Analytics in practiceDriving your business and saving you money Todd Nicholson February 2012
Three examples of analytics in practiceDomestic Tourism Segmentation(Ministry of Tourism)Serious Injury Model(ACC)Claim Duration Model(ACC)
Example 1: Domestic Tourism SegmentationWant to understand targetable groups within the NZ tourism marketWant to profile each segment so we know: - who they are - what they want - how to reach themWant to ensure each segment can be targeted
Key learning: Always keep your target audience in mind
Key learning: Always keep your target audience in mindEnsured all segments were marketable by segmenting on: - interests - age - ideal holiday type - inhibitors of travelThis gets us away from segmenting on holiday frequency and directs us towards holiday type.
Example 2: ACC serious Injury ModelACC has just over 5000 seriously injured clients. For these clients ACC provides:- Carers to help with day-to-day living- Weekly compensation and medical expenses- Capital itemsThe outstanding claims liability is currently $9.3 billion.However, increasing consistency is one of the ways growth in expenses has been successfully dampened.
Analytical models can give you transparency and consistencyNumber of care hours per week Functional Independence Measure
Key Learning: Milk your results When dealing with people there willNumber of care hours per week always be variation. So lets measure it! Functional Independence Measure
National serious injury service- Evidence based needs assessment- $820 million reduction in outstanding claims liability (due to the hard work of the serious injury team – this is simply a tool they’ve commissioned to help them).- Minimal bad publicity or media comment involving clients with a disability- No change in the usual, small number of legal challenges to decisions- An increase in the number of clients achieving their self directed outcomes
Example 3: Claim duration analysis (ACC)• ACC has over 50,000 weekly compensation claims every year• They cost almost $1 billion a yearAim of the analysis: to accurately predict claims duration based on past experienceUltimate Goal: to make better decisions about services required and achieve shorter claim durations
International tools – Medical Disability Advisor (MDA)
Key learning: Know the power of your data!• ACC’s data is not perfect. For example, losing your job is a key risk factor but isn’t recorded in ACC data.• But it is still the best dataset available anywhere in the world for modelling injury recovery – Longevity – Universal coverage – No coming or going
Know the power of your data!There is nothing magic in our analysis. Its just• Survival analysis• Logistic regression• Generalized Linear Modelling (GLM)• Text mining (yes, even free text data can be a gold mine)The real difficulty is dealing with such a large amount of data
Milk your results (again!)Two parts of the analysis have been implemented for frontline day-to-day use• They allow branches to accurately identify which claims will require weekly compensation• Staff can take a more proactive approach• Staff can ensure high risk clients receive the correct services right from the start
Milk your results• Predict which claims are likely to last for a long time and WHY• Draws case managers’ attention to potential risks• Allows accurate allocation of resources – identifying clients who need no services is as important as those who need a lot.
Milk your results 1Proportion of claims still open 0.8 0.6 High Risk Claim 0.4 Low Risk Claim 0.2 0 -30 20 70 120 Weekly compensation days
So remember• Always keep your audience at the front of your mind• Prettiness is important• Milk your results• Models can give you consistency and transparency• Don’t underestimate the power of your data