Human Capital in Analytically- Driven Organizations: Attracting, Developing and Retaining Talent in a Competitive Market







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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


How the shift toward a data-driven

business impacts our hiring/screening


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

Berkshire Hathaway



How We Use Predictive Analytics

Underwriting –

– Valen

– Internal models


– 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


– 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


Egalitarian Managers – segmenting work

through data analysis, i.e. claim scoring, can

create hierarchical work models

Berkshire Hathaway



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


Predictive Analytic

Models 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


– 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


– Skill sets can be vastly



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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



– 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


– 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


Berkshire Hathaway


– 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


• 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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