Data Con LA 2020 Description The People at any organization are one of the most important stakeholders in the business. People Analytics & Research is the broad discipline in which employee data is leveraged to inform organizational decision-making. In current times, data science has found its way into People Analytics and Research with individuals using AI to predict or diagnose important metrics like turnover. However, it is only through ethical, context-driven, and inclusive methods that data science can continue to intelligently augment human resources. This talk will help attendees recognize and describe People Analytical challenges within their organizations and teams. Further, through a discussion of real-world examples, attendees will appreciate the need for inclusive and ethical context-driven best practices for People Analytics. Finally, attendees will be able to explore applications of AI/ML to problem solving for the People Analytics space. This is an interactive session, so please bring your questions, and get ready to put your thinking hats on! Speaker Sreyoshi Bhaduri, McGraw Hill, Manager, Global People Research and Analytics

1. DR. SREYOSHI BHADURI
(People) Analytics
@ThatStatsGirl
www.thatstatsgirl.com
DataScience

2. Hi!
I'm Sreyoshi
A People Researcher & Engineer.
I currently lead Global People Research & Analytics at
McGraw Hill. My work leverages data from employees to
better the employee experiences.
www.thatstatsgirl.com

3. Goals for this session(People)
first
Analytics
www.thatstatsgirl.com
Recognize and describe People Analytics
challenges within your organizations/teams.
Understand the need for inclusive and ethical
context-driven best practices for People Analytics.
Explore applications of AI/ML to People Analytics
problem solving within your organizations/teams.

4. Goals for this session
www.thatstatsgirl.com
Recognize and describe People Analytics
challenges within your organizations/teams.
Understand the need for inclusive and ethical
context-driven best practices for People Analytics.
Explore applications of AI/ML to People Analytics
problem solving within your organizations/teams.
WHAT IS PEOPLE ANALYTICS?
WHY IS IT IMPORTANT TO BE
INCLUSIVE & CONTEXT DRIVEN?
HOW CAN I BEST USE AI/ML IN
PEOPLE ANALYTICS?
2
1
3

5. What is
People Analytics?
1
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6. Have you heard of
People Analytics at
your organization?
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Put on your thinking hats
Type into the chat box.

7. 1
www.thatstatsgirl.com
has several names...
People Analytics

8. People Analytics, 1
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Talent Analytics,
Workforce Analytics,
HR Analytics are similar, NOT same...

9. People Analytics is...
1
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G A L , J E N S E N & S T E I N , 2 0 1 7
"A data-driven approach to managing people at work."
H E U V E L & B O N D A R U K , 2 0 1 6
"A systematic identification and quantification of the people
drivers of business outcomes."

10. People Analytics data can be -
1
www.thatstatsgirl.com
Demographic- related
Engagement- related
Interaction-related

11. People Analytics task can be -
1
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Descriptive
Predictive
Diagnostic

12. Demographic- related
Engagement- related
Interaction-related
People Analytics example -
1
www.thatstatsgirl.com
Descriptive
Predictive
Diagnostic
At the current rate, how many years will it take for our
senior leadership to comprise atleast 70% diversity?

13. What potential does People
Analytics have within your
team/organization?
www.thatstatsgirl.com
Type into the chat box.
Put on your thinking hats

14. 1
www.thatstatsgirl.com
E M P L O Y E E
L I F E C Y C L E
Attraction
Recruitment
O
nboarding
Engagement
Prom
otion
Retention
Separation
Consider the
employee
experience...

15. 1
www.thatstatsgirl.com
E M P L O Y E E
L I F E C Y C L E
Attraction
Recruitment
O
nboarding
Engagement
Prom
otion
Retention
Separation
"People analytics are needed to take
massive amounts of data being
generated before, during, and after the
recruting process and turn it into
actionable information."
S T E V E L E V Y , I N D E E D

16. 1
www.thatstatsgirl.com
E M P L O Y E E
L I F E C Y C L E
Attraction
Recruitment
O
nboarding
Engagement
Prom
otion
Retention
Separation
within Hiring/Recruiting/Talent Acquisition -
People Analytics can help drive with data as we hire the
best candidates for roles within our organization.
It also helps answer questions like -
Q: How long does it take to hire for a role?
Q: How diverse is our applicant slate?
Q: Is there unconscious bias in who/how we hire?

17. Why is it important to be
inclusive & context-driven ?
2
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18. 2
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L A Z L O B O C K , 2 0 1 5
i n W O R K R U L E S , f r o m h i s t i m e a s S V P P e o p l e O p e r a t i o n s , G o o g l e
"Don't trust your gut.
Use data to predict and shape the future."

19. Advancements in AI and ML have allowed us
to extend the boundaries and capabilities
of predictive analytics.
There is widespread belief that:
Algorithmic Intelligence
can replace
Human Intervention.
2
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20. Algorithmic Intelligence
can replace augment
Human Intervention.
2
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21. 2
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Our algorithms have bias!

22. 2
Our algorithms have bias!
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23. 2
In People Analytics,
bias can lead to
undesirable outcomes
including discrimination.
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24. What ways might the
pandemic have impacted
your team/organization?
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Type into the chat box.
Put on your thinking hats

25. www.thatstatsgirl.com
2
E M P L O Y E E
L I F E C Y C L E
Attraction
Recruitment
O
nboarding
Engagement
Prom
otion
Retention
Separation
Think of People
Analytics as -
Voice. Choice. Care.

26. How can I best use ML/AI in
People Analytics?
3
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27. What are some ways you can
reduce bias in the algorithms
you develop?
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Type into the chat box.
Put on your thinking hats

28. Descriptive
Predictive
Diagnostic
Demographic- related
Engagement- related
Interaction-related
www.thatstatsgirl.com
Researcher(s) Outcomes
Data Types Tasks
3

29. www.thatstatsgirl.com
Researcher(s) 3
Type into the chat box.
Do researchers contribute to
algorithmic bias?

30. Demographic- related
Engagement- related
Interaction-related
www.thatstatsgirl.com
Data Types
3
Type into the chat box.
How can our data be biased?

31. Descriptive
Predictive
Diagnostic
www.thatstatsgirl.com
Tasks
3
Type into the chat box.
How can bias in our methods be reduced?

32. www.thatstatsgirl.com
Outcomes
3
Type into the chat box.
How can bias in our outcomes be reduced?

33. Descriptive
Predictive
Diagnostic
Demographic- related
Engagement- related
Interaction-related
www.thatstatsgirl.com
Researcher(s) Outcomes
Data Types Tasks
3Sampling bias
Measurement bias
Exclusion bias
Experimenter bias
Confirmation bias

34. Reflect: Are you able to-(People)
first
Analytics
www.thatstatsgirl.com
Recognize and describe People Analytics
challenges within your organizations/teams.
Understand the need for inclusive and ethical
context-driven best practices for People Analytics.
Explore applications of AI/ML to People Analytics
problem solving within your organizations/teams.

35. DR. SREYOSHI BHADURI
@ThatStatsGirl
www.thatstatsgirl.com
Thank you!
(People) Analytics
DataScience