people analytics 2016 - shareable

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People Analytics 2016

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Page 1: People Analytics 2016 - Shareable

People Analytics 2016

Page 2: People Analytics 2016 - Shareable
Page 3: People Analytics 2016 - Shareable

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

Page 4: People Analytics 2016 - Shareable

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” ?

#

Page 5: People Analytics 2016 - Shareable

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

Page 6: People Analytics 2016 - Shareable

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

Page 7: People Analytics 2016 - Shareable

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

Page 8: People Analytics 2016 - Shareable

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.

Page 9: People Analytics 2016 - Shareable

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.

Page 10: People Analytics 2016 - Shareable

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

Page 11: People Analytics 2016 - Shareable

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

Page 12: People Analytics 2016 - Shareable

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

Page 13: People Analytics 2016 - Shareable

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

Page 14: People Analytics 2016 - Shareable

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

Page 15: People Analytics 2016 - Shareable

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

Page 16: People Analytics 2016 - Shareable

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%

Page 17: People Analytics 2016 - Shareable

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%

Page 18: People Analytics 2016 - Shareable

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%

Page 19: People Analytics 2016 - Shareable

Stop Relying On Anecdotes

Page 20: People Analytics 2016 - Shareable

Where are you in your journey?

DATA METRICS TRENDS ANALYTICS

Operations Generalists HRBPs/Leaders Analysts

“How Many” “Average” “Compared to last year”

“Strategic/Predictive” ?

Page 21: People Analytics 2016 - Shareable

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

Page 22: People Analytics 2016 - Shareable

“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

Page 23: People Analytics 2016 - Shareable

Take Action

Page 24: People Analytics 2016 - Shareable

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