The past eighteen months has been a particularly turbulent period for government policy, particularly given the challenges of the COVID response.
Public sector staff needed to crank up the speed of policy development and delivery, while at the same time dealing with increased complexity and a workforce transitioning to working from home. However, during this same period we have also witnessed some important policy failures. Both need to be faced squarely, and lessons learned for the future.
Data has become a game-changer for both the best and the worst of policy practices.
The community has now become accustomed to a steady diet of graphs, charts, and interactive images. This is not just public relations window dressing, but instead it is part of a fundamental shift in community attitudes about the way citizens want to interact with government.
Data points are now expected at ministerial briefings, otherwise ministers are not seen to be across their portfolio.
The media has been quick to transition to these new rules of engagement. Celebrity data analysts now make calls on election outcomes and guide the community through the complexity of COVID statistics. Government agencies must also compete for credibility against a barrage of “alternative facts” on social media, and a stream of opinion from media broadcasters.
The data genie cannot be put back in the bottle.
Trust the data, but not so sure about government.
Long running international research, such as the global Edelman survey, clearly shows that trust in public institutions continues on a low trajectory, and these numbers are particularly low for the public sector. While Australia’s trust rating lifted last year during the COVID lockdowns, this improvement was still off a low base. The underlying level of trust continues to be alarmingly low.
This finding may sit awkwardly for a Public Service whose raison d’être is to serve to the public, but the reality must be dealt with.
The Federal and State COVID responses provide some very good examples of successful strategies for dealing with a sceptical public. They demonstrate why corporate risk management strategies need to be carefully reassessed to deal with trust-related risks.
At the beginning of the pandemic, the Federal Government was quick to realise community trust could not be maintained if there were inconsistent messages on health policy and data. The Prime Minister moved quickly to strengthen the role of the policy/data advisory groups AHPPC and later ATAGI, and coordinated this information through National Cabinet. The Australian Department of Health also worked on delivering an up-to-date set of COVID data infographics for public and media consumption.
The State Government-run COVID-app projects have also received widespread community support. The relative success of these apps is due to their simplicity of design and clarity of the value proposition: The IT system was designed so that the citizen directly controls how the app is used and what data it collects. In turn, the State Governments undertook to only use the data for COVID tracing. It is noteworthy that the Queensland Premier was quick to quash the use of COVID tracing data for another purpose, even though Queensland Police had accessed COVID data using a legal search warrant. The Premier clearly understood the fragility of community trust. Social licence only stretches so far, even during a pandemic.
Don’t test the limits of community trust.
Community trust does have its limits, and governments are judged harshly when the limits of community trust have been crossed. These limits were most clearly on display during the unravelling of the government’s “Robodebt” initiative. This initiative was the subject of widespread community concern about the lack of fairness and procedural integrity. It was ultimately found to be unlawful through a series of legal cases. However, the implications of this failure go much deeper, and there are some important lessons for future data-related policy initiatives.
- Don’t blame the technology: In some of the media commentary, data analytics technology was blamed as the source of the problem. However, there are many examples in Australia and overseas where analytics and data matching software have been successfully used to identify potential incorrect claims and payments. Best practice policy approaches, tend to rely heavily on using data analytics to shape community behaviour (such as behavioural economics), rather than going straight to enforcement action.
- Data should not be weaponised: Government holds a privileged position in society because it can legally demand information from its citizens. It therefore holds a power imbalance relative to its citizens, as government is a data-rich custodian of information. There is a well-established convention in government called “model litigant”, which states government should not leverage its power imbalance over citizens when taking enforcement action. This means the government’s use of data should not only be driven by the legal right to undertake a particular action, but also by the procedural fairness of the way this action is undertaken.
Are you working across areas of data analysis, capability and governance within the public sector? Omdia in conjunction with SAS are hosting an Executive Panel and Breakfast event in Canberra on September 9 to delve further into the emerging opportunities that are available to government via a nuanced approach to data. Visit the event page to learn more and register.
Contemporary governments need to do more with data analytics.
Despite the high-profile fallout coming from Robodebt, properly managed data analytics is a policy area that needs greater attention from government.
When properly presented, credible data can add value by taking the emotion out of complex policy debates. The community has shown itself to be up to the challenge of working through complex systemic issues, particularly when it relates to issues the community cares about. During the recent NDIS funding debate, for example, the media was again quick to step in to fill the gap with its own analysis of the numbers.
Governments need to understand their citizens more clearly, and data analytics is a practical way to do it.
There is no shortage of government data to choose from, but legal accessibility to the data has become a bureaucratic mess. The government’s Data Availability and Transparency Bill hopes to solve the problem but a lot more work is needed to allay community concerns. The stakes are high. Countries in our region, such as New Zealand, have already demonstrated the significant benefits from drawing on a wide variety of data sources for policy development.
Australia does not have the luxury of putting this problem back into the too-hard basket. There are already several good examples where policy has successfully benefited from a comprehensive data-driven strategy.
The Pharmaceutical Benefits Scheme leads the world in providing cost-effective subsidised medicines to the community. This scheme uses complex modelling to look at the cost-benefit of new drugs and then uses this information to negotiate better prices through a national deal with international drug companies.
Rightsizing data governance.
Legislation can only provide part of the solution, and much of the heavy lifting needs to be done through governance and leadership within each government agency. Much work has already been done. Executive data champions and a renewed focus on the development of corporate data strategies are now producing promising results.
It is noteworthy, however, that the US Government has gone much further by codifying better practice through legislation – Foundations for Evidence-Based Policymaking Act (Evidence Act). The Evidence Act emerged from recommendations of the U.S. Commission on Evidence-Based Policymaking, and this represents a significant shift in bolstering the importance of underlying data research. The stated objective of the Act is that it “requires agency data to be accessible and requires agencies to plan to develop statistical evidence to support policymaking”.
Omdia research indicates government agencies have no shortage of data tools within each agency, but many of these may not be up to the task. Policy managers could be better served by more contemporary tools, particularly those that have industry solutions specifically aimed at the government sector. The IT industry has come a long way in supporting data analytics for policy development and delivery. Industry spokesman, Timothy Gunnell, is Head of Federal Government at international analytics firm SAS in Australia. He provides a valuable industry perspective on how much the data analytics industry has evolved:
“The speed at which the public sector needs to go from data to insights to decisions has accelerated rapidly over the last 18 months. Governments are now expected to have data-driven insights, instantly. The tools to achieve this are ready. Now is the time to take action.”