Government

Government

Applying analytics to ensure best practice resource optimisation and heightened societal return on investment.

DOC link to

THE CHALLENGE

On occasion, prisons have to operate at over capacity, with more prisoners than available beds. While the correlation between inmate numbers and prison officers is normally linear, Corrections had observed that this changed when a prison was full - with more staff time required for things like finding temporary accommodation and co-ordinating prison transfers. Although this could be managed using overtime, it was costly and not sustainable. Concerned that the appropriate staff funding was in place to manage occasional over capacity situations, Corrections tasked Datamine with creating a robust business case for Treasury that accurately estimated the extra funding required to cover projected increases in prisoner numbers.

THE SOLUTION

Datamine developed a data-driven approach to ensure a sound business case. The solution correlated payroll data, hours worked, inmate numbers, facility capacities and Ministry of Justice forecasts to predict future staff costs associated with an increase in prisoner numbers.

 

THE RESULT

The analysis revealed that staff costs increased from less than $380 per prisoner per week when occupancy was below 99% to over $420 per prisoner when occupancy rose to over 102%. When the prisons are nearly full, a 3% increase in the number of prisoners results in a 13% increase in staff costs. Quantifying these costs allowed a clear case to be put to Treasury.

To help Corrections continue to manage the increasing prisoner numbers, and provide an early warning of expected increases, Datamine also delivered an easy-to-use forecasting tool. Using this application Corrections now has a six-month forecast of expected prisoner numbers which assists in operational planning.

insurer link to

THE CHALLENGE

With overall responsibility for providing no-fault personal injury cover, a government-owned insurer wanted to develop a more customer-centric approach to the way it engaged with small businesses and asked Datamine to clearly establish two things:

  1. What was most important to small business clients in relation to the delivery of the insurer's services?
  2. How was the insurer performing in meeting those needs?

Being able to measure these variables and then identify distinct groups of customers with similar needs, the company hoped to gain actionable intelligence that would enable it to develop services that would increase overall customer satisfaction.

THE SOLUTION

By combining the insurer's existing small business customer data with BRC Research survey data relating to a sample of those customers, Datamine was able to develop a small business customer segmentation model for the company that answered both questions.

 

THE RESULT

Datamine analysis delivered the following rich information:

  • Primary and secondary client drivers – in terms of what aspects were most important to customer groups in their dealings with the company (by extrapolating the survey data across all customers).
  • Business customer demographics – including industry, number of employees, turnover, and company age.
  • Transactional satisfaction data – with regard to previous interactions and outcomes around dealings with the insurer.

touristcity link to

THE CHALLENGE

With the introduction of an international airport, a small tourist city had become a gateway to its region and local government leaders wanted to use this opportunity to create economic growth in the region – particularly in its retail sector. To do so it needed to understand the top-line differences between the retail sectors of itself and other tourist cities. Anecdotally, the Council believed it didn’t have the right ‘retail mix’ to service the new tourists, and by identifying both opportunities and threats, appropriate action could be taken to better target the region’s retail offering.

THE SOLUTION

Using Westpac Business Insight data, Datamine sized the market and spending habits of residents of each destination and analysed the current retail offering in all the requested tourist cities - highlighting the critical differences between them.

For example, Datamine identified that while mainstream clothing & footwear retailers dominated in the client city, there was a noticeable lack of specialist stores present – a key driver in the ‘out of town shopping trip’ - which saw 11% of the city’s residents regularly driving 60 kilometres for retail therapy in another town.

Datamine also noted that the top three restaurants in a similarly sized tourist town represented about the same share of ‘top 10 food destination sales’ as the three big fast food chains in in the client city, signalling an opportunity for additional food revenue if city improved its ‘tourist food destination’ offering.

THE RESULT

The District Council understood what it needed to do to increase spend in the city by locals and tourists alike, and began working towards attracting specific retailers to fill the gap in its retail offering and fuel economic growth in the region.