The Need to enable Foundational Shifts. The younger generation is more aware of environmental, social and governance issues that the world continues to face. Many of the countries in the region are emerging economies, where these issues become more apparent. COVID-19 has also inculcated an empathy in people and they are thinking of future success in terms of impact. The desire to enable foundational shifts is giving direction to the transformation journey in the region. The wonderful new paradigm that is the Digital Economy allows us to cut across all segments; and technology and its advancements has immense potential to create a more sustainable and inclusive future for the world.
Realising the Power of Momentum. The pandemic has caused major disruptions in the region. But every crisis also presents an opportunity to perhaps re-imagine a brighter world through a digital lens.The other thing that the pandemic has done is made people and organisations realise that to succeed they need to be open to change – and that momentum is important. As organisations had to pivot fast, they realised what I have been saying for years – we shouldn’t “let perfect get in the way of better”. This adaptability and the readiness to fail fast and learn from the mistakes early for eventual success, is leading to faster and more agile transformation journeys.
Where are we seeing the most impact?
Industries are Transforming. There are industries such as Healthcare and Education that had to transform out of a necessity and urgency brought about by the COVID-19 pandemic. This has led to a greater impetus for change and optimism in these industries. These industries will continue to transform as governments focus significantly on creating “Social Safety Nets” and technology plays a key role in enabling critical services across Health, Education and Food Security. Then there are industries, such as the Financial Services and Retail, that had a strong customer focus and were well on their digital journeys before the pandemic. The pandemic boosted these efforts.
But these are not the only industries that are transforming. There are industries that have been impacted more than others. There are several instances of how organisations in these industries are demonstrating not only resilience but innovation. The Travel & Hospitality industry has had several such instances. As business models evolve the industry will see significant changes in digital channels to market, booking engines, corporate service offerings and others, as the overall Digital Strategy is overhauled.
Technologies are Evolving. Organisations depended on their tech partners to help them in their make the fast pivot required to survive and succeed in the last year – and tech companies have not disappointed. They have evolved their capabilities and continue to offer innovative solutions that can solve many of the ongoing business challenges that organisations face in their innovation journey. More and more technologies such as AI, machine learning, robotics, and digital twins are getting enmeshed together to offer better options for business growth, process efficiency and customer engagement. And the 5G rollouts will only accelerate that. The initial benefits being realized from early adoption of 5G has been for consumers. But there is a much bigger impact that is waiting to be realised as 5G empowers governments and businesses to make critical decisions at the edge.
Tech Start-ups are Flourishing. There are immense opportunities for technology start-ups to grow their market presence through innovative products and services. To succeed these companies need to have a strong investment roadmap; maintain a strong focus on customer engagement; and offer technology solutions that can fulfil the global needs of their customers. Technologies that promote efficiency and eliminate mundane tasks for humans are the need of the hour. However, as the reliance on technology-led transformation increases, tech vendors are becoming acutely aware that they cannot be best-in-class across the different technologies that an organisation will require to transform. Here is where having a robust partner ecosystem helps. Partnerships are bringing innovation to scale in Asia.
We can expect Asia to emerge as a powerhouse as businesses continue to innovate, embed technology in their product and service offerings – and as tech start-ups continue to support their innovation journeys.
Ecosystm CEO Amit Gupta gets face to face with Garrett Ilg, President Asia Pacific & Japan, Oracle to discuss the rise of the Asia Digital economies, the impact of the growing middle class on consumerism and the spirit of innovation across the region.
Reconciling these seemingly conflicting requirements is possible. But it requires serious commitment from business and data/ analytics leaders – not (just) because regulators demand it, but because it is good for their customers and their business, and the only way to start capturing the full value from AI/ML.
1. ‘Heart’, not just ‘Head’
It is relatively easy to get people excited about experimenting with AI/ML. But when it comes to actually trusting the model to make decisions for us, we humans are likely to put up our defences. Convincing a loan approver, insurance under-writer, medical doctor or front-line sales-person to trust an AI/ML model – over their own knowledge or intuition – is as much about the ‘heart’ as the ‘head’. Helping them understand, on their own terms, how the alternative is at least as good as their current way of doing things, is crucial.
2. A Broad Church
Even in industries/ organisations that recognise the importance of governing AI/ML, there is a tendency to define it narrowly. For example, in Financial Services, one might argue that “an ML model is just another model” and expect existing Model Risk teams to deal with any incremental risks from AI/ML.
There are two issues with this approach:
First, AI/ML models tend to require a greater focus on model quality (e.g., with respect to stability, overfitting and unjust bias) than their traditional alternatives. The pace at which such models are expected to be introduced and re-calibrated is also much higher, stretching traditional model risk management approaches.
Second, poorly designed AI/ML models create second order risks. While not unique to AI/ML, these risks become accentuated due to model complexity, greater dependence on (high-volume, often non-traditional) data and ubiquitous adoption. One example is poor customer experience (e.g., badly communicated decisions) and unfair treatment (e.g., unfair denial of service, discrimination, misselling, inappropriate investment recommendations). Another is around the stability, integrity and competitiveness of financial markets (e.g., unintended collusion with other market players). Obligations under data privacy, sovereignty and security requirements could also become more challenging.
The only way to respond holistically is to bring together a broad coalition – of data managers and scientists, technologists, specialists from risk, compliance, operations and cyber-security, and business leaders.
3. Automate, Automate, Automate
A key driver for the adoption and effectiveness of AI/ ML is scalability. The techniques used to manage traditional models are often inadequate in the face of more data-hungry, widely used and rapidly refreshed AI/ML models. Whether it is during the development and testing phase, formal assessment/ validation or ongoing post-production monitoring, it is impossible to govern AI/ML at scale using manual processes alone.
o, somewhat counter-intuitively, we need more automation if we are to build and sustain trust in AI/ML. As humans are accountable for the outcomes of AI/ ML models, we can only be ‘in charge’ if we have the tools to provide us reliable intelligence on them – before and after they go into production. As the recent experience with model performance during COVID-19 suggests, maintaining trust in AI/ML models is an ongoing task.
I have heard people say “AI is too important to be left to the experts”. Perhaps. But I am yet to come across an AI/ML practitioner who is not keenly aware of the importance of making their models reliable and safe. What I have noticed is that they often lack suitable tools – to support them in analysing and monitoring models, and to enable conversations to build trust with stakeholders. If AI is to be adopted at scale, that must change.
Shameek Kundu is Chief Strategy Officer and Head of Financial Services at TruEra Inc. TruEra helps enterprises analyse, improve and monitor quality of machine
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Woolworths has committed to invest AUD 50 million in upskilling and reskilling their employees in areas such as digital, data analytics, machine learning and robotics over the next three years. The move comes as a response to the way the Retail industry has been disrupted and the need to futureproof to stay relevant and successful. The training will be provided through online platforms and through collaborations with key learning institutions.
The supermarket giant is one of Australia’s largest private employers with more than 200,000 employees. Under Woolworths’ ‘Future of Work Fund’ their staff will be trained across supply chain, store operations, and support functions to enhance delivery and decision-making processes. The retailer will also create an online learning platform that will be accessible by Woolworths employees as well as by other retail and service companies to support the ecosystem. Woolworths has plans to upskill their staff in customer service abilities, leadership skills and agile ways of working.
Woolworths’ upskilling program will also support employees who were impacted by Woolworths planned closures of Minchinbury, Yennora, and Mulgrave distribution centres due in 2025.
Woolworths’ Tech Focus
Woolworths has been ramping up their technology investments and having tech-savvy employees will be key to their future success. In October 2020, Woolworths deployed micro automation technology to revamp their eCommerce facility in Melbourne to speed up the fulfilment of online grocery orders, and front and back-end operations. Woolworths also partnered with Dell Technologies in November 2020 to bring together their private and public cloud onto a single platform to improve mission-critical processes, applications and support inventory management operations across its retail stores.
Future of Work
For many years, Ecosystm has been advising our clients to invest more in the skills of the business. Every business will be using more cloud next year than they are this year; they will suffer more cybersecurity incidents; they will use more AI and machine learning; they will automate more processes than are automated today. More of their customer engagements will be digital, and more insight will be required to drive better outcomes for customers and employees. This all needs new skills – or more people trained on skills that some in the business already understand. But too many businesses don’t train in advance – instead waiting for the need and paying external consultants or expensive new hires for their skills. Empowered businesses – ones that are creating a future-ready, agile business – invest in their people, work environment, business processes and technology to create an environment where innovation, transformation and business change are accepted and encouraged (Figure 2).
Empowered businesses can adapt to new challenges, new market conditions and respond to new competitive threats. By taking these steps to upskill and empower their employees, Woolworths is building towards empowering their own business for long term success.
Transform and be better prepared for future disruption, and the ever-changing competitive environment and customer, employee or partner demands in 2021. Download Ecosystm Predicts: The top 5 Future of Work Trends For 2021.
So for your company, once employees re-enter the workplace, how will your company create those processes, that level of trust and faith, that would allow movements and health status to be tracked by office automation? For example, how often should employees overtly be aware of their temperature being scanned?
Abilities of Buildings to Manage
Facilities management is trending towards intelligent building management systems (iBMS) which know about room occupancy, room hygiene and are tracking who has been where and with whom. Elevators will limit occupancy and direct users to the correct lift going to the correct location. I have already seen this in our city hospital where you get directed to the correct lift once you have entered information on your destination. This combines user interface devices such as touchless pads, system hardware, and access control management software.
The building can also possibly direct you via a building app to request a place to work. You could swipe your personnel card and then be shown several options based on your personal profile and job role, including private quiet rooms, communal areas, and outside meeting tables. Previous occupants can be noted to share hygiene tracing if necessary. Intelligent buildings already offer direct support to the employees who interact with them for HVAC, lighting control, and occupation sensor. They have the ability to reduce user friction while raising workplace experience metrics to create a measured environment.
User Trust & Participation
Users should be willing to participate to get access. To create the trust that is required for employees to be willing to participate in the process, companies need to share policies and demonstrate stewardship of the data accessed. Who is holding my locational data, for how long, and for what purpose?
Trust facilitates successful data sharing, which in turn reinforces trust. Trust is built when the purpose of data sharing is made clear, and when those involved in the process know each other, understand each other’s expectations, and carry out their commitments as agreed. Trust increases the likelihood of further collaboration and improves core surveillance capacity by supporting surveillance networks.
Will we put our trust in buildings and facilities management on our return to the office? If communication is clear and policy well articulated, the building can play a role in engaging users to return to some standards of in-office participation. But if communication is muddy and policy not made clear, people will make their own way to safety – potentially impacting the environment of others.
Transform and be better prepared for future disruption, and the ever-changing competitive environment and customer, employee or partner demands in 2021. Download Ecosystm Predicts: The top 5 Future of Work Trends For 2021.
Despite the pressure on budgets Ecosystm data makes a strong case to not cut your customer experience (CX) spend! Businesses in Singapore that are cutting their CX spend are less likely to return to growth, more likely to be competing on price (hence cutting margins), not focused on their digital and omnichannel customers, and have lower levels of innovation. Funnily enough, these are also the businesses with complex, legacy systems which need more focus to provide an improved CX! To be quite frank, businesses in Singapore who are cutting CX spend are setting themselves up for failure. With other businesses increasing CX spend, the gap between the customer experiences will grow to a point where customers will leave and it will be hard to catch up.
Prioritising your CX Spend
So now that you have secured your CX spend, where will you get the biggest bang for your buck? Let’s look at where businesses in Singapore are focusing their CX initiatives in 2021.
Offering an omnichannel experience. Your customers expect more than just a great digital experience – they want the right experience at the right touchpoint. The CX leaders in Singapore (who, unsurprisingly are often the market leaders) are already offering great omnichannel experiences, so this is quickly becoming about catching up – and not about getting ahead. Providing a consistent, personalised, and optimised experience across your digital touchpoints needs to be a top priority for your business today. If you are not offering conversational commerce solutions, start that strategy as soon as possible – you need to be where your customers are today. Extending this to physical channels and broader ecosystem partners should also be on your agenda.
Improving knowledge systems. Your knowledge systems don’t do what they say on the box. They don’t provide answers to questions – for employees or customers. In fact, if your customer service agents get asked a question they don’t know the answer to, their number one source for answers is actually their colleagues or team leaders – NOT the knowledge management system! Start investing in systems – or ideally a single system – that help your employees get better, faster answers to questions. Make sure that the system is providing the same answers to both your employees and your customers across all touchpoints – physical and digital.
Migrating customer service platforms to the cloud. Over half the businesses in Singapore that we assessed have this as a top CX priority. Cloud solutions offer faster time to value, lower management costs, give access to more regular improvements and often provide the ability to easily integrate with partners who offer product extensions and customisations. This trend will continue in 2021 and 2022 as more businesses realise that their legacy customer service or contact centre platform is inhibiting their ability to innovate their customer experience. These systems also help businesses to stay compliant and reduce the reliance on internal IT – which has traditionally struggled to keep up with the fast-changing nature of the contact centre and customer service teams.
Investing in AI and machine learning. Many businesses are using AI to provide the personalised and optimised customer experiences they aspire to. AI and machine learning are allowing businesses to create personalised offers, offer a next-best action and automate services. Advanced banks in Singapore can create interest rate offers for each individual customer based on their credit profile and history. 46% of businesses in Singapore are already using AI to offer recommendations for customer service agents, 44% to optimise or test messaging and campaigns and 43% to provide faster, more accurate access to information and knowledge. 18 months ago, AI was a business differentiator – allowing your business to create a stand-out CX. Today AI is quickly becoming a standard practice – the battle now is around using AI to create personalised and optimised experiences.
A great customer experience will be the most important factor in lifting your business to pre-pandemic growth levels and helping your business remain competitive in today’s tough business conditions. When it comes to CX, there is no such thing as “saving your way to growth”.
Your opportunity to drive greater business success lies in your ability to better win, serve and retain your customers. Refresh your customer strategy and capability today to make 2021 an exceptional year for your business.
SAS announced that it has acquired Boemska, a provider of low-code development tools and analytics workload management software. The small, privately held company is UK-based with an R&D centre in Serbia. The acquisition will be integrated into SAS Viya, its cloud-native platform, which includes containerised analytics and machine learning offerings. Terms of the deal have not been disclosed.
A SAS silver partner, Boemska has wins in Health, Finance, and Travel. Most of its reference clients are based in Europe in addition to a small number in the US and South Africa. Boemska has two primary software offerings – Enterprise Session Monitor (ESM) and AppFactory. Additionally, it delivers cloud migration, performance diagnostics, and application development services.
Boemska ESM provides visibility into performance and cost management of analytics workloads. The product enables self-service root cause analysis for developers, monitoring and batch schedule optimisation for administrators, and departmental cost allocation of cloud resources. ESM manages SAS, R, and Python workloads and is compatible with workload management platforms from the likes of IBM and BMC. Boemska shipped an updated version of ESM in 2020 to improve the UI and ensure support for SAS Viya. At the time, it announced that its development team had doubled in the preceding 12 months, suggesting a trajectory of growth.
SAS Focuses on Cloud-Native Analytics and AI
SAS launched Viya 4.0 in mid-2020, a major step in its vision to become a provider of cloud-native analytics and machine learning solutions. The platform includes offerings, such as Visual Analytics, Visual Statistics, Visual Machine Learning, and Visual Data Science packaged in containers and orchestrated by Kubernetes. Microsoft Azure has become its preferred cloud partner, assisting in developing SAS Cloud, hosted from data centres in the US, Brazil, Australia, and newly launched facilities in Germany and the UK. Viya managed services are also available from Azure regions. AWS and Google Cloud are expected to make the leap to Viya 4.0 from version 3.5 soon. As part of its cloud-native strategy, SAS now offers three tiers for software updates – bi-annual, monthly, or immediately after release.
The major overhaul of SAS Viya is part of the vendor’s USD 1B investment into AI over three years from 2019-2021. The platform includes a heavy emphasis on NLP, machine learning, and computer vision. The integration of Boemska’s low-code development offering into Viya will allow SAS clients to extract greater value from AI by quickly embedding it in mobile and enterprise applications. The converging trends of citizen developers and data literacy suggest SAS has selected the right path for the future.
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Let us focus on the use of NLP, specifically on how it has been used by banking authorities for policy decision making during the COVID-19 crisis. AI has the potential to read and comprehend significant details from text. NLP, which is an important subset of AI, can be seen to have supported operations to stay updated with the compliance and regulatory policy shifts during this challenging period.
Use of NLP in Policy Making During COVID-19
The Financial Stability Board (FSB) coordinates at the international level, the work of national financial authorities and international standard-setting bodies in order to develop and promote the implementation of effective regulatory, supervisory and other financial sector policies. A recent FSB report delivered to G20 Finance Ministers and Central Bank Governors for their virtual meeting in October 2020 highlighted a number of AI use cases in national institutions.
We illustrate several use cases from their October report to show how NLP has been deployed specifically for the COVID-19 situation. These cases demonstrate AI aiding supervisory team in banks and in automating information extraction from regulatory documents using NLP.
De Nederlandsche Bank (DNB)
The DNB is developing an interactive reporting dashboard to provide insight for supervisors on COVID-19 related risks. The dashboard that is in development, enables supervisors to have different data views as needed (e.g. over time, by bank). Planned SupTech improvements include incorporating public COVID-19 information and/or analysing comment fields with text analysis.
Monetary Authority of Singapore (MAS)
MAS deployed automation tools using NLP to gather international news and stay abreast of COVID-19 related developments. MAS also used NLP to analyse consumer feedback on COVID-19 issues, and monitor vulnerabilities in the different customer and product segments. MAS also collected weekly data from regulated institutions to track the take-up of credit relief measures as the pandemic unfolded. Data aggregation and transformation were automated and visualised for monitoring.
US Federal Reserve Bank Board of Governors
One of the Federal Reserve Banks in the US is currently working on a project to develop an NLP tool used to analyse public websites of supervised regulated institutions to identify information on “work with your customer” programs, in response to the COVID-19 crisis.
Bank of England
The Bank developed a Policy Response Tracker using web scraping (targeted at the English versions of each authority/government website) and NLP for the extraction of key words, topics and actions taken in each jurisdiction. The tracker pulls information daily from the official COVID-19 response pages then runs it through specific criteria (e.g. user-defined keywords, metrics and risks) to sift and present a summary of the information to supervisors.
Even with its enhanced efficiencies, NLP in SupTech is still an aid to decision making and cannot replace the need for human judgement. NLP in policy decision is performing clearly defined information gathering tasks with greater efficiency and speed. But NLP cannot change the quality of the data provided, so data selection and choice are still critical to effective policy making.
For authorities, the use of SupTech could improve oversight, surveillance, and analytical capabilities. These efficiency gains and possible improvement in quality arising from automation of previously manual processes could be consideration for adoption.
Attention will be paid in 2021 to focusing on automation of processes using AI (Figure 2).
Based on a survey done by the FSB of its members (Figure 3), the majority of their respondents had a SupTech innovation or data strategy in place, with the use of such strategies growing significantly since 2016.
For more mainstream adoption, data standards and use of effective governance frameworks will be important. As seen from the FSB survey, SupTech applications are now used in reporting, data management and virtual assistance. But institutions still send the transaction data history in different reporting formats which results in a slower process of data analysing and data gathering. AI, using NLP, can help with this by streamlining data collection and data analytics. While time and cost savings are obvious benefits, the ability to identify key information (the proverbial needle in the haystack) can be a significant efficiency advantage.
Singapore FinTech Festival 2020: Infrastructure Summit
For more insights, attend the Singapore FinTech Festival 2020: Infrastructure Summit which will cover topics tied to creating infrastructure for a digital economy; and RegTech and SupTechpolicies to drive innovation and efficiencies in a co-Covid-19 world.
Five9, a cloud-based contact centre solutions provider announced the acquisition of intelligent virtual agent (IVA) platform provider, Inference Solutions for about USD 172 million. Five9 and Inference Solutions have been partnering for the last couple of years, with Five9 being a reseller for Inference Solutions’ IVA platform. The acquisition is expected to provide a boost to Five9’s AI portfolio, automate contact centre agent activities and provide AI-based omnichannel self-service solutions.
The need to drive greater automation in the contact centre is high on the agenda, and this acquisition demonstrates how important AI and automation is to contact centre modernisation. The old-fashioned ways of long wait times, being passed on through different menus on the IVR and being asked to repeat yourself through the older speech recognition engines is starting to not only frustrate customers but will become obsolete. Based on Ecosystm’s research, close to 60% of contact centres globally stated that investing in machine learning and AI is a top customer experience priority in the next 12 months.
Inference has come a long way since its inception at Telstra Labs
Inference Solutions (founded in 2005) was spun out of Telstra Labs. It has since expanded to the US and developed a suite of solutions in the IVA segment. They have a good partnership strategy with the leading telecom providers globally as well as the UC/contact centre vendors. Inference Solutions uses resellers such as service providers, UC, and contact centre software providers – and these include AT&T, Cisco (Broadsoft), Momentum Telecom, Nextiva, 8×8 and many others. The Inference Studio solution will see a new release in the next few months where the solution will come pre-built with the ability for the contact centre team to pre-load the contact centre conversations. These can be conversations that have been going on for 6 months or longer. The Studio solution will then be able to analyse and understand the underlying intent of the conversation, match the intent so that it can be used to auto train the bots accurately. That process of matching the intent and training is expensive and if you can automate some elements of that, it will bring the cost of the deployment down. Its solution integrates into NLP engines from Google, AWS, and IBM. In Australia they continue to work on patents in close partnerships with Melbourne University and RMIT. Throughout its journey, Inference has built a good base of customers in the US, UK, and Australia.
Five9 to accelerate on its vision of AI and Cloud
Contact centre modernisation is high on the agenda for many organisations and this will lead them to build AI and automation at the core of their customer strategies. The discussion spans across the CEO, Digital and Innovation, and the Contact Centre teams.
Five9 had acquired Whendu, an iPaaS platform provider empowering businesses and developers with no-code, visual application workflow tool, optimised for contact centres in November 2019, and Virtual Observer, an innovative provider of cloud-based workforce optimisation, also known as Workforce Engagement Management (WEM) in February of this year.
The pandemic has resulted in increased engagement of contact centres with customers. Companies are gradually looking for ways to automate tasks, deliver better communication, speech and text recognition, decipher languages, and implement solutions mimicking humans. As a solution to these challenges, IVAs are being viewed as efficient and effective digital workers for a modern contact centre. IVAs represent increased throughput, more accurate results, and better-informed agents.
Successful use cases have shown that conversational AI can reduce calls and repetitive queries by 70-90%. IVRs with monolithic, complicated menus will start becoming unpopular and force contact centres to embark on a modernisation and automation strategy. If we evaluate the shift in priorities after COVID-19, we see that organisations are ramping up their self-service capabilities and their adopt of AI and machine learning (Figure 1).
The acquisition will give Five9 a foothold in the Asia Pacific region with an initial focus on the Australia market. The Australia market is by far the most advanced cloud contact centre market in the Asia Pacific. Five9 gains a team of staff that will help them fuel the contact centre modernisation discussion across the Asia Pacific. As the region has a complex market, the need to work with local carriers and partners will be critical for further expansion. Five9 has made an important acquisition in building in IVA capability into its CCaaS solution.
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The Top 5 Retail & eCommerce Trends for 2021
There Will Only be Omnichannel Retailers
The value of an omnichannel offer in Retail has become much clearer during the COVID-19 pandemic. Retailers that do not have the ability to deliver using the channel customers prefer will find it hard to compete. As the physical channel becomes less important new revenue opportunities will open up for businesses operating in adjacent market sectors – companies such as food and grocery wholesalers will increasingly sell direct to consumers, leveraging their existing online and distribution capabilities.
Most customers transact on mobile device – either a mobile phone or tablet. New capabilities will remove some of the barriers to using these mobile devices. For one, technologies such as Progressive Web Apps (PWA) and Accelerated Mobile Pages (AMP) will provide a better customer experience on mobile platforms than existing websites, while delivering a user experience at par or better than mobile apps. Also, as retailers become AI-enabled, machine learning engines will provide purchase recommendations through smartwatches or in-home, voice-enabled, smart devices.
COVID-19 Will Continue to be an Influence Forcing Radical Shifts
In driving the economic recovery in 2021, we will see ‘glocal’ consumption – emphasis on local retailers and global players taking local actions to win the hearts and minds of local consumers. There will be significant actions within local communities to drive consumers to support local retailers. Location-based services (LBS) will be used extensively as consumers on the high street carry more LBS-enabled devices than ever before. Bluetooth beacon technology and proximity marketing will drive these efforts. Consumers will have to opt-in for this to work, so privacy and relationship management are also important to consider.
But people still want to “physically” browse, and design aesthetics of a store are still part of the attraction. In the next 18 months, the concept of virtual stores that are digital twins will take off, particularly in the holiday and Spring clearance sales. Innovators like Matterport can help local retailers gain a more global audience with a digital twin with a limited technological investment. At a minimum, Shopify or other intermediaries will be necessary for a digital shop window.
The Industry will See Artificial Intelligence in Everything
AI will increase its impact on Retail with an uptake in two key areas.
Customer interactions. Retail AI will use customer data to deliver much richer and targeted experiences. This may include the ability to get to a ‘segment of one’. Tools will include chatbots that are more functional and support for voice-based commerce using mobile and in-home edge devices. Also, in-store recognition of customers will become easier through enhanced device or facial recognition. Markets where privacy is less respected will lead in this area – other markets will also innovate to achieve the same outcomes without compromising privacy but will lag in their delivery. This mismatch of capability may allow early adopters to enter other geographic markets with competitive offers while meeting the privacy requirements of these markets.
Supply chain and pricing capabilities. AI-based machine learning engines using both internal and increased sources of external data will replace traditional math-based forecasting and replenishment models. These engines will enable the identification of unexpected and unusual demand influencing factors, particularly from new sources of external data. Modelling of price elasticity using machine learning will be able to handle more complex models. Retailers using this capability will be in a better position to optimise their customer offers based on their pricing strategies. Supply chains will be re-engineered so products with high demand volatility are manufactured close to markets, and the procurement of products with stable demands will be cost-based.
Distribution Woes Will Continue
Third party delivery platforms such as Wish and RoseGal are recruiting additional international non-Asian suppliers to expand their portfolios. Amazon and AliExpress are leaders here, but there are many niche eCommerce platforms taking up the slack due to the uneven distribution patterns from the ongoing economic situation. Expect to see a number of new entrants taking up niche spaces in the second half of 2021, sponsored by major retail product brands, to give Amazon a run for their money on a more local basis.
As the USPS continues to be under strain, delivery companies like FedEx in the US who partner with the USPS are already suffering from the USPS’s operational slowdown, in both their customer reputation and delivery speed. In 2021, COVID-19 – and workers’ unions – will continue to impact distribution activities. Increased spending in warehouse automation and new retail footprints such as dark stores will be seen to make up for worker shortfalls.
China’s Retail Models Will Expand into Other Markets
China’s online businesses operate in a large domestic market that is comparatively free of international competitors. Given the scale of the domestic market, these online companies have been able to grow to become substantial businesses using advanced technologies. All the Chinese tech giants – among them Alibaba, ByteDance, DiDi Chuxing, and Tencent – are expanding internationally.
China’s rapidly recovering economy puts those businesses in a strong position to fund a competitive expansion into international markets using their domestic base, particularly with their Government’s promotion of the country’s tech sector. It is harder to impose restrictions on software-based businesses, unlike the approach that we have witnessed the US Government take for hardware companies such as Huawei – placing constraints on mobile phone components and operating systems.
These tech giants also have significant experience in a Big Data environment that provides little privacy protection, as well as leading-edge AI capabilities. While they will not be able to operate with the same freedom in global markets, and there will be other large challenges in translating Chinese experience to other markets – these tech players will be able to compete very effectively with incumbent global companies. Chinese companies also continue to raise capital from US stock exchanges with The Economist reporting Chinese listings have raised close to USD 17 billion since January 2020.
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