[aiim17] big data and its use in human capital and workforce planning decisions - cathleen hampton

© Hampton Resources, Inc. 2016 Proprietary, All Rights Reserved Slide 1

Big Data

And its Use in Human Capital and Workforce Planning Decisions

March 2017

Proprietary, All Rights Reserved Slide 2© Hampton Resources, Inc. 2016

Hell…

…is for Real!


Dante’s Nine Circles of Hell


Was Dante a Recruiter?

Too experienced

Too weak

Moved around too much

It hurts to read this resume

Experience is too dated

We haven’t used that skill in 15 years…

This is great, but…Long periods of unemployment

This guy’s held the same job title for 10 years!

I’d rather have someone with a higher level of education

Community college? Really?

They’re asking for how much? Gee, I wish I made that much when I was their age!


Artificially Intelligent

Hiring Manager…?

Magic

Predictive

Analytic

Report

Bad Resume

Old Skills

Too Weak

Too Mobile

No Progression

Experience

Degree


Prove the Ideal is Really Ideal…Wait, What?

At best, Big Data identifies correlations not causation.


Squaring Dante’s Circles is like Herding Cats

Recruiting success factors– Predictive success factors

• Skills measurements• Years experience• Educational achievements• Job progression

– Ideal behavioral indices• Self starter• Independent • Reliable


And the EEOC is Watching“Employers should be concerned with the disparate impact of their employment-related data mining and analysis….the first step is to show and look at the tool. Does it cause a disparate impact? Once you get there, the tool would be considered illegal if it does not accurately predict success in the job.“…indeed, if you do possibly have prejudices built into the data, something might be validated as predicting success on the job…. So there’s going to be a lot of interesting thought that needs to be done and technology work, really, around understanding how to validate these kind of concerns.”Carol Miaskoff, EEOC Assistant Legal Counsel, September 2014


Disparate ImpactOffice of Federal

Contract Compliance

Programs (OFCCP)

Equal Employment Opportunity Commission

(EEOC)

Office of Labor-Management

Standards (OLMS)

Employment and Training Admin

(ETA) Employee Benefits Security

Admin (EBSA)Office of Disability

Employment Policy

(ODEP)

Occupational Safety and

Health Admin (OSHA)

Office of Workers’ Compensation

Programs (OWCP)

Wage and Hour

Division (WHD)

Office of Public Engagement

(OPE)

Department of LaborPending New

Secretary


The Real World of HR

AND Reliab

le

Predictive Criteria

Defendable


“Born Digital, Stays Digital”

With regulatory focus on “bad business” practices– Leading the pack – risky– Lagging the pack – terminal– The safe zone – benchmark

Find synergy between data and actionable insights– Recognize the need to harness volumes of data– Blend structured and unstructured data– Establish and disseminate a single version of “truth”– Develop techniques for timely analysis and interpretation– Produce highly interactive data visualization


Strategic Imperative

Business Risks

Negative Business

Impact

Organizational Impact

AnalysisPeople

Technology

Processes


Impact Analysis


Questions to Be Answered• Data ultimately tells a story… a story based on bias

– Has the technology been validated? If so, how?– Is there a legal agreement with the Big Data Analytics Provider?– How and what are we capturing?– Is the data accurately reflecting optimum performance indices?– How do we segregate “silly data” from actual predictive data?– Analytically, is bias “baked into” the data?– Can we reliably and consistently defend our determinations?– Are we confident decisions are legally sound?– Is obsolete, irrelevant, or biased data purged?


In Summary, Dig DeeperThink discriminatory pattern or practice bias

– “Hidden” or “subjective” bias – “Horizon of conditions”

Are we prepared to defend by “show[ing] and look[ing]” at OUR OWN tool?

– Can we confidently answers key questions?– What about data storage and those hidden traps?– Compliance reporting capabilities need to go beyond the standard

report capabilities…what does that really mean?– Transparency of data is going to be vital moving forward.

While IT owns the tools, HR MUST own the Rules


Thank You!

Presenter:Cathleen M. Hampton

Hampton Resources, Inc.(703) 794-9442

Email: [email protected]: www.HamptonResources.com

LinkedIn Profile: http://www.linkedin.com/in/crihr/ Twitter: HamptonCM

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