Brisbane, 4101, QLD,
Australia
Queensland Treasury Technographics
Discover the latest software purchases and digital transformation initiatives being undertaken by Queensland Treasury and its business and technology executives. Each quarter our research team identifies on-prem and cloud applications that are being used by the 1541 Queensland Treasury employees from the public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources.
During our research, we have identified that Queensland Treasury has purchased the following applications: Aurion HR Employee Self Service for Employee Self Service in 2021, SAP Leonardo IoT for IoT Platform in 2018, SAP Customer Retention, powered by Leonardo ML for ML and Data Science Platforms in 2018 and the related IT decision-makers and key stakeholders.
Our database provides customer insight and contextual information on which enterprise applications and software systems Queensland Treasury is running and its propensity to invest more and deepen its relationship with Aurion , SAP , ELMO Software or identify new suppliers as part of their overall Digital and IT transformation projects to stay competitive, fend off threats from disruptive forces, or comply with internal mandates to improve overall enterprise efficiency.
We have been analyzing Queensland Treasury revenues, which have grown to $459.0 million in 2024, plus its IT budget and roadmap, cloud software purchases, aggregating massive amounts of data points that form the basis of our forecast assumptions for Queensland Treasury intention to invest in emerging technologies such as AI, Machine Learning, IoT, Blockchain, Autonomous Database or in cloud-based ERP, HCM, CRM, EPM, Procurement or Treasury applications.
About Customer
Queensland Treasury is at the heart of the Queensland Government, driving and facilitating better financial and economic outcomes for Queensland. We work to improve the quality of life for Queenslanders by growing and strengthening the economy, creating jobs and improving services.
Scope and Challenges
“We don’t want a system where the machine is making decisions. But we do want the machine to offer up next best action recommendations to our staff, that they have the option to follow – or not – based on their experience and knowledge of how the legislation should be applied… We’d also like a system that can ingest big data and take action within certain parameters. Natural disaster, the machine might be able to find out which customers are impacted and replace debt collection notices with proactive letters giving additional time to pay”.-said Liz Goli, Commissioner of Queensland’s Office of State Revenue (OSR).
Outcome and Implications
Within the transformation, OSR is pursuing a tax insights project, initially as a proof-of-concept but now as a full production deployment. The application built on SAP Leonardo machine learning will be progressively rolled out across OSR to all tax lines, commencing July 2018. A more responsive and tailored approach to individual taxpayers will lead to a more timely collection of revenue and reduction in debt across all tax lines, and additional revenue to fund essential services for Queenslanders. Machine learning application had been designed to propose the next best approach, payment suggestion, or debt management procedure to best support.
HCM
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
Insight Source |
|---|---|---|---|---|---|---|---|---|---|
| Aurion | Legacy | Aurion HR Employee Self Service | Employee Self Service | HCM | n/a | 2021 | 2021 | In 2021, Queensland Treasury implemented Aurion HR Employee Self Service to centralize employee access to HR and payroll functions. Aurion HR Employee Self Service serves as the department's Employee Self Service entry point and is positioned within the HRIS landscape alongside Aurion Timekeeper and ELMO. Configuration focused on core self service capabilities such as employee profile management, leave and absence requests, timesheet submission and approval, and support for recruitment administration including vacancy advertising and appointment workflows. The implementation also incorporated establishment management and Job Evaluation Management System inputs, aligning digital records with the department's role descriptions and workforce planning processes. Processing touchpoints were configured to support payroll processing activities managed by the HR branch. Integrations were established with Aurion Timekeeper for time and attendance synchronization and with ELMO for learning and performance management, reflecting the HR systems inventory that lists Aurion/ESS/Timekeeper and ELMO. The deployment also referenced OpenText Content Manager as the corporate Electronic Documents and Records Management System to maintain document retention and records linkages from employee files. Operational coverage included the Human Resource branch and payroll functions within Queensland Treasury. Governance for the rollout emphasized updated HR workflows for recruitment and establishment management, HR training courses and use of the online learning platform, and alignment with internal audit and workforce reporting processes provided by the Corporate Administration Agency. The rollout combined system configuration and process changes to support recruitment and selection workflows, workforce planning and reporting, and payroll interfacing. Aurion HR Employee Self Service therefore reinforced core HR operational workflows while integrating with the department's existing HRIS components. | |
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Learning and Development | HCM |
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2020 | 2020 |
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Learning and Development | HCM |
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2021 | 2021 |
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Payroll | HCM |
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2021 | 2021 |
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Performance and Goal Management | HCM |
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2020 | 2020 |
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Time and Attendance | HCM |
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2021 | 2021 |
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Internet of Things
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
Insight Source |
|---|---|---|---|---|---|---|---|---|---|
| SAP | Legacy | SAP Leonardo IoT | IoT Platform | Internet of Things | n/a | 2018 | 2018 |
AI Development
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
Insight Source |
|---|---|---|---|---|---|---|---|---|---|
| SAP | Legacy | SAP Customer Retention, powered by Leonardo ML | ML and Data Science Platforms | AI Development | n/a | 2018 | 2018 | In 2018, Queensland Treasury implemented SAP Customer Retention, powered by Leonardo ML. The initiative is categorized as ML and Data Science Platforms and leveraged SAP Leonardo machine learning capabilities alongside SAP HANA PAL to support analytics for taxpayer services. OSR partnered with SAP to develop a proof of concept focused on transforming taxpayer services, with explicit operational scope in revenue collection and debt management. The program concentrated on predictive modeling and retention analytics to inform revenue collection strategies and case prioritization within Queensland Treasury operations. Architecturally the proof of concept combined cloud native SAP Leonardo model development and orchestration with in-database analytics using SAP HANA PAL for scoring and analytic processing. Models and scoring outputs were positioned to feed operational workflows for revenue collection and debt management rather than standalone reporting, aligning machine learning outputs to caseworker decision support and prioritization. Governance for the POC emphasized iterative model validation with OSR stakeholders and staged operationalization, including testing data science outputs against existing taxpayer service processes. The engagement remained framed as a proof of concept between OSR and SAP with a focus on embedding ML driven insights into revenue collection and debt management workflows. |
CyberSecurity
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
Insight Source |
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Secure Web Gateways (SWG) | CyberSecurity |
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2021 | 2021 |
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