Improving the ease and speed of accessing benefits is key to government efforts to extend social and economic safety nets to what the International Social Security Association (ISSA) refers to as the 鈥溾��. Self-employed and gig workers, as well as rural, migrant, and domestic workers are typically time-poor, not already engaged in social protection systems, and are often not included in targeted outreach programs. This makes them vulnerable to economic shocks and cost-of-living increases that can tip them into poverty and homelessness.

As such, many government agencies and not-for-profit organisations are looking at ways to make social services more accessible and responsive by reducing the 鈥渉assle costs鈥� associated with claiming benefits.

How AI can help

Governments around the world have been realising significant efficiency gains through applying artificial intelligence (AI) in the back-office to improve workforce productivity. Encouragingly, there are also recent examples of AI being leveraged in the front-office to improve the efficiency and effectiveness of citizen engagement.

1. Quicker time to payment with AI-supported assessment processes

At , a combination of Machine Learning (ML) and Generative AI (GenAI) support staff to efficiently process applications for more than 鈧�3.5 billion in financial aid.

麻豆原创 Machine Learning is used to link citizen application data to supporting documentary evidence, enabling case workers to expedite processing for the bulk of applications and to focus their attention on those most likely to be non-compliant. Across two programs, Hamburg reports that nearly 180,000 benefit applications have been processed, with more than 10 million pages of supporting documents automatically evaluated and classified by AI.

麻豆原创 Generative AI Hub has also been introduced to summarise inbound applications and to generate draft outbound correspondence, further reducing time to payment for customers while minimising the burden of repetitive manual work for staff.

2. Improved customer service with AI-powered workflow automation

Similarly, uses 麻豆原创 AI to automate workflows and to recommend potential benefits based on customer circumstance data. AI has contributed to a 20% increase in user productivity, which amounts to a substantial efficiency gain when applied to an agency of 9,000 public employees managing 鈧�1.8 billion in monthly payments. These efficiencies flow through to citizens, as described by the Deputy Director General of Benefits and Subsidies, who reports their AI-enabled system 鈥溾�as empowered me to shift focus from administrative tasks to truly enhancing citizen service, allowing for quicker responses and more meaningful interactions.鈥�

3. Faster query resolution with AI-enabled chatbots

At , an 麻豆原创 AI chatbot responds to 50% of citizen inquiries with no human intervention, resulting in 77% being answered and closed within the same day. While social services inquiries would typically be more complex, there鈥檚 certainly potential for AI to categorise and prioritise inbound communications and to route them to the appropriate channel or group. This is the case for more than 83% of the inquiries being received by the Office every day, which embassy staff say 鈥溾�eans efficient communication, satisfied customers and a gain in personnel resources for other tasks.鈥�

Reducing the barriers to adoption with embedded AI

To date, the types of use cases described above have been delivered as custom AI solutions, limiting uptake to agencies that are sufficiently resourced to assemble AI systems from Large Language Models (LLMs) and other necessary components. This is further exacerbated by the additional work needed to protect customer data, prevent bias, and ensure the reliability of AI recommendations.

Thankfully these barriers to adoption are being reduced as AI capabilities become embedded into enterprise software, enabling agencies to adopt out-of-the-box solutions. For example, something as simple as supporting staff to retrieve information using AI-enabled natural language search could reduce the time customers spend waiting on hold while their case worker struggles to locate their file.

Revolutionising social services with agentic AI

The advent of agentic AI could be a tipping point for social services AI use. By virtue of their ability to take multiple paths and iterative steps towards achieving an outcome, AI agents are particularly suited to the type of complex case processing inherent in social services. We can imagine a future where benefit applications are picked up and processed by a team of specialised AI agents that can autonomously validate compliance, determine eligibility and entitlement, identify potentially fraudulent claims, and present reasoned recommendations to human case workers for approval.

Such a future could be just around the corner. predicts that, 鈥渂y 2028, 33% of enterprise software applications will include agentic AI, enabling 15% of day-to-day work decisions to be made autonomously.鈥� Similarly, it notes, 鈥渂y 2029, agentic AI will autonomously resolve 80% of common customer service issues without human intervention, leading to a 30% reduction in operational costs鈥�.

In summary, AI is already enabling early adopters like Hamburg鈥檚 Ministry of Finance to improve the efficiency of application processing for social benefits. AI adoption in social services is now set to scale as AI capabilities are embedded into enterprise software, and this could lay the groundwork for a big leap forward with agentic AI. AI will be increasingly capable of reducing the 鈥渉assle costs鈥� associated with claiming benefits, helping to ensure that social and economic supports reach the people that need it, when they need it.

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When Tauranga City Council members at the helm of this fastest growing city in New Zealand decided to modernize a 20-year old ERP system, they were fully aware of the challenges they faced in meeting the evolving needs of a burgeoning community. With a population of about 155,000 people and counting, Tauranga is the fifth largest city in the country.

鈥淭auranga is growing quickly and we need to think differently about how and where we live, and how we manage the existing and increased housing and infrastructure requirements of our growing city,鈥� said Scott Oehm, head of digital delivery at Tauranga City Council. 鈥淓qually important is the need to increase community engagement, getting the community more involved in the decisions that affect their daily lives.鈥�

Modular strategy makes digital journey easier

At the heart of Tauranga鈥檚 ambitious digital journey is , which has fostered greater collaboration, transparency, data reliability, and change management across administrative operations. As the local authority responsible for the administration of property rates 鈭� otherwise known as taxes 鈭� as well as charges for water use, along with managing recreational spaces, plus other license and regulations, the Council opted for a phased-in system update, beginning with .

鈥淗aving a modular strategy to upgrade our legacy ERP systems is making the transformation much more manageable,鈥� said Oehm. 鈥淲ith this initial roll-out across finance, people in each business unit and the larger community we serve are receiving the benefits of greater collaboration and transparency.鈥�

Measurable results prove value of digitalisation

Already the impact of the new system is palpable. People on the financial team have become more strategic working alongside other business units to improve budgeting, offer valuable financial insights, and increase internal collaboration.

Oehm said that with greater visibility into more reliable data from automated processes, the council can better meet community expectations for transparency and accountability from local authorities. What鈥檚 more, the financial team has significantly sped up monthly and year-end processes and project reporting. Automation reduced manual processing tasks for financial analysts by 25 percent, and time spent on capital project reporting by 30 percent.

Going digital also brought more rigor to processes like . Now people are required to obtain up front approval for any expenditures, simplifying procurement while meeting financial standards.

鈥淭his project has been very much business-driven, allowing managers and administrators to focus on and drive the results they want to achieve,鈥� said Oehm. 鈥淏ecause the system touches nearly all business groups within the organization, everyone had some input. Working together, the team has realized huge efficiency gains.鈥�

Digital sparks cross-team collaboration for continuous learning

In an unexpected bonus, the 鈥渃hampions鈥�, subject matter experts, and user groups originally created as part of the 麻豆原创 S/4HANA finance project have morphed into de facto change management teams. Some still meet regularly, not necessarily to talk about 麻豆原创 solutions, but how they can help each other create further efficiencies.

鈥淚n sharing what’s worked and what hasn’t worked, people are continuously learning from each other,鈥� said Oehm. 鈥淭hese aren鈥檛 just managers. We鈥檝e empowered administrative staff to work together to find the best outcomes for the organization. People can problem-solve themselves, and also be a source of ideas for IT to make improvements over time.鈥�

Connected ERP platform is strong foundation for growth

Oehm saw 麻豆原创 S/4HANA as the foundation supporting the city鈥檚 growth beyond the finance team to include property ratings and community relations. He said that property ratings constituted the bulk of the city鈥檚 revenues, and community relations were integral to multi-cultural relationship building.

鈥淲e now have an iterative system to track solid financials and ensure good processes without overwhelming our people,鈥� he said. 鈥淲e can move at our own pace, evolving the system as city and organisational needs grow, supporting quality of life for an influx of people community-wide.鈥�

Explore more real-life success stories from 麻豆原创 ANZ customers that are digitally transforming their business.

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The taskforce also urged governments to more favourably evaluate proposals or tender bids from companies that adopt cyber security and other risk standards for telecommunications and the internet of things (IoT). Again, they know that without security being front of mind throughout the supply chain, vulnerabilities can creep in.

The taskforce鈥檚 recommendations for federal, state and local government agencies follows in the wake of the government moving to expand the label of 鈥渃ritical infrastructure鈥� and create new security obligations and mandatory reporting for various public and private organisations via the draft legislation on Protecting Critical Infrastructure and Systems of National Significance.

These organisations could face steep penalties if they 诲辞苍鈥檛 answer the call to become deeper partners with Australia鈥檚 government in all aspects of security, particularly cyber.

The government is clearly taking a more holistic approach to cyber security 鈥� and so are enterprises. But this gets tricky once you factor in cloud solutions (Public and Private), whose agility and scalability are increasingly necessary for organisations to capitalise on the value of rich data, streamline distributed operations, realise cost efficiencies and make better use of contemporary and emerging tech.

However, platforms like 麻豆原创 HANA have evolved over a decade to help reconcile some of these tensions. Let鈥檚 take a look at how.

Can cloud solutions complicate security?

Regardless of architecture, security teams have to think carefully about who has access to data and how they鈥檙e accessing it.

Most recently, with on-premise architecture, it was a little more like a traditional building with an entrance and an exit. It鈥檚 a lot simpler to control security when you鈥檙e managing limited entry points. While many or even most cloud providers have robust security measures in place, cloud solutions do come with more entry points.

However, the security of those entry points differs based on public versus private cloud, as well as a wide variety of factors. For instance, within public cloud, there鈥檚 simply a greater number of side doors that require the same level of security. With private cloud, you control who has a door and what you let in and out.

That doesn鈥檛 mean organisations should sacrifice the benefits of all public cloud solutions 鈥� in fact, that might do more harm than good. It just means that security considerations need to govern any decision to bring new cloud extensions or providers into your environment. But ensuring scalable, enterprise-wide solutions is where things can get trickier.

Solutions that marry security with flexibility

In many organisations, elements of information are taken out of core systems and put into other data lakes, repositories or spreadsheets. The same piece of information is not only repeated in multiple areas but also with varying degrees of security applied to each of those different locations. If the weakest link determines the strength of the chain, then this approach means there are far more links whose strength is even harder to control or test.

Solutions like 麻豆原创 HANA, whose 10-year evolution has always been anchored in protecting information and assets, can go a long way to resolving this sort of issue. As an enterprise-scale in-memory database designed to allow end users to have a conversation with their data, HANA caters to large volumes of data and diverse use across a broad user community. The way this can be leveraged for better security is simple: the more information you have in a secure, controlled, unified container, the easier it is to protect that information with centralised security measures.

HANA also enables real-time anonymisation of data displayed in SQL views. This means companies can analyse even the most sensitive and regulated of records 鈥� such as those in healthcare 鈥� while still protecting data and supporting compliance with privacy standards like the European Union鈥檚 General Data Protection Regulation (GDPR).

Solutions like Data Warehouse Cloud are the next evolution in further resolving tensions between innovation and security. It allows organisations to extend secure data environments to secure cloud solutions, combining features of HANA with the rigorous security frameworks provided by a range of hyper-scalers. So, even in complex multi-cloud systems, you can achieve a consistent enterprise-wide data management framework and connectivity to other systems, whether that be public, private, on-premise systems or ubiquitous data sources like IoT devices.

Changing how we think about cyber security

Various types of platforms and architectures can help achieve robust, enterprise-wide security frameworks without sacrificing the benefits of cloud. But strengthening your security posture will also depend on shifting mindsets and educating stakeholders about cyber security and management of risk. There are plenty of business imperatives for this already, but 2021 will see additional regulatory control and incentives as the federal government takes a bigger role in cyber security.

Two big mindset shifts need to happen across all of industry and critical infrastructure sectors. First, when it comes to IT systems and reporting environments, we too often test them based on how we expect them to perform. Particularly from a security perspective, we need an extra level of testing that focuses on what malicious actors want to do and what they鈥檙e going to try. It鈥檚 important to test systems based on how we want them to be used but also how we 诲辞苍鈥檛 want them to be used.

Secondly, we often talk about how to collect data, store data and extend data. Cyber security compels us to ask: what are we going to do with this data? How will people use it? This is particularly crucial now that workers are less tethered to offices or corporate networks. It鈥檚 more important than ever to think about the potential usage of data and truly consider its security risk, ensuring that the device and solution set you鈥檙e using to present or extract that data is genuinely secure.

Major crises and national challenges in 2020 have reinforced the importance of collective success 鈥� when even one element struggles, so does the larger group. It鈥檚 an especially important principle in cyber security, where the tiniest vulnerability can open entire ecosystems to potential harm.

Yet the choice between security and innovation is a false one. Still, the topic is undeniably complex and demands ongoing discussion and thought.

So, what are you doing to protect your organisation while still pushing it forward?

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Embracing technology: the public sector of the future

To better serve its citizens, the public sector faces an existential need to become more agile, more mobile and more efficient. Some of the most hotly anticipated solutions include those enabled by artificial intelligence (AI). Ranging from predictive analytics to machine learning to intelligent robotic process automation, AI is one of the surest paths for extracting insights and value from growing volumes of data.

This has fuelled aspirations for everything from advanced smart cities to new approaches in population health management 鈥� often these solutions involve predictive analysis that could help agencies make better decisions, respond faster during crises and even pre-empt problems altogether. Some agencies are making use of AI applications already, like听, which used machine learning to predict tax non-compliance and netted the state an extra $27 million in revenue.

Government also has a unique role to play when it comes to AI 鈥� since all Australians are impacted in some form or other by government鈥痵ervices, governments must take the lead in their use of AI, whether through operations or service delivery.

Yet broader adoption remains low. A 2018 investigation by the 麻豆原创 Institute for Digital Government (The SIDG) found that, while 80 per cent of public sector organisations were working toward data transformation, less than 15 per cent had progressed beyond the prototype stage.

The SIDG teamed up with University of Queensland researchers to assess where the sector is at in 2020. The resulting white paper,听, identifies the biggest AI challenges in the public sector 鈥� and how leaders can overcome them to finally harness the true potential of AI solutions.

The resource challenge: building AI capability and securing human talent

AI relies on large datasets, high-quality data, the right platforms and 鈥� importantly 鈥� data science talent.

This is resource-intensive 鈥� an acute challenge in the public sector where data is often purposefully siloed, and fractured across complex, ageing legacy systems. These overlapping issues create a sort of chicken-egg dilemma, where leaders may struggle to secure funding and executive buy-in without proven value 鈥� but proving value depends on funding and executive buy-in.

The research did uncover examples of success, though. One agency was able to overcome data-sharing barriers by outsourcing its AI model development, which was then trained with citizens鈥� payment data instead of sensitive personal data. Another agency chose a commercial-off-the-shelf AI development platform to decrease maintenance burdens.

Misunderstandings about AI and inflated hopes also demand project-level governance to manage expectations and encourage ongoing commitment from executives.

The process challenge: pre-empting machine fallacies by keeping humans in the loop

Despite myths of robot overlords and job losses, algorithms only outperform humans in their ability to process huge datasets. They still lack the context-specific reasoning capabilities that we have, which means AI solutions can鈥檛 simply be plugged into existing workflows. Agencies will need to rethink processes to combine the strengths of machines and people.

This is complicated because of the barriers that often separate data scientists and subject matter experts, demanding redesign for entire workflows. The researchers found that agencies who were able to reconcile these issues were those who embedded data scientists in everyday operations and encouraged collaboration with subject matter experts.

Successful approaches include co-location and collaborative workshops but, interestingly, interview data also highlighted the importance of attracting data scientists with strong soft skills and good communication.

Organisations were keenly aware of the need for human oversight and the risks of deferring to automation. Many were already redesigning workflows to ensure AI was doing the heavy lifting and data-crunching, with human workers acting as the controllers of the AI and making final decisions.

The explainability challenge: minimising bias and enabling transparency

Advanced AI models have an 鈥渆xplainability problem鈥� 鈥� that is, the complexity of their logic and the sheer volume of data can make decision-making inscrutable to us.

This is a massive hurdle in the public sector, where public trust often depends on transparent rationale and straightforward accountability. It鈥檚 an even bigger challenge once we consider that algorithms have already demonstrated a serious risk of bias and error.

The researchers found that some agencies have been establishing strict oversight and procedural systems with these specific risks in mind. For instance, one agency excluded demographical data in favour of behavioural data to minimise bias in the model鈥檚 predictions.

Another created a more extensive end-user interface that visualised a customer journey and highlighted risky payment behaviours. This provided visibility into the factors affecting the overall risk estimate.

The culture challenge: reducing distrust among employees and citizens

Despite research indicating AI adoption rarely comes from a desire to reduce headcounts, job security fears abound. Additionally, the researchers found some human workers continuing to distrust AI鈥檚 decisions.

One solution is educating employees about the potential of AI-enabled tools 鈥� this can be an easier sell once employees witness the elimination of low-value tasks and admin burdens, freeing them to focus on more strategic and interesting work.

The public sector faces public resistance, too. Some agencies have the added challenge of a power imbalance, as citizens who rely on their services may not be able to switch providers like they would in the private sector.

While wider societal perceptions may evolve in a way that reduces distrust, there鈥檚 no simple solution to these challenges. Trust will depend on proven value and the effective management of unintended consequences 鈥� which will in turn depend on many of the solutions mentioned above.

The public sector faces unique challenges with AI solutions but also stands to gain some of the biggest rewards. And, promisingly, some agencies are already demonstrating how to address these issues.

Using an even deeper look into the public sector鈥檚 relationship with AI,听听provides a practical framework for developing the foundations necessary for effective AI development in government.

However, it鈥檚 an area that requires deeper exploration, which is why The SIDG will continue partnering with the University of Queensland to understand ongoing challenges.

To read more about 麻豆原创 Australia’s public sector offer, 听

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From COVID-19 testing to business stimulus programs, quarantine measures to training schemes, many citizens who may rarely be aware of the government鈥檚 role in our lives have become much more so over the months since the coronavirus pandemic hit Australia.

on the 麻豆原创 Public Sector Homepage.

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The first two articles in our 鈥淒ealing with Disruption鈥� series looked at how digital technologies might enable governments around the world to nudge citizens towards cooperation and coordinated action in containing COVID-19, and to address issues of hand washing, face touching, self-isolation, collective action, and crisis communication. In this article, the 麻豆原创 Institute for Digital Government (SIDG) will present a conceptual architecture for Digital Nudges and demonstrate how it could be applied to improve crisis communications relating to a second-wave outbreak of the Coronavirus.

Using digital nudges to support government responses to coronavirus

To demonstrate how our conceptual architecture might be applied, we will consider the scenario of a second-wave outbreak of the Coronavirus, such as was .

Figure 1: The first- and second-wave outbreaks of COVID-19 in Australia.

was identified on 25 January 2020. The number of new cases rapidly increased and peaked nine weeks later, with reported on 28 March. The Australian government responded very successfully with a for flattening the curve, and by mid-April there were a relatively low number of new cases being reported daily. Although the virus had not been eliminated, it appeared to have been suppressed sufficiently for lockdown restrictions to be eased across Australia. Unfortunately, were identified in Melbourne on 20 June, foreshadowing a second-wave and prompting a reinforcement of restrictions to contain the outbreak. Even so, Australia鈥檚 second-wave proved more difficult to contain than the first, peaking at reported on 5 August.

Due to the localized nature of the second-wave outbreak, stay-at-home restrictions were reintroduced only in metropolitan . Most notably, in North Melbourne and Flemington were immediately locked-down, with residents of 33 Alfred Street subsequently required to isolate for two weeks. While it was generally agreed that this was a necessary measure, the immediacy of the action combined with various communication challenges resulted in widespread confusion and concern among the 3,000 public housing tenants. captured the sentiment at the time:

• 鈥淲hen I came back home I did see hundreds of cops everywhere, so it was really intimidating.鈥�
• 鈥淚t鈥檚 been getting more and more intense, people are really panicking.鈥�
• 鈥淲e weren鈥檛 told any information, they just shut us down, didn鈥檛 let us leave our houses.鈥�
• 鈥淚 just feel like we鈥檙e being treated like criminals.鈥�
• 鈥淲e do not need 500 officers guarding the nine towers. We need nurses, we need counsellors, we need interpreters.鈥�

In what has been an unprecedented year, the hard lockdown of Melbourne鈥檚 public housing towers was an unprecedented action by the Australian government, law enforcement and public health services. To that point, Australian citizens had not experienced a lockdown under guard, except in cases of returned citizens undertaking hotel quarantine.

In special cases such as this, efficient and effective crisis communication is key 鈥� not only in ensuring compliance 鈥� but in promoting cooperation through credibility, empathy and respect. Behavioral Science can assist by influencing individual decisions towards the most positive outcome, and digital technologies can be used to scale and personalize traditional nudges to improve outcomes for mass cohorts.

Conceptual Architecture for digital nudges听

Figure 2: A conceptual architecture for digital nudges.

Nudging is a delicate process, with significant preparation required to avoid unintended consequences 鈥� especially when the stakes are as high as they are in the case of COVID-19. These stakes are raised even higher when the nudges are to be delivered by governments, at scale, using digital technologies. The is to optimize utility and mitigate risk using an iterative process of randomized controlled trials with rapid cycle evaluation. Whether the nudge is to be delivered as part of a trial, or to the population at large, an iteration of the nudging process typically spans:

• Design and contextualize: The nudge is designed to achieve the outcome of interest, based on an exploration of the available data. A key consideration is the situational and social context of the environment in which the nudge is to be deployed. In the case of crisis communications, nudges need to for citizens鈥� circumstances.
• Simulate and deploy: Randomized controlled trials can be used to simulate the likely response to a given nudge. A variation of this approach would involve using , to enable simulations to be run faster and safer than with human subjects. In the case of crisis communications, these simulations could be aligned to the accepted thresholds of a national or local containment strategy.
• Monitor and measure: Having deployed the nudge, social listening and devices can be employed to monitor the actual response. Although it may be difficult to measure the effectiveness of nudges as a behavioral modifier, a control group who does not receive the nudge may be used. In the case of crisis communications, we might also consider performance against 鈥渇ake news鈥� as a measure of effectiveness.
• Analyze and improve: Here we distinguish between measurement and analysis, specifically within the context of diagnostics 鈥� analyzing why a particular action has been taken or a particular outcome achieved. Based on this analysis, improvements can be made to the design of the nudge, and thus the iteration continues. In the case of crisis communications, certain visualizations (e.g. ) might be published to encourage community cooperation and coordinated action.

Digital nudges: Core capabilities

As described in our first article, predictive analytics, contextualization, and experience management are the core capabilities required to deliver digital nudges. Breaking down these capabilities will enable us to illustrate how they can support policymakers and service agencies, working with behavioral scientists and technology partners, to improve the effectiveness of traditional nudges.

• Predictive Analytics:
  • Behavioral Insights: The ability to detect patterns in citizen behavior, based on transactional and experiential data. For example, based on their prior responses to government requests, we can expect Citizen X to comply with stay-at-home orders.
  • Journey Visualization: The ability to visualize the citizen鈥檚 journey over time, including major life events, changes in circumstance, and their interactions with government. For example, based on the healthcare, social services and financial supports they have recently accessed, Citizen X is likely a vulnerable person who will need additional supports.
  • Simulation: The ability to simulate the likely responses to a digital nudge, including the ability to compare alternative approaches. For example, Nudge A will increase compliance with stay-at-home orders by 5%, with 80% confidence.
  • Next Best Action: The ability to recommend the optimal course of action, based on (autonomous) machine learning. For example, Nudge A will be most effective for Citizen X, while Nudge B will be most effective for Citizen Y.

• Contextualization:
  • Profiling: The ability to assemble a digital profile of a citizen, by combining data from multiple sources (as permitted by government regulations). For example, we know that Citizen X is at high risk, since they are over 80 years of age and live in high-density public housing.
  • Segmentation: The ability to create target groups, comprising citizens with similar profiles and needs. For example, Segment A comprises citizens of working age, who are likely concerned about the impact of stay-at-home orders on jobs.
  • Campaigns: The ability to proactively outreach to target groups with nudges tailored to their circumstances. For example, Nudge A will be delivered to citizens of working age, while Nudge B will be delivered to citizens over the age of 65.
  • Preferences: The ability to communicate with citizens via their preferred channel, and at their preferred time and place. For example, Citizen X usually responds promptly to SMS sent around lunchtime.

• Experience Management:
  • Social Listening: The ability to monitor social media to track changes in citizen sentiment over time. For example, citizens under lockdown are complaining that police presence is making them feel like criminals.
  • Surveys: The ability to solicit direct feedback from citizens. For example, Citizen X responded that they couldn鈥檛 understand the specifics of the stay-at-home order because English is their second language and no translation service was provided.
  • Measurement: The ability to measure the response to a digital nudge, based on transactional and experiential data. For example, Nudge A increased compliance with stay-at-home orders by 3%, compared with the control group who did not receive the nudge.
  • Diagnostic Analytics: The ability to uncover why certain nudges are, or aren鈥檛, working. For example, Nudge A was widely criticized as being disrespectful, resulting in a lower level of compliance than anticipated.

The underlying business platform supports the design, development, and management of our digital nudges.

• Analytics: The ability to analyze transactional and experiential data. Desirable features include the ability to:
  • surface actionable insights based on predictions;
  • dynamically drill-down into records of interest;
  • visualize citizen journeys over time; and
  • update data and visualizations in real-time.

• Intelligent Technologies: The ability to build, execute and manage machine learning applications. Desirable features include the ability to:
  • process big data holdings to build advanced machine learning models;
  • support profiling and segmentation of data in line with contextualization capabilities;
  • generate predictions and next best action recommendations; and
  • make improvements based on (autonomous) machine learning.

• Data Management: The ability to access and work with big data, in real-time. Desirable features include the ability to:
  • consolidate data from multiple sources;
  • work with transactional data in real-time, without impacting operational systems;
  • work with analytical data in-place, without the need for replication; and
  • ensure the security and privacy of citizen data.

• Application Development & Integration: The ability to develop and integrate business applications. Desirable features include the ability to:
  • accelerate the design and development of advanced machine learning applications;
  • run simulations in support of what-if analysis;
  • support an open ecosystem of development partners; and
  • integrate with external systems (e.g. geographic information systems).

In presenting this conceptual architecture, our intent has been to provide a framework that governments can use to deliver digital nudges. We believe this framework to be general-purpose, while acknowledging that certain scenarios will require additional capabilities. Our chosen use case of crisis communications serves as an illustrative example. Please note that, since this conceptual architecture is vendor-agnostic, the described capabilities could be sourced from any technology provider.

To read more about how digital technology can be used to improve public sector services, visit .

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As part of 麻豆原创鈥檚 commitment to helping business become more resilient and agile in today鈥檚 challenging environment, the recent Forum provided free industry-specific webinars that explored how governments, business and the community can work together to drive a faster economic recovery.

The Forum was a follow-up to the inaugural Adaptive Strategies event in May, where industry advisors and executives shared their perspectives on the strategies that Australian and New Zealand organisations were taking in response to some of the challenges we have faced this year – from the bushfires to the global pandemic. Regardless of industry, common themes that emerged were; digital preparedness, the importance of collaboration, business continuity, keeping customers and employees safe, safeguarding supply chains, mitigating risks, and building resilience for future events. Members of our team in the Digital Transformation Office at 麻豆原创 Australia & New Zealand participated in these sessions and here are some highlights.

Adaptive Strategies in a Changed World ACCELERATED

Small and medium enterprise (SME) will play a pivotal role in getting Australia back to work, which according to the 2019 Small Business Ombudsman Report accounts for 35% of our national GDP and 44% of Australia鈥檚 workforce. The SME sector, much like larger enterprises, has been hit by three primary challenges 鈥� cashflow management, employee engagement/availability, and supply chain disruption.

To further understand how innovation and increasing productivity can foster growth in this sector, Hannah Baudert, Federal Government Director at 麻豆原创 spoke with the Australian Small Business and Family Enterprise Ombudsman (ASBFEO), Kate Carnell in the dedicated

For the , Anton Kroger, Director of Energy and Natural Resources at 麻豆原创 hosted a discussion with Angela Williamson, Partner at Integral Supply Networks Advisory, Sanjiv Manchanda, CEO for Atlas Iron, and Robert McCarthy, GM at Dyflex Solutions.

A key takeaway from this session was the importance of engaging with remote workforces and contractors while managing supply chains during this time of uncertainty. With ever-changing legislation and continued fears around the safety and supply of resources 鈥� both human and material, mining operators should utilise technology that helps keep its various stakeholders connected and compliant.

As highlighted in the discussion, it鈥檚 not just about reducing costs and maintaining business continuity but ensuring the productivity and wellbeing of various staff members, processes, and equipment throughout the product lifecycle. Miners should use this opportunity to take stock prior to digital transformation, understand business capacities and systems to ensure they鈥檙e aligned with overarching strategic goals.

Evan Mantis, General Manager for Consumer and Service Industries at 麻豆原创 introduced the with Steven Moraitakis, Transformation Lead for Consumer Goods and Retail at 麻豆原创, and Jackie Pearson, Executive GM for Business Transformation at Sigma Healthcare.

Ms Pearson which they kick-started due to the legacy 鈥榯echnology debt鈥� created across the organisation. With four separate ERP systems and a host of different applications that were highly customised, disparate, and not providing the necessary insights, Sigma Healthcare needed to optimise its technology and processes to operate more intelligently.

Moving ahead with their digital transformation program not only mitigated risk but broke down structural silos and unified all parts of the organisation, allowing staff to work more efficiently while creating value in multiple business areas. Currently in the process of evolving its ERP ecosystem to integrate all data touchpoints into a single platform with 麻豆原创 S/4HANA, Sigma Healthcare was able to withstand the COVID-19 disruption by relying on agile technology and its best in class distribution centres. Ms Pearson is fiercely powering through implementation remotely, emphasising the organisation鈥檚 ability to quickly adapt to new circumstances.

For the , Jonathan Fogarty, Utilities Lead Architect for 麻豆原创 hosted a panel discussion with Danica Lawrence, IS Lead Chief Architect for Powerco NZ, Rob Scott, Director and Principal of HR Strategy and Innovation at Deloitte, Aaron Green, Senior VP and Head of 麻豆原创 SuccessFactors APAC, and Gavin Mooney, Utilities Lead Architect for 麻豆原创 Australia.

With ongoing challenges and uncertainties, the panel discussed the importance of connecting and collaborating with staff while maintaining company culture. As businesses focus on productivity and safety, the key is facilitating remote work with operational and intelligent technologies 鈥� helping staff to work seamlessly and minimising manual, in-field work. For example, Internet of Things (IoT) and machine learning capabilities are facilitating predictive maintenance, optimising asset use and longevity while increasing the efficiency of maintenance crews. By assisting fieldworkers through augmented reality, and reducing the amount of fieldwork required using touchless substations and smart metering, utilities are improving their processes and keeping everyone safe during the pandemic.

In the , Peter Jose, General Manager for Financial Services at 麻豆原创 introduced a discussion between Darryl Fox, Industry Account Director at 麻豆原创 and David Earls, Executive GM of Enterprise Services and Technology at IAG. They discussed how IAG are utilising digital technology to empower staff, stay connected to their customers and maintain service continuity. Prior to the lockdown, IAG already had 30% of staff working predominantly from home which helped set a solid foundation in terms of technologies and practices for ensuring productivity.

Evan Mantis opened the with Asha Bisla, GM of Business Applications at Broadspectrum, Shenaz Bilkis, Global Industry Director for Construction and Real Estate at 麻豆原创, and Mike Denning, Business Architect for Service & Engineering Industries at 麻豆原创.

Asha shared insights into how Broadspectrum are working closely with strategic partners to fast track critical processes. Leveraging technology allowed the business to facilitate remote working at scale, manage the scheduling and safety of projects and people, while using communications and analytics software to forecast and plan for ever-changing circumstances.

Uday Bonu, Regional Industry Lead for Public Sector at 麻豆原创 , VP of Digital Government Transformation at 麻豆原创 to explore the impact of COVID-19 on public services and the strategies that can help governments work more efficiently to deal with the increasing demand for social services in the face of declining revenues. By implementing and accelerating digital initiatives, governments and private businesses can help set the industry norms and motivate change for the better in terms of processes and systems.

Taking insights from each of these industry sessions, it is clear that organisations of all sizes, in all industries, are squarely focussed on safeguarding their employees and customers, while maintaining business continuity. Technology and digitisation is playing a vital role in supporting and facilitating rapid change. In polling attendees, 麻豆原创 found that businesses across industry sectors are reprioritising and/or accelerating digitalisation projects in response to the pandemic 鈥� using the global shift to focus more on future-proofing operations.

Access the from the 麻豆原创 2020 Adaptive Strategies in a Changed World ACCELERATED Forum to gain further insights on specific industry challenges and how 麻豆原创 solutions are helping organisation to become more adaptive and resilient in this rapidly changing environment.

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We鈥檝e seen the immense shutdown of travel 鈥� significantly limiting the movement of people and goods everywhere with widespread economic ramifications. Government, healthcare providers, suppliers, and other industries are co-ordinating in ways we have never experienced before to ensure continuity of service and that the public remain safe and informed.

To help organisations as they navigate through this challenging period, 麻豆原创 recently hosted a series of virtual forums called . This digital event featured industry-specific episodes to provide perspectives on how businesses might adjust, adapt, and thrive in this crisis.

I participated as part of the public services session alongside Lee Miezis, CEO at Bushfire Relief Victoria and Simon Bush, GM Policy and Advocacy at Australian Information Industry Association (AIIA) and managing director, Bush Consulting. Together we discussed the impact of COVID-19 on workforces, legislation, risk and compliance, and the critical role of technology in helping businesses and society emerge from this stronger than before.

Let鈥檚 take a look at some of the key points that were discussed:

The Vital Importance of Good Data
Governments have crisis plans but putting them into effect at scale is challenging at the best of times. How this is done can have a massive impact upon our lives, families, society and our economy.

The main challenge lies in when to act and how to ensure successful execution especially in the middle of the crisis itself. Lee will provide insights from his experiences during the recent bushfire crisis, the vital importance of data to enable smart decision-making, and how they have built a culture of resilience to adapt in times of need.

Rebuilding Trust Through Technology
We鈥檝e spoken previously on the importance of building public trust by understanding citizen鈥檚 expectations and experiences. The wide-reaching capacities and applications of technology make this easier than ever before. Intelligent technology was a vital cornerstone in creating the experience economy, and now 鈥� more than ever 鈥� people鈥檚 experiences will inform how well we emerge from this current crisis.
Citizens need to feel they can trust governments 鈥� especially during times of crisis.

This means being transparent in terms of response and funding, ensuring people understand the legislative changes that are developing as rapidly as COVID-19 news unfolds. Communication through digital platforms not only facilitates better accessibility for public service providers and citizens, but can be used to help co-ordinate response efforts across industry sectors.

To learn more about how public services and governments are mitigating risks and responding to this global pandemic, to the second edition of the 鈥� going live on August 6^th 2020.

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