Boryana Dineva, VP, Human Resources, Wikimedia Foundation Are you paying close attention to the trends coming out of your referral program? If you aren’t, you should. It’s good stuff. Boryana's former team realized they were short-sighted when simply paying referral bonuses quarter after quarter, only monitoring the volume of referrals and the budget impact of the program. As referrals and employee data built up, her realized they possessed a rich dataset that could be mined for meaningful trends. As a result, positive change was driven throughout the company to shape culture, increase talent caliber, and even help diversity. Join this session to learn about the many strong correlations between referral and referee attributes and how Boryana has applied those correlations to help drive or supplement various talent initiatives—and how you can do the same. Check out the best of Talent Connect: http://bit.ly/1MBqz6m

2. Boryana Dineva
VP of Human Resources
Wikimedia Foundation
The Warrior, The Crab and The Wild Card

3. Game plan
My story in 3mins (+ The Secret Sauce)
Culture
Program
What we knew
What we didn’t know - BIG DATA
What we found
What can you do today?
Q & A
Note: All numbers in this presentation are dummy data and for illustrative purposes only.

4. My Story

5. Numbers,
Stats,
Data,
…
Psychology,
Feelings,
Words,
Policy,
…
HR
Data
Scientists
The
Business
Bring Data
(+ The Secret Sauce)

6. The Tesla Culture
1. Competitive to be the best in all that we do
2. No fear of solving hard problems ourselves
3. Be entrepreneurial, resourceful
4. Minimize bureaucracy, just get it done
5. Efficient and sustainable (demonstrate our mission)
6. Work hard, love what we do, have fun!

7. What we knew
~20% of all new hires
Manufacturing: High %, less hired
Engineering: Smaller %, almost all hired
Sales & G&A: In between
NA good
EMEA better
APAC MIA Note: All numbers in this presentation are dummy data and for illustrative purposes only.

8. What we didn’t know
Are they any good?

9. What we didn’t know.
Time To Fill: Shorter for Referral vs Regular Hire?
Cost: Referral vs Regular Hire?
Diversity: More or less through referrals?
Social dynamics:
Who refers who?
Same group or cross-functional?
Retention
Performance

10. BIG DATA

11. What we found
Time To Fill: Shorter for Referral vs Regular Hire?
Cost: Referral vs Regular Hire?
Diversity: More or less through referrals?
Retention (!)
Social dynamics(!)
Performance (!)

12. Referred
Not Referred
Note: All numbers in this presentation are dummy data and for illustrative purposes only.
0.40
0.50
0.60
0.70
0.80
0.90
1.00
Referred Employees stay longer.
Employees that refer stay longer.
Successful referrers stay longer.
0.70
0.75
0.80
0.85
0.90
0.95
1.00
Made Referral
Never Made Referral
0.70
0.75
0.80
0.85
0.90
0.95
1.00
Referral Hired
Referral Not Hired

13. The warrior.
The crab.
The wild card.
(5-10%)
(10-20%)
(30-50%)
(5-10%)
Note: All numbers in this presentation are dummy data and for illustrative purposes only.

14. 1. Download data and start building your big data:
Variables on referrers
Variables on referrals
2. Use the program to drive or supplement:
Hiring pushes
Diversity
Recognition
Engagement
What can you do today?

15. Boryana@Wikimedia.org
Boryana.Dineva@gmail.com
Q&A

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