Data: Unleashing the potential
How are government agencies using data to improve regulatory outcomes?
How are government agencies using data to improve regulatory outcomes?
In the ever-evolving landscape of regulatory practices, the role of technology and data-driven decision-making cannot be overstated. A year ago, Objective Corporation embarked on a mission to understand how regulators across Australia and New Zealand were embracing various forms of regulatory technology, or "RegTech." The survey aimed to shed light on everything from foundational systems managing licensing and permitting workflows to the use of cutting-edge tools like drones and mobile apps, which had become a hot topic in the era of COVID-19 contact-tracing apps. The findings painted a picture of regulators just beginning to scratch the surface of what technology, particularly digital solutions, could offer to enhance their effectiveness.
Let’s delve into the key takeaways from the survey, explore the challenges regulators face in becoming data-driven and intelligence-led organisations, and present case studies that exemplify the power of data in regulatory practices.
Last year's survey revealed that while 95% of regulators considered data sharing relevant to their work, only 14% had the capability to do so effectively. This gap between recognition and implementation underscored the challenges in the path to becoming data-driven regulators.
Becoming Data-Driven is a Cultural Journey: One of the central themes that emerged was the importance of leadership in fostering a culture that values data-driven decision-making. Without strong leadership and a commitment to change, embracing data can be an uphill battle.
Data for Targeting Regulatory Efforts: Data was predominantly used for targeting regulatory efforts, such as identifying high-risk regulated entities. However, there is ample scope to use data for broader purposes, such as setting annual priorities, developing regulatory strategies, and informing policy advice.
Engaging and Supporting Frontline Staff: To make better use of data, it's critical to engage and support frontline staff. This includes providing the necessary tools, training, and incentives to ensure accurate data entry and effective data utilization.
Building Data Capability Incrementally: Rather than pursuing a "Big Bang" approach, the most effective strategy is to build data capability incrementally. This involves demonstrating the value of data through early projects and gradually investing in new tools and resources.
Collaboration Between Data Analysts and Intelligence Professionals: Combining the strengths of data analysts and intelligence professionals can lead to more comprehensive and effective data utilization. Intelligence professionals excel in finding novel data sources, while data analysts are skilled at analysing and visualising data.
The Importance of Strong Data Governance: Establishing clear roles and responsibilities for data governance is crucial. Inconsistent data due to inaccurate data entry and system-related issues can hinder progress. Solid data governance ensures data quality and integrity.
Electoral Commissions Promoting Voter Enrolment
Case: Electoral commissions in both Australia and New Zealand utilised data sharing to encourage young people to enrol to vote.
Impact: Data sharing enabled these agencies to target and engage with specific demographics, promoting civic participation and voter enrolment.
Tax Agencies Identifying Incorrect Tax Payments
Case: Tax agencies harnessed data to identify individuals who may be paying incorrect amounts of tax.
Impact: This data-driven approach helped tax agencies uncover discrepancies, enhancing revenue collection and tax compliance.
Veterans Affairs Administration Cross-Checking Pilot Benefits
Case: The Veterans Affairs Administration in the US cross-checked federal government databases to identify pilots receiving benefits for mental health disorders and other conditions that should have been disclosed to aviation regulators.
Impact: This case exemplifies the importance of data matching in ensuring public safety, revealing instances where pilots were receiving benefits while potentially posing risks as licensed professionals.
Becoming a data-driven and intelligence-led regulator is an ongoing journey, one that requires leadership, cultural change, and incremental improvements in data capabilities. While challenges persist, the benefits of data-driven decision-making, including targeted regulatory efforts, improved complaint triaging, and enhanced enforcement, are worth the effort.
The case studies mentioned above demonstrate the tangible impact of data in regulatory practices, from promoting civic participation to ensuring public safety. The journey towards embracing data is far from over, but with the right strategies and a commitment to change, regulators can unlock the full potential of data to enhance their effectiveness and better serve their communities.
If you want to dive deeper into the survey results, case studies, and gain a comprehensive understanding of the challenges and opportunities in regulatory data utilisation, we encourage you to download the full report from the Objectives website. Your feedback is valuable in shaping the future of data-driven regulatory practices.
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