Ambulance Victoria (AV) is moving ahead with a plan to utilise predictive analytics in the field, following on from claims of its ability to revolutionise real-time decision-making. However, wider uptake among other emergency services agencies across Australia has been mixed.
In a Request for Tender (RFT) AV has called for suppliers of real-time predictive analytics to create a platform which enables real-time decision support for the organisation. The specification document notes the need to operate through a “single pane of glass” from the end-user’s perspective, stipulating that the controls and information be easily accessible by a single interface or dashboard, through a smart device such as a phone or tablet.
This will allow ambulances to make decisions on the spot, hopefully utilising data such as patient records, traffic information, hospital services and capacity.
‘Real-time’ predictive analytics refers to the dynamic nature of the data-sets used, and in AV’s proposed platform this data must be readily actioned within very short timeframes of minutes or seconds to provide information on the best course of action after a triage of an emergency situation.
Invoking elements of a co-design process to overcome potential pitfalls from relying on a single supplier the RFT is looking for a Primary Platform Supplier to lead the implementation of the platform, as well as the creation of a general panel with multiple suppliers to aid in developing new functionalities for the overall platform. This is in-line with AV’s aim of establishing a system based on “flexibility, scalability and modular approach”.
Suppliers are required to form “a strategic partnership with Microsoft or a Microsoft Gold Partner in the Data and Analytics Domain”.
AV is not the first emergency services agency in Australia to seriously consider real-time predictive analytics to support rapid decision-making in the field. Then CIO of Fire + Rescue NSW (FRNSW), Richard Host, championed ‘Project Miinder’ in an interview with Intermedium in 2014, which was to enable allocation of resources through a similar process.
However, this approach was discontinued as the current communications and operations infrastructure was “already highly effective” in the allocation of resources on the ground in emergency situations, according to a FRNSW spokesperson.
Although the feasibility and usefulness of predictive analytics for rapid decision-making processes may vary area between agencies and jurisdictions, it does have a broad range of applications within emergency services in other areas.
In 2018 the NSW Government established the Fire Safety and External Wall Cladding Taskforce in the wake of the Grenfell Tower fire in London to investigate whether similar cladding could put buildings in NSW at risk.
The Taskforce comprised of FRNSW, the Data Analytics Centre, DFSI and a number of other agencies which collaborated, combining pre-existing data-sets to identify 3,000 at-risk buildings. Inspections were then able to be carried out and mitigation strategies and contingency plans could be discussed with tenants.
Another use of predictive analytics useful to FRNSW and other agencies is through the analysis of retiring fleets and other equipment which can provide insight into maintenance optimisation and renewal cycles.
Predictive analytics in other areas
Police in NSW, Victoria and overseas have also expressed interest in predictive policing. However, approaches so far have led to accusations of profiling in the UK, throwing up potential ethical pitfalls for both suppliers and agencies to consider.
A successful example of real-time predictive analytics has emerged through Transport for NSW’s Public Transport Information and Priority System (PTIPS), as part of the Intelligent Congestion Management Program contract awarded to Opal operator Cubic in 2018.
PTIPS links GPS and Opal data from the Sydney bus network with timetable information and the traffic light network, to ensure buses running behind schedule are given priority green lights on their runs.
The earmarking of $116.7 million over four years in the federal government’s Mid-Year Economic and Fiscal Outlook for the Department of Agriculture and Water Resources pledges to build a “national predictive analytics and intelligence capability” in biosecurity and highlights this initiative as a leading future opportunity in the application of predictive analytics.