100
120
0 200 400 600 800 1,000 1,200
Supercharged ProspectingSales And Body Language
Did not enroll in L&D coursework
Quarterly Sales (000’s)
Develop: Calculating Learning & Development Effectiveness
Learning & Development
DataSalesforce
Sale
s Att
ainm
ent (
%)
0
20
40
60
80
100
120
0 125 250 375 500
Develop: Calculating Learning & Development Effectiveness
Quarterly Sales (000’s)
Supercharged Prospecting
Did not enroll in L&D coursework
Sales And Body Language
Learning & Development
DataSalesforce
Sale
s Att
ainm
ent (
%)
0
20
40
60
80
100
120
300 400 500 600 700 800 900
Develop: Calculating Learning & Development Effectiveness
Quarterly Sales (000’s)
Supercharged Prospecting
Did not enroll in L&D coursework
Sales And Body Language
Learning & Development
DataSalesforce
Sale
s Att
ainm
ent (
%)
0
20
40
60
80
100
120
600 700 800 900 1,000 1,100 1,200
Develop: Calculating Learning & Development Effectiveness
Quarterly Sales (000’s)
Supercharged Prospecting
Did not enroll in L&D coursework
Sales And Body Language
Learning & Development
DataSalesforce
Sale
s Att
ainm
ent (
%)
0
20
40
60
80
100
120
0 200 400 600 800 1,000 1,200
Supercharged Prospecting
Did not enroll in L&D coursework
Sales And Body Language
Develop: Calculating Learning & Development Effectiveness
Step 1: Collect your data • Use two or more data sources • Link them (Employee ID works best)
Step 2: Build a “metric that matters” • Productivity/Performance Rate • Retention
Step 3: Incorporate trend if applicable • Helps complete the picture • Insights hide in data
Step 4: Analyze, then tell a story
Quarterly Sales (000’s)
Learning & Development
DataSalesforce
Row # Employee ID Demographic Data Regrettable Term within 1 year Participated Q1 Q2 … Q25
1 10001 Yes No ? ? ? … ?
2 10002 Yes No ? ? ? … ?3 10003 Yes No ? ? ? … ?4 10004 Yes No ? ? ? … ?
5 10005 Yes No ? ? ? … ?6 10006 Yes No ? ? ? … ?7 10007 Yes Yes ? ? ? … ?
8 10008 Yes No ? ? ? … ?9 10009 Yes Yes ? ? ? … ?
10 10010 Yes No ? ? ? … ?11 10011 Yes No ? ? ? … ?
12 10012 Yes No ? ? ? … ?13 10013 Yes Yes ? ? ? … ?14 10014 Yes No ? ? ? … ?
15 10015 Yes Yes ? ? ? … ?16 10016 Yes No ? ? ? … ?17 10017 Yes No ? ? ? … ?
18 10018 Yes No ? ? ? … ?19 10019 Yes No ? ? ? … ?20 10020 Yes Yes ? ? ? … ?
21 10021 Yes Yes ? ? ? … ?22 10022 Yes No ? ? ? … ?23 10023 Yes No ? ? ? … ?… … … … … … … … …
… … … … … … … … …2000 12000 Yes No ? ? ? ? ?
2014 Engagement Survey
Retain: Identifying Key Engagement Drivers of Retention
Engagement HRIS
The HR Business Partners have been tasked with identifying the key retention drivers at the company
40%
50%
60%
70%
80%
90%
100%
Month 3 Month 6 Month 9 Month 12
Survival Chart: I feel empowered to make bold decisions
Time since Engagement Survey
Moderate Driver of Retention
Answered Favorably
Answered UnfavorablyAnswered Neutrally
Retain: Identifying Key Engagement Drivers of Retention
Engagement HRIS
88%
78%
62%
40%
50%
60%
70%
80%
90%
100%
Month 3 Month 6 Month 9 Month 12
Survival Chart: I am given opportunities to develop skills relevant to my interests
Answered Favorably
Answered UnfavorablyAnswered Neutrally
Retain: Identifying Key Engagement Drivers of Retention
Time since Engagement Survey
Engagement HRIS
Strong Driver of Retention
92%
76%
45%
40%
50%
60%
70%
80%
90%
100%
Month 3 Month 6 Month 9 Month 12
Survival Chart: I believe my total compensation is fair, relative to similar roles at other companies
Answered Favorably
Answered UnfavorablyAnswered Neutrally
Retain: Identifying Key Engagement Drivers of Retention
Time since Engagement Survey
Engagement HRIS
Weak Driver of Retention
79%76%71%
Stop Relying On Anecdotes
Where are you in your journey?
DATA METRICS TRENDS ANALYTICS
Operations Generalists HRBPs/Leaders Analysts
“How Many” “Average” “Compared to last year”
“Strategic/Predictive” ?
Common Hurdles:
• Don’t have the analytics capabilities (talent)
• Don’t have enough data
• Don’t have enough resources (money)
My suggested approach:
• Gather your data and test your own hypothesis
• Find something interesting and gauge interest
• Ask for more time, data, and resources to explore the topic
“Young Company”Profile
The
“Mature Company” Common Hurdles:
• Don’t have the executive sponsorship
• Don’t have enough time
• Don’t have employee trust
My suggested approach:
• Take a reporting request and find the “question behind the question”
• Propose an analysis that would help take an anecdote to an evidence-based decision
• Ask for the time and white space to explore the topic - without pressure for a finding
Profile
The
Take Action
Questions? Connect with Culture Amp!
email: [email protected]
linkedin: thestevenhuang
More Resources:
www.peoplegeeks.com
People Geekly: http://bit.ly/pplgkly
People Geek Slack Channel: http://bit.ly/pplgeekslack
Steven Huang Data & Insights Strategist