Queensland’s Office of State Revenue Software Purchases and Digital Transformation Initiatives

Discover the latest software purchases and digital transformation initiatives being undertaken by Queensland’s Office of State Revenue and its business and technology executives. Each quarter our research team identifies on-prem and cloud applications that are being used by the 954 Queensland’s Office of State Revenue 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’s Office of State Revenue has purchased the following applications: SAP Customer Retention, powered by Leonardo ML for Machine Learning and Data Science Platform in 2018, SAP Leonardo IoT for IoT Platform 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’s Office of State Revenue is running and its propensity to invest more and deepen its relationship with SAP 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’s Office of State Revenue revenues, which have grown to $270.0 millions in 2019, 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’s Office of State Revenue 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.