Human Capital in
Analytically-Driven Organizations:
Attracting, Developing and Retaining Talent
in a Competitive Market
Presented by Rob Darby
President at Berkshire Hathaway Homestate Companies
What I Am Going To Talk About Today
How we are using Predictive Analytics
and Data Analysis as an insurance
company
How the shift toward a data-driven
business impacts our hiring/screening
process
The cultural implications of changing
the hiring paradigm
How we compete for talent in a
business world that is increasingly
reliant on quantitatively-gifted
Insurance Is Particularly Well-Suited For
Predictive Analytics
Lots of available data
Loss potential correlates strongly
with certain variables that can be
measured and for which data is
available - Pricing
Claims severity also correlates
with demographic characteristics
of injured workers – Controlling
our “cost of goods” = claims cost
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How We Use Predictive Analytics
Underwriting –
– Valen
– Internal models
Claims
– Grading claim severity based on
nature of injury, and other variables
that correlate to outcome:
• Age, sex, BMI, co-morbidities, litigation rate in region where claim occurs, etc.
• The first month after date of injury is critical for controlling cost
• Getting the right people managing the right claims early on – claims scoring.
Claims/Medical Management
– Which MDs/medical facilities
achieve the best outcomes
• Refine networks in states where you can
– Attorney involvement – which are
best vis-à-vis outcomes
• Refine panels
– Quality of data coding is a challenge
HR
– Improve quality of hire – performance,
retention, time to promotion
– Identify turnover risks
– Improve engagement and performance
– Correlation of hiring variables with “success”
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Barriers to Using Predictive Analytics
Quality/Availability of data
Finding correlations that are valuable in forecasting
– Correlation v Causation
– Over fitting to historical data
– Changes in underlying conditions require that predictive
models be dynamic
– Internal resistance
Skill set issues
Internal Resistance to Predictive Analytics
“Not the way I was taught to think about
underwriting/claims, etc!”
Mistrust of numerical analysis – “The
Actuarial Coup”
Skill sets that the Insurance Industry has
hired for historically do not match up with the
analytic rigor required to interpret and act on
model output
Machines are replacing people! Some
people call our underwriting model “the
robot”
Egalitarian Managers – segmenting work
through data analysis, i.e. claim scoring, can
create hierarchical work models
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Getting Started
Underwriting and Claims training
programs started in 2009 and 2011,
respectively. We decided that a “grow
from scratch” model was the only way
to teach the “right” habits.
– It is harder to change people who have been taught under a different paradigm and whose skill sets may be more
aligned with a traditional model
We have hired over 40 underwriting
associates and over 200 claims
associates
Predictive AnalyticModels are TOOLS to help humans make better and more informed decisions; however, the models need people who can synthesize
quantitative and qualitative data in their decision making – a new paradigm for hiring – “Dot
Connectors” or “Dual Hemispheric
Screening Process
•
Looking for analytic aptitude:
– Score higher in math/quantitative testing
– Demonstrate an ability to use both hemispheres of their brains in their work – we have applicants solve hypothetical business problems as part of interview
• Google and other tech firms are well ahead of the insurance industry in screening talent in this way
•
Looking for high fit with:
– BHHC culture
– The day-to-day work to be performed – Comfort with analytic decision making
•
Looking for potential:
– Management track – Technical leader track
– “Success” is defined for either track – Avoid the “Peter Principle”
Issues as We Transition
•
Turnover with the Associates is
high.
– This was an expectation
going in
– The impatience of the
Associate group is elevated:
• Compensation
• Pace of advancement • Expectations are raised
working in the Bay Area where comparisons to other entry-level positions may be unfavorable for us as an insurance company
•
The new associates cause
stress for tenured staff –
– Higher expectations from
management
– Skill sets can be vastly
different
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•
Interestingly, we are finding that
“Millennials” with high quantitative
scores can be inflexible and socially
immature – this is where the tenured
staff adds value in the training
process: client relationship
management/interpersonal
communication
– High IQ/Analytic skills do not correlate perfectly to “success” – We are starting to track
success/failure against hire
characteristics for certain positions to see if out screening process needs refinement
Growing Pains
•
It is challenging for us as an
insurance company to attract
and retain the type of talent
that is going to be successful
in an increasingly data-driven
world
– Competition with sexier industries: social media, software development, financial analysis
– We have to demonstrate that insurance is an interesting and lucrative career without offering beanbag chairs, free lunches, and six-figure
salaries for entry level positions
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– Attract
• Articulate a value proposition for working
at Berkshire
• Align aptitude and position
– Not all positions require math geniuses
• Pay competitive wages
• Offer work/life balance
What Are We Doing to Attract and Retain Talent
– Retain
• Develop and articulate career paths
• Regular review, feedback, promotions
• Create and encourage “horizontal opportunities”
– Build a resume of different skills – Increase visibility within firm
What Might the Future Look Like?
• More and better data and analytics on ‘what
works’
• More competition for data scientists, employees
and leaders who can best work with data
• More competition among companies using
analytics – if we’re all working with better models
and data, we must continue to go deeper
• The ‘Uberization’ of non-proprietary work
– “On demand” economy
– Flexible work schedules
Quantitative skills are becoming
increasingly valuable in business, including insurance
Increased competition for these skills is making hiring and retaining talent difficult especially in job markets like the Bay Area
He who analyzes best, wins. It is all about collecting, mining, and analyzing data to get an edge on competition
The hiring paradigm must change to compete in a world that feeds on “Big Data”
Changing hiring profiles will cause stress with existing employees who were hired when “industry experience” was valued more than raw analytic ability
Cultural changes are inevitable and painful…but there is no other way to
survive and win if you don’t embrace data analytics in your decision-making process
How do I get started?
Berkshire Hathaway
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