This is a brief summary of some of the major differences between the New Normal and the Great Bounce Forward. I look forward with excitement and some trepidation towards this future. One where business success will be dictated not only by our customer obsession, but also the ability of our business to pivot, shift, change and adapt.
I can’t tell you what will happen in the future – a green revolution? Another pandemic? A major war? A global recession? Market hypergrowth? All the people living life in peace? Imagine that…
What I can tell you is what your organisation needs to do to be able to meet all of these challenges head-on and set yourself up for success. And to me, that won’t look like the new normal. There is nothing normal about these business capabilities at all.
But it is not just about offering online sales. In the digital world, customers now expect to be able to track packages, get alerts when they are delivered, and have access to easy and free returns. Again – if you don’t do this today, you are creating poor customer experiences and are most likely losing business to those that offer great experiences.
Here is what organisations are witnessing:
The need to evolve their CRM solution. Salespeople expect the CRM to give them insights on who to sell to, why to sell to them and what approach will work best. CRM systems that don’t provide this analysis are letting businesses and salespeople down.
Analytics has to be turned into actions. More businesses are telling their analytics partners to stop telling them what to do, and just do it! Automating the outcomes of BI and analytics is beginning to be expected.
Ease of use has become essential. Interactions and processes need to be intelligent and easy to automate. We no longer throw teams of people at challenges – we automate the outcomes and use technology to deliver entirely new experiences without teams of employees pulling strings behind the scenes.
Process and technology changes happen quickly and seamlessly. We have been taught this by Zoom, Microsoft, AWS and Google. If you aren’t doing this today, you are behind the market and behind the expectations of your employees and customers.
Ecosystems are emerging to enable this agility and innovation. We can now innovate with a growing range of partners. Companies can partner for a single sale and move on. Start-ups are being embraced by dinosaurs, and competitors are becoming partners. More companies than ever are involving their own customers in their innovation processes. Ecosystems are changing the ability of technology and business teams to offer new and improved services to customers and employees.
Time for a Shift in Organisational Culture
Seemingly, the world changed overnight. But many of these changes have been in the works for years. It just took a global crisis to highlight how important they are and how much organisations need to change to embrace these opportunities. The only thing holding businesses back from thriving in the Great Bounce Forward are their people and culture. If you can embrace these changes, your businesses will move forward and emerge as different companies to the ones that entered the pandemic in early 2020. You’ll be more open, agile, innovative and digitally aware. You’ll be able to move in new, unheralded directions, driving improved customer, shareholder, or citizen value.
So stop thinking about how your business will bounce back. Make plans for it to bounce forward into the unknown.
Last week Microsoft announced the acquisition of Nuance for an estimated USD 19.7 billion. This is Microsoft’s second largest acquisition ever, after they acquired LinkedIn in 2016. Nuance is an established name in the Healthcare industry and is said to have a presence in 10,000 healthcare organisations globally. Apart from Healthcare, Nuance has strong capabilities in Conversational AI and speech solutions to support other industries. This acquisition is in line with Microsoft’s go-to-market roadmap and strategies.
Microsoft’s Healthcare Focus
Microsoft announced their Healthcare Cloud last year and this acquisition will bolster their Healthcare offerings and market presence. Nuance’s product portfolio includes clinical speech recognition SaaS offerings – Dragon Ambient eXperience, Dragon Medical One and PowerScribe One for radiology reporting – on Microsoft Azure. The acquisition builds on already existing integrations and partnerships that were in place over the years.
“Microsoft Cloud for Healthcare offers its solution capabilities to healthcare providers using a ‘modular’ approach. Given how diverse healthcare providers are in their technology maturity and appetite for change, the more diverse the ‘modules’, the greater the opportunities for Microsoft. This partnership with Nuance also brings to the table established relationships with EHR vendors, which will be useful for Microsoft globally.
The Healthcare industry continues to struggle as the world negotiates the challenges of mass vaccination. But on the upside, the ongoing Healthcare crisis has given remote care a much-needed shot in the arm. Clinicians today will be more open to documentation and transcription services for process automation and compliance. The acquisition of Nuance’s Healthcare capabilities will definitely boost Microsoft’s market presence in provider organisations.
However, Healthcare is not the only industry that Microsoft and Nuance are focused on. The Microsoft Cloud for Retail that was launched earlier this year aims to offer integrated and intelligent capabilities to retailers and brands to improve their end-to-end customer journey. Nuance has omnichannel customer engagement solutions that can be leveraged in Retail and other industries. As Microsoft continues to verticalise their offerings, they will consider more acquisitions that will complement their value proposition.“
Microsoft’s Focus on Conversational AI
Microsoft already has several speech recognition offerings, speech to text services, and chatbots; and they continue to invest in the Conversational AI space. They have created an open-source template for creating virtual assistants to help Bot Framework developers. In February, Microsoft announced their industry specific cloud offerings for Financial services, Manufacturing, and Non-Profit, and also introduced a series of AI and natural language features in Microsoft Outlook, Microsoft Teams, Microsoft Office Lens and Microsoft Office mobile to deliver interactive, voice forward assistive experiences.
“There is no slowing down in this space and the acquisition clearly demonstrates the vision that Microsoft is building with Nuance – a vendor that has made speech recognition, text to speech, conversational AI the foundation of the company. This is a brilliant move by Microsoft in the Conversational AI space and a win-win for both companies.
This move could also mark further inroads for Microsoft into the contact centre space. With Teams now being integrated into contact centre technologies, working with large customers using speech and conversational AI, Dynamics 365 could herald the start of more acquisitions for Microsoft to bolster a wider customer engagement vision.
The Conversational AI war is heating up and various other cloud vendors such as Google and AWS are starting to get aggressive and have made investments in recent years to enhance their Conversational AIcapabilities. Google Dialogflow has been seeing rapid uptake and they now have deep partnerships with Genesys, Avaya, Cisco and other contact centre players. Microsoft coming into the game and acquiring a company with years of history and IP in the speech space, demonstrates how the cloud battle and the war between Google, Microsoft and AWS is heating up in the Conversational AI. All of a sudden you have Microsoft as a powerhouse in this game.”
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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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 market is growing rapidly with large global RPA specialists such as UiPath, Automation Anywhere, Blue Prism and AntWorks experiencing high rates of growth in the region.
RPA vendors in Asia Pacific, are typically addressing immediate, short-term requirements. For example, healthcare companies are automating the reporting of COVID-19 tests and ordering supplies. Chatbots are being widely used to address unprecedented call centre volumes for airlines, travel companies, banks and telecom providers. Administrative tasks increasingly require automation as workflows become disrupted by remote working.
Companies can also be expected to scale their current deployments and increase the rate at which AI capabilities are integrated into their offerings
RPA often works in conjunction with major software products provided by companies such as Salesforce, SAP, Microsoft and IBM. For example, some invoicing processes involve the use of Salesforce, SAP and Microsoft products. Rather than having an operative enter data into multiple systems, a bot can be created to do this.
Large software vendors such as IBM, Microsoft, Salesforce and SAP are taking advantage of this opportunity by trying to own entire workflows. They are increasingly integrating RPA into their offerings as well as competing directly in the RPA market with pureplay RPA vendors. RPA may soon be integrated into larger enterprise applications, unless pureplay RPA vendors can innovate and continually differentiate their offerings.
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First, let me share a couple of general observations. Currently, we are still in the eye of the storm. Many are unable to see any light at the end of the tunnel. There is quite a bit of negative sentiments, and some fail to see that the situation will ever improve. I am sure similar thoughts occurred during other crises: the 1918 Pandemic (Spanish Flu); the Great Depression of the 1930s; the Dot.com bust of 2001; SARS in 2003; and the Global Financial Crisis/Great US Recession of 2007. During each of these events, a sense of impending Armageddon came over much of the population. Certainly, in each instance, people did experience some personal and social permanent changes, with which they learned to adapt and cope. But, inevitably, the world did go on and Armageddon did not occur.
One of the basic truths I believe, is that humans require and crave interaction with other humans. Think about the videoconferencing applications. The use of these apps grew exponentially as the main communication channel. Instead of just audio, it was audio and video. These mediums greatly assisted society in coping and adapting. Mankind, and the Natural World, will always find a way.
Here are the predictions from the article:
Companies that traffic in digital services and e-commerce will make immediate and lasting gains
Remote work will become the default
Many jobs will be automated, and the rest will be made remote-capable
Telemedicine will become the new normal, signaling an explosion in med-tech innovation
The nationwide student debt crisis will finally abate as higher education begins to move online
Goods and people will move less often and less freely across national and regional borders
After an initial wave of isolationism, multilateral cooperation may flourish
I very much agree with the author’s first prediction. This one is fairly obvious, as it has proven true throughout the crisis with providers such as Amazon, Zoom and others. It is expected to continue into the post COVID world. This is also evident from the findings of the Ecosystm research on the impacts of COVID-19. Organisations intend to continue to use digital technologies, even after the immediate crisis is over (Figure 1).
A Natural State of Equilibrium will Emerge
I believe for each of the areas described in the predictions, there will be various levels of long-term modification. None of them will return to their pre COVID-19 state, as we have all experienced going down the rabbit hole. During the pandemic, due largely to the lockdowns, the pendulum swung significantly towards one side. Many times, when people predict a new view, the current state is considered the New Normal. For me, the relevant question is: Will things stay as they are now, or will there be a new natural state of equilibrium? If so, what will it look like, in each of these areas? I don’t believe there is one answer, or one New Normal for all the dimensions being discussed. I believe a new normal state will potentially be different for each individual, each company/entity and each condition. In a post COVID-19 world there could be 50 shades of grey in each of these areas.
One of the predictions states that remote work will become the default. It must be remembered that part of work is a collaborative effort. While video conferencing has enabled collaborative efforts, the importance of the accidental interaction at the break room, printer, etc. can’t be under-estimated. It is these unscheduled interactions that enable accidental collaboration which can lead to great solutions. Thus, there will be many shades to the Future of Work – there will not be one absolute.
A similar example is a prediction for higher education. Part of the learning process a university offers is interacting with people who are not similar to your background or beliefs. That is one of the benefits of a diverse university. Similar to the corporate environment, many different types of learning environments will enable a person to gain great experiences from the time at university.
The advantage of all these alternatives will be the additional options and benefits to people post COVID compared to the pre COVID-19 world. It will present many great opportunities for entrepreneurs and innovators, as well as end-users and consumers. It will create new and iterative ‘middle spaces’. It will be possible for a David to emerge and challenge a Goliath(s).
The two Chinese characters for the word ‘crisis’ are “danger” and “opportunity”. Just as we are in a dangerous time now, it has also presented new and different opportunities. Those opportunities will continue to exist even when the danger has passed. I am also reminded of the old expression “May you live in interesting times”. It very much applies to all of us now and in the future. I wish the same for all of you.