The Last Mile Problem
How Data Science and Behavioural Science can Work Together
IPAC Toronto
James Guszcza, PhD, FCAS, MAAA Deloitte Consulting
Two overdue sciences
“Why do professional baseball executives, many of whom have spent their lives in the game, make so many colossal mistakes? …
It takes time and effort to switch from simple intuitions to careful assessments of evidence.”
— Thaler and Sunstein review of Moneyball
“Many programmes and services are designed not for the brains of humans but of Vulcans. Thanks in large part to Kahneman and his many collaborators pupils and acolytes, this can and will change.”
Classic examples of data science
(aka “Moneyball” aka “big data”)Predictive models can be used to:
• Hire more effective employees (Moneyball)
• Predict who is most likely to default on a loan (credit scoring)
• Predict who is most likely to crash their car… and how badly (actuarial science) • Predict next best offer, customer churn, lifetime value (marketing science)
• Predict recidivism (law)
• Identify episodes of waste, fraud, abuse (government) • Identify unsafe workplaces (risk management)
• Identify physicians at highest risk of being sued for malpractice (risk management) • Identify divorced parents most likely to lapse on child support payments
• Predict healthcare utilization
• Estimate risk of such disease states as diabetes, hypertension, heart disease • Predict college grades using high school transcript data
Data science – a narrow frame
DATA MODEL
Data Science as a Strategic Capability
“All statistics is consulting” – Andrew Gelman
DATA MODEL
Data Science as a Strategic Capability
“All statistics is consulting” – Andrew Gelman
DATA MODEL
STRATEGY
Our focus: “the last mile problem”
Predictive models can point us in the right direction… they can tell us whom to target…
but they don’t tell us how to prompt the desired
Our focus: “the last mile problem”
Predictive models can point us in the right direction… they can tell us whom to target…
but they don’t tell us how to prompt the desired
behaviour change. Furthermore:
Behavioural insights without
data analytics motivate one-size-fits-all intervention
strategies.
Our focus: “the last mile problem”
Predictive models can point us in the right direction… they can tell us whom to target…
but they don’t tell us how to prompt the desired
behaviour change. Furthermore:
Behavioural insights without
data analytics motivate one-size-fits-all intervention
strategies.
MODEL
Can we do better by working together?
Yes they did
Motivating example: the 2012 Obama reelection
campaign used predictive models to identify whom to target.
Yes they did
Motivating example: the 2012 Obama reelection
campaign used predictive models to identify whom to target.
It also used behavioural insights to more effectively act upon the predictive model indications.
Supporting child support
Predictive models are increasingly used to guide child support
enforcement officers to
non-custodial parents at highest risk of lapsing on their child support
payments.
Commitment cards could be field tested to prompt the desired behavior change.
Push the worst, nudge the rest
The city of New York uses predictive models to deploy building inspectors to the highest-risk buildings.
Behavioural nudge tactics could be employed to ameliorate lesser risks that don’t merit immediate physical inspections.
Let’s keep ourselves honest
Government agencies, tax authorities, insurance companies, regularly employ statistical fraud detection methods to guide fraud investigators to the most suspicious cases.
• But many forms of fraud are ambiguous or matters of degree (“soft fraud”)
• And fraud detection algorithms yield false positives
Behavioural nudge tactics are “soft” interventions that are well-suited to such ambiguities.
Invoke peer effects and people’s “internal reward systems”… not just hard incentives…
Driving behaviour change
Actuaries now use telematics data to better segment and price insurance policyholders in terms of their utilization and riskiness.
But could the data be used to create new products and services… … periodic or real-time reports that serve as behavioral nudges …
Ideas
• Detailed feedback reports to help student
drivers learn and older drivers stay behind the wheel longer and safer
• Feedback prompting carbon footprint
Personalized health coaching
Lifestyle and medical data can used to predict individuals’ healthcare utilization and likelihood of various disease states. But once we’ve identified the highest risks, what can be done to change behaviour?
Health coaches are a promising behavioral strategy.
Furthermore: analytics could be used to guide the hiring and matching of health coaches with patients.
