Speech to the SAS Users New Zealand Conference

E nga mana, e nga reo, e te iwi o te motu, tena koutou, tena koutou, tena koutou katoa

It’s a pleasure to be here this morning to open the SAS Users New Zealand conference.

We’re at a very exciting place at the moment.

The world of data analytics is new for a lot of people in Government, and just a little bit scary for some.

But the way I see it - by harnessing the skills analysts like you have when you look at information, we have the power to change - and save - lives. 

In business and the corporate sector, data collection has long been used to analyse customer habits, and best meet the needs of clients.

So why can’t Government do the same?

Why can’t we get smarter with the huge amount of information we have on people, and use it to better support them?

With departments like MSD taking the same approach to data analytics that the corporate sector has been doing for decades, we have a huge opportunity to help children, families and individuals overcome the barriers they face, and thrive.

Through the Investment Approach to welfare, the Children’s Action Plan and cross-Government work, the careful analysis of information is starting to make a difference.

There is a great deal of information out there - but it is only useful if we can look at it in a way that helps transform lives.  

With the help of professionals like you that is exactly what we are doing.

Since 2011, analytics have been at the heart of our welfare reforms.

And the reason for reform?

• Over 352,000 people on benefit in December 2010, or 13% of the working age population.

• 161,000 people received a benefit for at least half of the previous 10 years.

• 139,000 had spent more than a decade on benefit since 1993.

• 220,000 children in benefit dependent homes.

The welfare system was not providing people with the support they needed to build a better future for themselves.

It was passive rather than active - and it was not as work-focused as it could or should have been.

One of the first steps we took to turn this around was to develop a model which estimated the risks of welfare dependency among school leavers.

Working alongside the Ministry of Education, we began to pull apart data on school leavers that looked at things like:

• Qualifications.

• Suspensions and expulsions.

• Reasons for leaving school.

• The age at which they left.

That was combined with information from Work and Income and Child, Youth and Family, to create a ‘probability factor’ of a young person going on benefit within 3 years of leaving school.

This age-group are often vulnerable at the best of times, and even more so during times of economic crisis.

For example, the number of young people receiving the unemployment benefit peaked at 23,000 in 2010, up from 10,500 just a year earlier.

By understanding the patterns within this group at a level of detail never before examined, we were able to develop a system of support directly targeted at catching young people before they turn to the benefit.

That was the Youth Services initiative, which we introduced in 2012.

I’m proud to say we’re now seeing the lowest number of youth people not in employment, education, or training since 2008. 

There has also been an increase of 28,500 (9.3%) 15 to 24 year-olds in work over the past year.

We then wanted to go one step better.

A Baseline Valuation of the welfare system had never been attempted before.

Why not? The Government - and the taxpayer - spends around $8b on benefits a year, that’s $22m a day.

A key feature of the valuation, which was first carried out in 2011, was the use of the analytical technique of ‘segmentation’.

The commercial sector has long been doing this - grouping together people at similar stages of life with similar characteristics, to better understand their needs.

So we did it with our clients, and the numbers were astonishing.

What we saw was that those on UB - which is where interventions had been almost exclusively focused, only made up 5% of lifetime costs on welfare.

That’s a fraction compared to the lifetime costs of sole parents (23%) and those on Sickness (9%) and Invalid’s Benefits (24%), but UB was where our investment was going.

The total lifetime cost of all beneficiaries was put at $78 billon. 

That included over $1 billon for just 4,000 16 and 17 year olds.

By being better informed about who was receiving a benefit and how long for, we can make better decisions about the support and investment they need.

We can identify what’s not working well, and redirect our spending to where it’s more effective.

That’s helping sole parents, who we’re now targeting with more investment than ever before.

The last 12 months saw over 8,000 sole parents come off benefit, a 9.4% drop.

We’ve now completed three valuations, and are increasingly able to understand who our clients are and what services are helping them get ahead.

This is light years away from how it was in the past, with every person on benefit getting the same support whether that’s what they need or not.

Businesses don’t work like that, and now the welfare system is catching up, thanks to technology and data.

As you all know analytics and ‘big data’ are growth industries at the moment.

Technology is only going to get more powerful and more sophisticated.

The Government is belatedly embracing this, and finally realising that working smarter with the information we have is the key to unlocking the door of effective investment and action.

Data analysis, and the work that you do, is also capable of saving lives.

I’m talking about the contribution you can make to early interventions, where support can be placed at the top of the cliff - not the bottom.

So much of my work is based at the bottom of that cliff - supporting long-term beneficiaries who’ve never been asked what they’re capable of, supporting sexual abuse survivors, and the victims of child abuse.

Too often, children are battered, violated and killed by those who should love and protect them.

The thing is - we often know who these children are.

We know their families, and agencies like CYF and Police have often already been involved.

CYF carried out a piece of work in 2008, looking at the children known to child protection, and how many of them ended up in the Youth Justice system.

This work resulted in the ‘6s-to-9s model’, which calculated the risk factor for children aged 6 to 9 entering the youth justice system 8 to 10 years later.

This is especially crucial considering almost 60% of people who go through the youth justice system end up in prison.  

The cost to Corrections for each of them is around $1.5 million.

Again, I wanted to take this sort of work one step further.

How can we transform the snippets of information we have on vulnerable children into a clear picture that helps us identify those most at risk at the top of the cliff?

Yes, it’s important to do what we can to keep a young person from committing crime - but it’s far more important to do what we can to stop a child being abused or killed.

The most relevant information about a child early in their life is information about their siblings, parents and caregivers.

This can also be the hardest information for social workers to collate quickly and analyse thoroughly.

A joint piece of work between MSD and Auckland University in 2012 led to the development of the Predictive Risk Model.

We’re now exploring this to see how it can better improve the lives of vulnerable children. 

CYF receives around 154,000 notifications of concern about children a year. 

61,000 notifications require further action, and 22,000 findings of abuse are substantiated.

As I said - we often know who these families are.

Predictive Risk Modelling can assemble and summarise information about children quickly, so frontline workers can get on with better protecting those they work with.

Using the data we have, including previous CYF engagement and family history, we found it’s possible to pinpoint which children are most at risk before harm is done.

Once social workers are alerted to a risk level through the information gathered, they can look at the case and work out much quicker exactly what those risks are, and what they can do to help. 

We’re also developing the Vulnerable Kids Information System, or ViKi. 

ViKi will enable frontline professionals, like socials workers and teachers, to register any concerns about children using a web-based programme. 

This will mean wider information is available to people working with children, helping form a much more comprehensive picture of a child. 

Concerns around ethics and privacy are absolutely top of mind, which is why we set up the Expect Advisory Group on Information Security.

This is currently being led by former Governor-General Sir Anand Satyanand, and will oversee the development of the Risk Predictor Tool and ViKi.

These tools are being designed with the clear message that the data collected and analysed will only be used to contribute to the decision making process around interventions.

They are not intended to replace professional judgement and never will.

But they are tools which frontline professionals can use, which I believe will be far more effective than just throwing money at the problem of child abuse, crossing our fingers and hoping we’ll get better results. 

What I hope Risk Predictor Modelling will do is transform the data Government already holds and has access to, to make the picture clearer and the path of intervention more certain.

This way, we will be able to go exactly where we need to be - the right family, the right child, at the right time - and we will have a better understanding of exactly what they need.

I know many of you here use your skills and expertise in data analytics in the corporate sector - helping businesses increase profit and market share.

And there’s nothing wrong with that - in fact the Government is following your lead and finally catching up to what corporates have been doing for decades.

I’m also glad to see several Government agencies represented here - I hope you agree with me this is exciting stuff.

We have a golden opportunity in the social sector to use data analytics to transform the lives of vulnerable children, families and individuals.

I’m unafraid to say the challenges Government faces through this work are greater than those for businesses and the private sector.

The data we have is richer, but more complex and fragmented.

The problems facing vulnerable people are multi-faceted and overwhelming, and the work for those supporting them is immense.

The cost of failure is greater.

It is a person spending their entire life on benefit never getting the investment or support they needed.

It is the lives of children at risk of abuse and neglect.

While we are rightly constrained by concerns around privacy and ethics, we have the moral imperative, and the power to take action and make a difference.

Are you up to the challenge of working with us?