Human Capital in Analytically- Driven Organizations: Attracting, Developing and Retaining Talent in a Competitive Market Presented by Rob Darby President at 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 employees What lessons have we learned so far? 2
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 3
Underwriting Valen How We Use Predictive Analytics 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. 4
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 5
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 Interpreting results 6
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 7
Getting Started 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 Synthesizers 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 8
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 9
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 Job (in)security 10
Growing Pains 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 11
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 12
What Are We Doing to Attract and Retain Talent Retain 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 Develop and articulate career paths Regular review, feedback, promotions Create and encourage horizontal opportunities Build a resume of different skills Increase visibility within firm 13
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 Specific alignment with work interests/competencies 14
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? 15
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