While these descriptors weren鈥檛 immediately unique, the conversation was. I caught up with one of the experts, Aidan Brecknell, who leads the digital supply chain team at 麻豆原创 ANZ, for his thoughts on what leading organisations are experiencing right now.

Resilient supply chains pivot with incredible speed

Having worked closely with supply chain leaders in ANZ, Brecknell said that organisations were redefining supply chain resilience for sustainable business.

鈥淭丑别 pandemic unleashed new challenges far beyond the capabilities of traditional lean supply chains that focused on executing repeatable processes at scale,鈥� he said. 鈥淟eaders understand that they need to address a new set of challenges like being able to turn on a dime to find different sources for raw materials, or even design and produce entirely new products. These organizations are modeling different scenarios, building in contingency plans, and executing on those.鈥�

During the broadcast, Brecknell and Martin Barkman, senior vice president and global head of digital supply chain marketing and solutions at 麻豆原创, shared the 鈥渨inning formula鈥� of modern supply chains. Unlike their lean predecessors, resilient supply chains are both customer and employee-centric, built on relationships with sustainable suppliers, and based on product sustainability across the entire lifecycle of an item.

Digitalisation transforms more than supply chains

The pandemic forced companies to understand and act on the difference between digitisation and digitalisation. Having data in digital form has long been the norm. Digitalisation means organizations can both capture intelligent data and change business processes including how supply chains operate. To be clear, this is not taking the same processes and making them digital. This is about creating completely new ways of managing supply chains by connecting information across applications company-wide and partners. During the broadcast, Brecknell summed it up like this:

鈥淪upply chains have been pushed and tested to their limits, and they鈥檝e become so reliant particularly locally on their ecosystem suppliers to access raw materials. It became evident quickly of the importance to digitalize processes within the supply chains, as well as the supply network itself,鈥� he said. 鈥淚n Australia and New Zealand, we saw some tremendous examples of where customers had invested ahead of the curve, and were able to transition quickly because of that agility in their supply chain.鈥�

One global industrial materials manufacturer digitalised supply chain processes to centrally manage over 200 inventory processes across 60 sites. The objective was to improve forecast accuracy, for on-time delivery, and greater profitability. Another 麻豆原创 customer, an energy and natural resources company, digitalised operations to better track freight emissions, providing real-time metrics for compliance with carbon neutral goals.

Interconnected data for supply chain resilience

Brecknell said there鈥檚 been significant customer uptake of 麻豆原创鈥檚 Business Network solution that brings together information from sourcing and production through finance, transportation logistics and delivery, including the entire product life cycle. With immediate, connected insights, companies can more profitably sense and respond to disruptions in a strategic, synchronised manner. Organisations can create more individualised, high-quality products in response to changing customer demands. They can prove their sustainability commitment as reflected in their choice of suppliers and operations. They can even attract and keep top talent who increasingly expect employer goals and actions to mirror personal sustainability values.

鈥淭丑别 allows organisations to connect all of their business partners on one central platform,鈥� said Brecknell. 鈥淲ith complete visibility into the entire supply chain, companies can collaborate with suppliers to source, track, and trace materials faster for shorter product delivery time frames as well.鈥�

As Barkman said during the broadcast, 鈥渂y capturing all the information about how the supply chain is operating, we preserve the digital thread of the supply chain. We have the information of how a product is being used, how assets are performing, and feed that back not just to the supply chain and manufacturing, but all the way to how products are designed.鈥�

Making a business case for supply chain networks

The elephant in the room is that interconnected business networks aren鈥檛 the reality in most organisations. Brecknell agreed that while connecting all this data and changing mindsets about how business operates is a huge undertaking, it鈥檚 well worth it.

鈥淥rganisations are getting on board with supply chain resiliency and sustainability because it鈥檚 good for business. With an extended collaborative network, organisations can mitigate supply chain risk even in the face of unexpected disruption,鈥� said Brecknell. 鈥淚f an organisation really wants to build resiliency and sustainability into supply chain, they have to have the data, and that has to be aligned across the entire supply chain.鈥�

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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聽

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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that supply chains are broken, exemplified through a lack of visibility, lack of collaboration, and lack of coordination.

Since most supply chains are based on transaction and reactive models, multi-faceted supply networks cannot adapt quickly enough to spikes or drops in demand. COVID-19 has inadvertently demonstrated the weaknesses of this system and highlighted the need for change.

Digital technology platforms can create the transparency and connectivity necessary to mitigate risks and navigate through crises. Visibility across supply networks is vital in response to emergencies. 鈥� ensuring that they were able to quickly develop a temporary hospital and use those beds to treat patients with COVID-19.

This is a time to unite, to focus on everyone鈥檚 safety and assist those we can. In response to the huge shifts we are seeing globally across industries, 麻豆原创 recently hosted a series of virtual forums called . There were seven industry-specific episodes focused on key challenges, solutions, and learnings from this current crisis.

Also, to help guide businesses through this challenging period, through the crisis period, to support an enhanced supply chain and improved experience management. These two critical branches of business dictate an organisation鈥檚 success 鈥� because a company鈥檚 ability to provide the right product and service to customers and staff is paramount.

Supply Chain Management and Disruption
麻豆原创鈥檚 primary focus has always been helping businesses anticipate and adapt to change through technology. Looking at supply chains, we鈥檝e already seen the importance of interconnectivity, the ability to create transparency across supply networks that is embedded across different organisations, departments, and borders. The more connected we can make disparate systems and processes, the greater visibility we can create across supply chains to better manage sudden spikes in demand.

The ability to intelligently manage supply chains with data driven insights helps business plan, adapt, and grow. It鈥檚 about understanding planning as a service, which is possible through , which is freely available for business looking to scenario planning and evaluation of supply chain impacts, options, and financial implications.

The also broadens the visibility of organisational supply chains to gain an understanding of suppliers鈥� situations, analyse risks, and better manage the experiences of staff and suppliers throughout the business ecosystem.

Using this solution, businesses can gather feedback suppliers to understand potential supplier restraints and delivery timelines risks, areas for optimisation, and ways to better collaborate with suppliers to ensure business continuity even during crises. This is critical as suppliers, staff, and customers all face extraordinary challenges and organisations must be seen as responsive and communicative.

Communication and Support for People
Building team cohesion during crises, or reskilling them for organisational changes, is vital. Employees need to feel heard and supported, which is why their engagement can be better managed and understood through platforms like Qualtrics.

using Qualtrics to understand how staff are feeling, the associated root causes, and what they can do to help. With the ability to provide this quick and convenient service across any device helps keep volunteers engaged and provides significant insights for improvement.

St John Ambulance also noted that the speed and ease at which Qualtrics was able to go live, the in-built reporting tools, and automatic alerts, have all made the volunteer experience easier to manage and understand.

The data insights produced during this time of crisis will help business safeguard themselves from future impacts, building resilience and discovering best practice. It is a challenging time, but it also presents an opportunity to refine practices and ensure that everyone is kept informed and safe.

麻豆原创 is here to help and provide assistance for any business struggling to digitally transform and adapt to these rapid changing circumstances.聽 to the second edition of the 鈥� going live on August 6^th 2020.

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