Rethinking data: driving innovation in the public sector
Almost two years on, COVID-19 continues to cause widespread disruption to our healthcare system, our economy and our way of life.
Many organisations are still working to put in place effective data strategies and utilise data to its fullest to optimise their businesses. It is no different in the public sector. The pandemic has fuelled innovation as many public sector organisations have been forced to accelerate their data investments to support remote working and provide accessible digitised services for the community.
Increasingly the public sector is realising the benefits of data-driven initiatives and is looking post-pandemic to invest in more data-driven initiatives. In fact a recent study by Qlik and Omdia in APAC showed that 72% of CDOs in Australia regretted not having invested more in data-driven initiatives before the pandemic hit. Meanwhile, just over half of public sector organisations in Australia now routinely rely on data for mission-critical decisions.
So how can we spark innovation in the public sector and drive better policymaking through data? Technology is only part of the solution. The way forward involves not only reassessing current technology investment to meet current and emerging requirements but also driving a data-literate and data-centric culture as a priority.
The COVID period has provided some important lessons about the strategic value of data in digital government. However, these important lessons could easily be lost without a systematic effort to incorporate these lessons into business-as-usual corporate management practices and agency-wide strategic plans.
Build a case around the value of data
As with the c-suite in the private sector, convincing public sector leaders on the value of data continues to be a challenge. Resourcing and limited budget remain key barriers to further data investments.
However, investments in analytics and data can help the public sector address both its immediate and long-term challenges while maximising resources. Research from McKinsey estimates that globally, governments stand to capture US$1 trillion by using big data analytics to plug revenue leaks. A further study showed that efforts to apply data analytics to eliminating waste, fraud and government abuse could offer returns as high as 10 to 15 times their cost. There are significant non-financial benefits as well, from improving trust and efficiency to reducing waste.
The Tasmanian Health Service (THS) is an example of how early investments in real-time data can vastly improve organisational visibility and empower rapid, effective public emergency response. The THS kickstarted its modern analytics journey in 2016 and worked over the years to create a central data analysis system with Qlik Sense to improve operational efficiency.
When COVID-19 hit in early 2020, the THS was already prepared to hit the ground running. Nine staff spent just four days creating a dedicated COVID-19 dashboard that enabled healthcare workers across regions to identify COVID-19 cases, conduct rapid contact tracing and lock down infections. Today, departments across the THS proactively use real-time dashboards to improve data veracity and automate tasks, improving healthcare effectiveness from the emergency room to the operating theatre.
Sharing such examples of analytics success will help garner leadership support and resources to invest in analytics transformation. While this enables CDOs to get started on sparking innovation, CDOs must follow through by actively engaging leaders and staff by closely reporting progress, celebrating successes and sharing learning opportunities.
Conduct an assessment of your technology investment
To achieve similar success levels as the THS, public sector agencies must work together with their CDOs to assess their current technological capabilities, identify their most pressing challenges and decide on the outcomes they wish to achieve.
Addressing these priorities requires honest self-assessment. Does your organisation have up-to-date data infrastructure to support proper data integration and analysis? Are there enough data touchpoints at the front line? What kinds of inter-agency data sharing efforts are in place? Do your staff have appropriate tools that support data integration, analysis and visualisation?
To get a more comprehensive, accurate assessment, public sector organisations must consult with data experts familiar with the entire analytics journey.
Develop a data-literate workforce and data-centric culture as priority
Technology as mentioned is only one part of the solution. Public sector organisations must invest in developing a data-literate workforce and creating a data-driven culture. According to the Qlik and Omdia research, Australian CDOs want a strong corporate culture of using data to support decisions (80%) and a more data-literate workforce (68%).
A way to go about it is by pairing analytics experts with public sector domain experts throughout the organisation. This promotes a culture of shared learning where groups can borrow on each other’s expertise to do more with data. As the analytics experts empower domain experts with the knowledge to handle data better, they will also find themselves learning more about the realities on the ground and the public sector’s operational needs.
However, public sector leaders must also enact change from the top by establishing a data governance framework that clearly defines roles, responsibilities and processes for ensuring effective use, ownership and data accountability across the organisation. While data governance ensures compliance, it also promotes efficient use of clean and accurate data across different public sector agencies, saving time and costs.
But to continue to drive innovation within the public sector, leaders must work together with CDOs to continually assess their organisation’s technology strategies while ensuring the workforce is well equipped to use data-informed decision-making to create long-lasting benefits to the citizens. As examples such as the THS show, there is a strong case for data investment when the right tools and people come together with a common goal.
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