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Transcript of Turbocharging the recruiting engine: How LinkedIn used data to drive recruiting efficiency | Talent...
Jennifer Shappley Director, Talent Acquisition, LinkedIn
How LinkedIn Used Data to Drive Recruiting Efficiency
Chris Pham Data Scientist, LinkedIn
How LinkedIn Used Data to Drive Recruiting Efficiency
• The analytics performed to estimate hires• How we achieved alignment between
Recruiting, HR, and Finance• How we held Recruiting accountable• Impact and lessons learned• Q&A
Agenda
LinkedIn operates the largest professional network on the internet
450M+ members around
the globe
+2 new members
per second
10K employeesworldwide
30 cities around
the globe
45% headcount growth
rate per year
Headcount Plan is finalized
Visualization shown is for illustrative purposes only
With timing of budget planning cycles, Recruiting is never in line with business demand
How does Recruiting become more strategic when it comes to meeting hiring demand?
Forecasting hires and staffing Recruiting teams accordingly
Workforce Plan -forecasting hiring demand-
Incremental Hiring Backfill Hiring “Ripple” Effect
FP&A Incremental Headcount Plan
Org Shape
Incremental Hiring by Level!
Attrition Rates
Transfer Probabilities
PromotionRates
Probability ofInternal Transfer
(r)
1
Adjusted Backfill!Hiring by Level!
Backfill Hiring!By Level!
( 1 - r )________
Forecasting hires and staffing Recruiting teams accordingly
Capacity Plan -determining people needed to meet targets-
Seasonality
Incremental Headcount by Month
Historical seasonalityof terminations
18 sub-BUs and 5 regions
Total hiring by BU, Region, Level and !
Month!
Recruiting Resources
Recruiter Productivity(hires per month)
Support Ratios
Manager Span of Control
Talent Acquisition!Headcount!
Forecasting hires and staffing Recruiting teams accordingly
Incremental Hiring Backfill Hiring “Ripple” Effect
FP&A Incremental Headcount Plan
Org Shape
Incremental Hiring !by Level!
Attrition Rates
Transfer Probabilities
PromotionRates
Probability ofInternal Transfer
(r)
1
Adjusted Backfill!Hiring by Level!
Backfill Hiring!By Level!
( 1 - r )_________
Backfill Hiring “Ripple” Effect Seasonality Recruiting Resources
Incremental Headcount by Month
Historical seasonalityof terminations
18 sub-BUs and 5 regions
Total hiring by BU, Region, Level and
Month!
Recruiter Productivity(hires per month)
Support Ratios
Manager Span of Control
Talent Acquisition!Headcount!
Workforce Plan Forecasting hiring demand
Capacity Plan Determining people needed to meet targets
NAPKIN
How do we enforce operational excellence and accountability?
Meet Regularly
Drive Alignment
Adjust as Needed
A new operational framework between Analytics & TA Leadership
Check your Assumptions
• TA lead & Analytics partner meet monthly to review resourcing and attainment to plan
• Review demand
• Is attrition what we expected?
• Did we accurately plan for
demand?
• This will be a dynamic process – review regularly and make necessary adjustments
• Partner with Analytics to
recalibrate model based on actual outcomes
• Ensure you’re aligned with your business leaders
• Regularly sync with Finance
and Human Resources
Involving the right Stakeholders
Talent Acquisition HR Business Partner
Finance Business Leader
Capacity of TA team, insight into employment trends
Insight into workforce trends, attrition and organizational
changes
Timing of hires to align with budget
Where will the team be growing? What skillsets will be needed in
the future?
TalentAnalytics
95% of actual hires were accurately predicted by our model
13% of our annual budget was given back to the business
• The modeling done would’ve been useless if we hadn’t turned it into an actionable plan
• Recalibrating the model when necessary
• Transparency of data across all recruiting teams to break down silos in how teams managed productivity and performance
• Buy-in is hard
• Don’t wait for the stars to align
• You don’t need perfect data quality, or complex tools, or even an analytics team
Lessons Learned