National Digital Strategies

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Most countries recognise the importance of digital technologies and have developed or are developing national digital strategies. Many of these efforts tend to be cookie-cutter approaches with a Christmas tree of initiatives. Such plans often borrow from others without customisation or contextualisation, while incorporating whatever happens to be the flavor of the month. We would argue that any attempt at a digital strategy should start with a strong sense of focus. In such endeavors, less is often more. Plans should also articulate overarching values, principles, and frameworks that can serve as a compass to set direction and bring a sense of coherence to disparate efforts by multiple stakeholders. Finally, no strategy is complete without a proper sequencing of initiatives.

Given the rapid digitalisation of economies across the world, we are fast moving from a paradigm that considers the digital economy within well-defined sectoral boundaries, to one where digital technologies are becoming ubiquitous – touching every facet of society. The phrase “digital economy” is losing significance as the economy itself becomes digital. In a context where digital technologies are getting embedded and enmeshed across the economy, the complexity of developing, coordinating and implementing national digital strategies has become a daunting task. The rapid rate at which new technologies and business models are emerging, makes it even harder for policymakers to keep pace.

In an environment of exploding complexity and rapid change, it is crucial to adopt a more structured and, in some sense, a more minimalist approach to digital strategy. Ideally, such an approach should look at digital strategy from four perspectives:

  1. Focus. Identification of the most critical areas that can have cascading impacts across the economy
  2. Guiding compass. Defining a broad set of values, principles, and frameworks to guide action by multiple players and align strategy to the achievement of societally relevant goals
  3. Organisational design. Redefinition and reinvention of the organisational structures of government to contend with fast moving technologies and business models
  4. Sequencing. Determination of the sequencing and timing of various policy interventions.

To elaborate further on these four dimensions:

Focus

Digital technologies are not an end in themselves but are tools for achieving societal objectives. Examples of such goals are national development plans, or the United Nations Sustainable Development Goals (SDGs). Another example is Kate Raworth’s ‘Doughnut Economics’ which wisely aims to balance planetary with societal goals.

Donut Economics, Kate Raworth

Keystone Objective. National development goals/SDGs tend to be broad in their scope, and there is a danger of efforts becoming too diffuse when incorporated as part of a national digital strategy. There may, therefore, be a need to sharpen the focus further. One approach might be to identify a keystone objective which can potentially have cascading impacts across the economy and use it for providing strategic focus.  Such a keystone would help reduce/eliminate redundancies and wasteful investments. In the corporate sector, Paul O’Neill’s singular focus on “zero worker injuries” while leading Alcoa is an enduring example of success.

A digital strategy that follows the various causal links to achieve the keystone goal of ‘Good Jobs for All’ as an example would end up touching upon every important aspect of the digital economy. It would be an interesting parallel to William Blake’s poem of seeing the “world in a grain of sand”.

Problem Statements. A great way of achieving focus is to identify problem statements and use them to solicit innovative solutions. Some leaders in digital government, e.g., Israel’s Ministry of Health, the Monetary Authority of Singapore, and the EU (among others) have been pursuing such an approach with a fair degree of success.

Guiding Values, Principles and Frameworks

National digital strategies would benefit from the adoption of values, principles, and frameworks that could provide broad guidance to multiple players undertaking their digitalisation initiatives. Having a directional compass would offer strategic alignment and cohesion – while allowing for innovation and creativity on the part of individual actors.

Example of Values. Values are the touchstone to decide what should be prioritised and to what purpose. Openness, positive impact, empathy, and compassion are excellent values adopted by many successful organisations.

Example of Guiding Principles. The UK has recently come up with the Gemini Principles for a National Digital Twins strategy:

Gemini Principles for a National Digital Twins strategy

Example of a Framework. The OECD has formulated a six-dimensional Digital Government Framework:

1. From the digitisation of existing processes to digital by design

2. From an information-centred government to a data-driven public sector

3. From closed data and processes to open by default

4. From a government-led to a user-driven administration

5. From government as a service provider to government as a platform

6. From reactive to proactive policy making and service delivery

Organisational Design

Existing organisational structures of government are primarily designed for an analog world and need to change to become more relevant in the digital era. A good starting point for an organisational redesign is the area of digital regulation which often adopts a narrow sectoral approach that is likely to be sub-optimal. Also, the rapid pace of technological change typically results in laws and rules lagging technology.

Digital regulation needs to be designed from the ground up to be cross-sectoral, cross-border, cross-platform, public-private, and technologically oriented. Given that digital technologies are general purpose technologies, their regulation should be cross-sectoral as a horizontal, rather than as a vertical. Given that data flows are often agnostic to national boundaries, and the most valuable tech companies (e.g., social media companies) are outside most national borders, it is essential to bring a cross-border perspective to regulation. Similarly, the oversight of Over the Top content (OTTs), for example, requires cross-platform approaches.

If regulatory actions have to keep pace with technology, it will be necessary for regulators to work upstream with innovators and startups through strong public-private partnerships.

Some countries starting with the UK have established regulatory sandboxes to work closely with the private sector. Regulators will also have to leverage technology better in the future to retain their relevance. A case in point is tackling online harms. It may be impossible to prevent the spread of harmful content on social media, without the use of automated safety technologies.

Sequencing

A sound digital strategy should have a correct sequencing of actions for promoting the digital economy. Foundational elements, e.g., broadband networks, ease of data access, cybersecurity, digital skills, agile regulation, and entrepreneurship deserve precedence over other aspects.

Finally, to paraphrase Boon Siong Neo and Geraldine Chen in their book ‘Dynamic Governance,’ in developing a national digital strategy it is crucial to think ahead, think across, think big, and think again.

 

 

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Awareness Personal Cyber Attacks
Awareness of Personal Cyber Attacks

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The NCSC’s first ‘UK cyber survey’ published alongside global password risk list. The UK government’s cybersecurity organisation National Cyber Security Centre (NCSC) provides cybersecurity support and guidance to the private and public sectors.

The survey identified exploitable gaps in personal level security management. The study was carried out between November 2018 and January 2019 and revealed that 89% of the respondents used the Internet and only 15% acknowledged a greater understanding of personal security measures.

The NCSC also published an analysis of the 100,000 most commonly used passwords that have been accessed by third parties in global cyber breaches. The analysis shows that less than half of the respondents do are not concerned about the strength of passwords for their emails and online accounts. Some examples of commonly used passwords used by people rely on their own names, Premier League football teams, musicians and fictional characters for inspiration.

This general lack of understanding of the cyber world can be harmful to individuals but can be devastating to organisations. A chain is no stronger than its weakest link, and insecure passwords may pose a serious security risk to an organisation. “We rely on passwords in all facets of our online world, so this presents a massive risk to anyone taking short-cuts.  Unfortunately, if organisations are not prepared, and allow the use of similarly insecure passwords, the flow on effect of a breach can escalate rapidly” says Alex Woerndle, Principal Analyst Cybersecurity, Ecosystm “The passwords in the above list are very weak. Even without the knowledge provided in the list, a hacker would be able to crack these passwords in seconds with the right tools. Even password complexity cannot always protect an organisation. What about a user that re-uses a complex password repeatedly, and that password is part of a breach? That puts all of the organisation’s logins at risk”.

There are some additional steps that system administrators and IT professionals need to consider when it comes to securing passwords and managing logins.

The global Ecosytsm Cybersecurity & Data Privacy study found the most common controls organisations implement to manage data access.

Security controls organisations implement to manage data access

“The main step being used currently is ensuring MFA is enabled wherever possible.  While not a perfect solution, it provides a circuit breaker for the most common types of attacks that would get anyone using insecure passwords into trouble” says Woerndle.

The NCSC hopes to reduce the risk of further breaches by building awareness of how attackers use easy-to-guess passwords, or those obtained from breaches and help guide developers and system administrators to protect their users. NCSC has framed guidelines covering multiple aspects of managing and maintaining security on its website.

Ultimately this problem will not go away until we find a genuine replacement for passwords. The pure scale of growth in the number of systems and applications that all users, both at a personal and on a professional level, have access to, makes password management complex and frustrating.  While focusing on how to strengthen your passwords and other easy steps to avoid a cyber attack, may be a good start, it will not be enough, as long as systems and applications are dependent on passwords for better security.


The Changing Shape of Asia’s Cybersecurity Landscape
The latest in our Leaders BreakFirst series. Following the launch of our Cybersecurity and Data Privacy study, Ecosystm is delighted to share the insights from almost 7000 deployments globally.Featuring two of Ecosystm’s cybersecurity and data privacy experts on one stage- Claus Mortensen and Carl Woerndle, this session will highlight the findings from our Cybersecurity & Privacy research.

Register Now

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AI IoT Sports
How IoT and AI will transform the sports business?

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This is an abstract of my presentation in Dubai on 23rd April 2019. I want to convey my special thanks to Dr. Eesa Bastaki, President of the University of Dubai for inviting me on the occasion. It was a magnificent experience delivering at such a great University.

In the year 2016, I considered Rio as the first Internet of Things (IoT) Olympic games in my article “The future of “The Internet of Olympic Games”. In Rio, we saw how athletes, coaches, judges, fans, stadiums, and cities benefited from IoT technology and solutions which transformed the way we see and experience sports. Next year we will have another opportunity to validate my predictions for the upcoming Tokyo 2020 Summer Olympics. Therefore, we may designate Tokyo as the first Artificial Intelligent (AI) Olympic Games.

During my presentation at the University of Dubai, I explained to the audience how incredible IoT and AI technologies are and to what extent they are impacting our sports experience. I elaborated on IoT and AI’s significant role in health management, improving aptitude, coaching, and training. These technologies are enabling athletes to improve performance, coaching for better preparation, fewer judgment errors, and a better experience for spectators. I also commented on the importance of IoT and AI to enhance the security of teams, audience, stadium, and cities altogether.

With the use of IoT and AI we are creating a world of smart things transforming sports business where every thousandth part of a second is crucial to predict the outcomes of a race, a match or a bet. I cited various examples on how different sports are utilising IoT and AI, and not in the least I shared a vision of the future that’s like 10-15 years onwards from the present – Can you envision a world of a real and virtual world of sports integrated together? Can you visualise robots and humans or super-humans playing together?

On the other side, speaking of the challenges involved with AI, IoT, and machine learning models for sporting, I conveyed the dark side of these technologies. We cannot forget the fact that the sports industry is a market and therefore enterprises, Governments, and individuals may make erroneous uses of these technologies.

In summary, it in this session I shared my point of view on-

  • How IoT and AI will transform coaches, athletes, judges, and fans.
  • How IoT and AI will attract the audience to the stadiums
  • How IoT and AI will transform the Industry?
  • How AI is changing the future of sports betting?

How IoT and AI will transform athletes, coaches, judges and fans?

Athletes

While the true essence of a sport still lies in the talent and perseverance of athletes, it is often no longer enough. Therefore, athletes will continue to demand increasingly sophisticated technologies and cutting-edge training techniques to improve performance. For example, we may see biomechanical machine learning models of players to predict and prevent potential career-threatening physical and mental injuries or can even detect early signs of fatigue or stress-induced injuries. It can also be used to estimate players’ market values to make the right offers while acquiring new talent.

Coaches

Coaches are consuming AI to identify patterns in opponents’ tactics, strengths and weaknesses while preparing for games. This helps coaches to devise detailed game plans based on their assessment of the opposition and maximise the likelihood of victory. In many leading teams, AI systems are used to constantly analyse the stream of data collected by wearables to identify the signs that are indicative of players developing musculoskeletal or cardiovascular problems. This will enable teams to maintain their most valuable assets in prime condition through long competitive seasons.

Judges

We tend to think that technology is helping us to make decisions in sports more accurate and justified. That´s why we look at the inventions such as from Paul Hawkins – creator of Hawk-Eye, a technology that is now an integral part of the spectator’s experience when watching sport live or more recently VAR in soccer.

The use of technology is allowing the decision makers to experience the game with multiple cameras angles in real-time combined with the aggregated data from various sensors (stadiums, things, and athletes) thus making them make more objective and accurate decisions.

We as spectators or fans need more transparency about the exercise’s difficulty, degree of compliance and final score. And we have the technology to do it.

The IoT and AI technology don’t claim to be infallible – just very, very reliable and judges also need to be adapted to new technologies.

Fans

Without fans, sports would find it difficult to exist. It is understandable companies are also targeting fans with IoT and AI to keep them engaged whether in the stadium or at home.

How IoT and AI will attract the audience to the stadiums?

The stadiums, sports clubs and many leagues across the globe are incorporating technologies both inside and outside the stadium areas to boost the unique experiences for fans and not only during the gameplay.

The challenge is how to combine the latest technologies with old-school stuff to please supporters from both newer and older gen. people looking forward to witnessing a game in a stadium?

How will the stadiums of the future be? I read numerous initiatives of big clubs and leagues, but I am excited about the future stadium of Real Madrid. I wish the club would allow me to advise them how to create a smart intelligent Global environment to provide each fan with an individual experience, know who is in the crowd, learn fan behaviors to anticipate their needs.

How IoT and AI will transform the Industry?

“As long as sports remain a fascination for the masses, businesses will always have the opportunity to profit from it. As long as there is profiting to be gained from the world of sports, the investment in and incorporation of technology for sports will continue.”

I went through an article warning about an entirely new world order that is being formed right now. The author explained how 9 companies are responsible for the future of AI. Three of the companies are Chinese (Baidu, Alibaba, and Tencent, often collectively referred to as BAT), while the other six are American (Google, Amazon, IBM, Facebook, Apple, and Microsoft, often referred as the G.Mafia). The reason is obvious, as far as AI is about optimisation using the data that’s available, these 9 companies will manage most of the sports data generated in the world.

Collaboration is needed now to stop this threat and to address the democratisation of AI in sports. It is important that companies and Governments around the globe work together to create guiding principles for the development and use of AI and not only in Sports. This means we need regulations but in a different way. We do not want AI power to lie only in a handful of lawmakers, renowned and smart people who lack skills in IoT and AI.

Will AI change the future of sports betting?

The impact of technology on sports cannot be specifically measured, but some technological innovations do raise questions about fairness. Are we still comparing apples with apples? Is it right to compare the speed of an athlete wearing high-tech running shoes to one without?

Whether we like it or not, technology will continue to enhance the athlete’s performance. And at some point, we will have to put specific rules and regulations in place about which tech enhancements are allowed.

There is a downside to advanced technology being introduced to sports. Nowadays, Machine Learning models are routinely used to predict the results of games. Sports betting is a competitive world itself among fans, but AI can substantially tilt that playing field.

I am afraid that IoT and AI companies may spoil the result predictions but more concerned about the manipulation of competitiveness that AI algorithms could bring with the Terabytes of data collected with IoT devices and other sources like social media networks, without the permission of the users.

The sports industry is already generating billions of dollars every year and without control and awareness, we could find the future generation of ludopaths and a small number of service providers controlling the game.

Let me know what else would you like to see in my future posts. Leave your comments below.

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Canada Denmark nationwide IoT implementation
Ecosystm Snapshot: Nationwide IoT Networks in Canada and Denmark

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In the last few weeks, there have been announcements in Canada and Denmark on nationwide IoT networks launches. Moving away from pilot projects, test cases, implementations across large factories and campuses or even citywide networks to drive smart city initiatives; these countrywide IoT networks give organisations access to lower cost means to implement large, more integrated, IoT projects.

Sigfox Canada announced the launch of Canada’s first coast to coast low-bandwidth IoT network which is the nation’s first IoT network on such a scale. The network leverages low-power wide area network (LPWAN) technology offering a capacity to support millions of IoT sensors. The solution is anticipated to provide efficient and cost-effective connectivity for businesses looking to adopt IoT technology.

Similarly, Teracom, a Denmark-based telecom operator in partnership with Loriot, (an IoT infrastructure provider) announced an IoT LoRaWAN – Long Range Wide Area Network network in Denmark. We have previously seen the Netherlands implementing a nationwide long range (LoRa) network for IoT and Singtel’s commercially available narrowband Internet of Things (NB-IoT) network in Singapore.

“There is no doubt that services like LoRaWAN will help boost early adoption of IoT services and at this stage, there is a segment of the market which is a good fit. However, the longevity of LoRaWan is less certain. Compared to LoRaWAN, NB-IOT has arguably been too late to the game and it may fail in the short term but may very well win in the long term.” says Copenhagen based Ecosystm Principal Analyst, Claus Mortensen.

Efforts are being made by both the Sigfox and Teracom to enhance the network coverage and quality in the countries. A lot of the focus on IoT in Denmark has been bundled into the future deployment of 5G. However, most IoT applications do not need high bandwidth.

“The issues with large countries such as Canada, Australia, and the US is how do you economically cover large geographic area with a very varied population density? In contrast, smaller countries like Denmark can have a mesh thrown over them very easily” says Ecosystm Executive Analyst, Vernon Turner.

With 5G though, the telecom providers appear to be in a better position as they understand that 5G will be driven by the enterprise segment in the short to medium term and they have been actively involved in developing use cases from the get-go which also includes a focus on IoT services.

IoT offers a plethora of opportunities to companies looking to adopt or expand the country-wide networks. Both mature countries and emerging economies are at dissimilar life-cycles in their degree of IoT  technology adoption but we expect to witness more technology sharing and network concatenation in the near-future.

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Verint Engage
VendorSphere: Verint’s Intelligent Virtual Assistant Experience

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I recently attended the Verint Engage event in Sydney, which had over 700 attendees. Conversations on artificial intelligence (AI) and analytics garnered a lot of attention this year. Verint showcased the deployments of intelligent conversational bots used by some of the biggest brands in Asia Pacific. Some of these customers include Spark NZ, Suncorp and AAMI. In 2018, the company acquired Next IT, a provider of conversational AI virtual assistant, to accelerate their move in the automation and analytics space. Verint’s choice of Next IT was driven by the need to provide their customers with a solution that has deep expertise in the contact centre space and to have an automation solution that is deeply integrated into their broad portfolio of solutions.

Last week, Verint announced the launch of AI Blueprint, a conversation analysis system that identifies intelligent virtual assistant (IVA) use cases and accelerates automation. The solution then delivers a “blueprint” of precisely how businesses can get started with AI or continue to grow their AI capabilities.

Verint is no stranger to the contact centre market and has an established presence in areas of quality monitoring, analytics, knowledge management and compliance.

Key Takeaways from Customers on Intelligent Virtual Assistants:

  • Engaging senior stakeholders. For a successful deployment, many organisations had to involve senior management in the discussion. These ranged from CIOs, CDOs and CEOs. The conversation around automation and AI for customer service is no longer contained within the contact centre. Many organisations spoke about having senior management involved in the pre and post launch of the virtual assistant deployment. Getting buy-in and feedback from senior management is key as the AI discussion forms part of a broader digital strategy for the organisation. The global Ecosystm AI study, which is live and ongoing, also finds that senior management is the second highest influencer for AI procurement and implementations.

  • Integrating Knowledge Management to the AI deployment is important. Organisations at the Verint Engage event highlighted that the route to a successful intelligent virtual assistant deployment is to embed knowledge management capabilities into the AI platform. By failing to incorporate knowledge management, the intelligent virtual assistant experience will be poor, leaving customers frustrated.
  • Working with a vendor that understands contact centres is key. Some of the customers at the event had worked with other well-known brands AI in the market prior to working with Verint. They moved to Verint primarily for two reasons.  One was that the cost of deployment was less on the Verint platform and secondly, they wanted to work with a vendor that not only understood AI but that had a deep understanding of the contact centre environment. Compliance, training, speech analytics, coaching and quality monitoring are core capabilities of Verint’s portfolio.  These are important elements in the overall deployment of AI.
  • Striking the right balance between automation and voice. Several of the organisations highlighted the savings realised, when the deployment was done well and fully integrated into knowledge management. Automation will in the long run help reduce contact centre calls and live chat costs. However, it was emphasised that the agent or human element remains important and cannot be ignored.  The seamless hand off to the agent when the query cannot be answered is important.

Ecosystm Comment:

Virtual assistants need to be fed with the right information to make the discussion with the customer engaging.  A solid knowledge management strategy is key to the success of a virtual assistant deployment. Without analytics and knowledge management integrated into AI, the CX will be poor leaving customers feeling frustrated. When deployed well, the virtual assistant can help answer most of the queries due to a structured knowledge bank with detailed FAQ. The ability to have it updated regularly and in real time is critical. It is important for contact centres to not rely on full automation within the contact centre.

Verint is starting to win deals in the AI and virtual assistant space with some of the largest brands in Asia Pacific. Some of the customers include those from the financial services sector. Verint’s success is not just in the intelligent virtual assistant market. It is their ability to deliver an all-encompassing solution across self-service, analytics, knowledge management, quality monitoring and compliance.

 

 

 

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IoT fueling Digital Ecosystem-to-enable-widespread-Digital-Transformation-2
Hannover Messe 2019 gives a Glimpse of Future IoT-Based Digital Exchanges

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Is the IoT fueling a Digital Ecosystem to enable widespread Digital Transformation?

Ready or not, digital transformation (DX) is here and is already revealing its impact on every aspect of our lives. In some cases, the transformation is obvious. Take the way we call for a ride-share or taxi, find a room to stay, or chat to a robot for your favourite song – these are all part of mainstream DX. More subtle examples, with a Digital Ecosystem working behind the scenes, can be found in things like checking out at the retail store without ever opening your wallet or jumping into the latest automobile and getting your directions mapped out for you.

DX is often described as the integration of digital technology into all areas of business while changing how you operate and deliver value to customers. Advancements involving cloud computing, analytics, social and mobile technologies are reshaping the customer experience (CX) and opening the door for innovation and new business services. DX is also a cultural change that requires organisations to continually experiment with new ideas while being comfortable with failure and accepting that speed has become a business imperative for everyone.

DX will fundamentally change the way we think about creating a product and how we take it to market. Gone are the days of ‘make and sell’— that is, finding a market (after the fact) for the latest bright and shiny invention or innovation and forgetting about the “thing” that’s left behind with the customer. We have flipped from building stagnant technology-for-technology’s sake, as well as having little or no real-time information about most of the product’s lifecycle, to now creating customer-centric solutions teeming with data about everything at all times.

What’s fueling this major shift? The widespread connection of things to the Internet that had never been connected before, including machine-to-machine connectivity. All thanks to embedded smart sensors making IoT an omnipresent phenomenon. By 2025 there will be over 80 billion ‘things’ connected to the Internet which in turn will provide input to feed digitally transformed companies. Industrial business models everywhere will also flip to a ‘sense and respond’ environment where customers and suppliers will know almost everything there is to know about the service or product being sold and delivered to us (within the realms of data privacy regulations).

The Emergence of the Digital Exchange

In the midst of this DX there is vast opportunity: a new customer engagement model to make things better and easier for everyone. Digital businesses cannot be built and serviced by a single supplier – it’s just too complex. There are too many new sources of IoT data that are used to feed business systems and to drive outcomes. Instead, we are seeing businesses that serve the same set of customers from consortia or digital ecosystems or digital exchanges made up of a wide range of participants with an equally wide range of talents and needs.

As more companies become digital, we expect that there will be thousands of ecosystems in existence across every industry. In this collaborative environment, companies with a mutual interest in a particular industry — sometimes crossing traditional industry lines — will join a digital exchange whereby they can openly innovate and scale their business by tapping in to a global community. Just think of the power and value of the exchange as being similar to the network effect (something like Metcalfe’s Law) whereby the more the participants engage in activities in the exchange, the more value everyone gets out of the digital exchange. Microsoft’s Satya Nadella calls this “creating more surplus outside us.”

Some of the key benefits we can expect from the digital exchange are:

  • Co-innovation between startups looking for partners and established vendors looking for external ideas for product improvement
  • Collaboration to solve like-minded industry challenges
  • Creation of open and interoperable tools to speed up new products and services offerings
  • Ability to leverage a large and diverse set of partners who can help each other discover new markets and services within their own industry and beyond

Digital exchanges can be wild and confusing, and they may seem disorganised to the newcomer. Think of the first impression you have when you walk into a large open-air market selling antiques. Initially everything seems to be piled into stalls with no logical reason. However, to the experienced shopper and stall owner, there is an organised manner to it that makes sense. And there are many wonderful things waiting to be revealed.

At this year’s Hannover Messe an original example of a digital exchange was rolled out by Schneider Electric called Schneider Electric Exchange — their digital ecosystem and business platform. Schneider Electric Exchange also has a structure to it that is geared up to help specific roles or personas and make it easier for anyone to find the right partner for solving specific business challenges. It is also set up to step someone through the life-cycle process of creating a solution by connecting them to the right tools with the right partners for the right markets. Business value can be created within the Exchange but is equally powerful outside when delivered to the end user. For example, building management designers can use Schneider Electric Exchange to find partners who are also experts of emerging technologies such as digital twins, 3D-Print, AR, and analytics.

We believe that digital exchanges will create immediate economic benefits by reducing friction and inefficiencies in the overall customer supply chain. Participants will be able to innovate faster and deliver quicker — even as customers’ experiences and expectations rise, evolve, and change at the lightning pace of the digital economy. Over time we expect that vendors’ Net Promoter Score (NPS) to rise as a result of improved business processes from these exchanges.

In conclusion, IoT will be the pebble that creates the ripple in the DX pond. Data will be created from every sensor that will be used to create competitive differences at every stage of a company’s value chain. Businesses that do not embrace the use of the data and innovate themselves as well as their products do run the risk of being very quickly disrupted. Companies also do not have the financial and technical resources to do all of this by themselves – hence, the opportunity to be part of a digital exchange is the way to be agile, cost-effective, and competitive. Every time, businesses that waited while a new ‘industrial revolution’ was taking place, lost out. Today, who will dare to disrupt instead of being disrupted? We are at the tipping point of digital transformation and there is no time left to sit on the sidelines – businesses need to jump in to a dynamic digital ecosystem and partner with each other through their industry’s digital exchange!

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AI Redefining the Banking Experience
AI Redefining the Banking Experience

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AI is powering products, processes, strategies and customer experience in the Banking industry.

The banking industry is all geared up to embrace Artificial Intelligence (AI), to address its business requirements. In general, banks are struggling to implement smart services within their compliance framework, and have an incomplete view of their customer needs from their legacy systems. However, the industry continues to be reliant on legacy systems, largely because of the involvement of too many complex platforms, technologies, and systems which make migration or integration cumbersome.

Meanwhile, modern Digital Banks are aligning their services to customer needs by embedding AI and machine learning within their existing systems. The banking industry’s experimentation with AI is opening new opportunities for improving customer experience (CX).

“We are not too far away from a day where traditional enterprise applications are no longer relevant. The purpose of those traditional systems was to simplify, codify, and automate business and customer processes. But in the mid-term future, we will have a time where the entire process is intelligent – where the system/application creates the best business process for the customer on the fly”, says Tim Sheedy, Principal Advisor, Ecosystm.

Elevating CX and Security

Banks are being transformed through AI adoption, especially in areas such as process automation, cyber security (especially in threat analysis and intelligence, and fraud/transaction security) and better information sharing systems for both their corporate and retail customers.

 Business Solutions being Addressed by AI in Banking

Business Solutions being Addressed by AI in Banking

Customer Experience

Customer Service is one of the core banking applications. Adoption of technologies such as virtual assistants and natural language processing (NLP) techniques is redefining CX in the banking industry.

“With emerging technologies setting a new bar for personalisation and value-add, banks looking to stay ahead of the curve simply cannot afford to ignore them,” says Jannat Maqbool, Principal Advisor, Ecosystm.

Personalised financial advice is another area where banks are taking advantage of AI applications. While it might be a perception that AI will reduce the human touch when it comes to CX, in reality, it provides more accurate and timely assistance. For instance, Bank of America has built an AI virtual assistant, “Erica” which actively assists 25 million clients on its mobile platform. Erica searches for past transactions and informs customers on their credit scores and connects with them to provide analytics and information on their account.

Marketing Automation

As profit margins decrease in the Banking sector, and Fintech technologies become more mainstream, banks need to ramp up their marketing initiatives, to remain competitive. AI is helping banks to optimise their marketing dollars.  Machine learning algorithms can analyse customers’ entire banking journey involving interactions, transactions, location history, and usage patterns to develop insights and make marketing decisions with unprecedented accuracy. Decisions on a range of marketing initiatives across product improvement, new products and services offerings, and targeted marketing keeping in view customers’ financial goals will be automated. This will impact the profit margin as sales cycles shorten, and customers banking journeys become more satisfying.

Process Automation

There are certain functions in banks which require a lot of manual labour such as billing, generation of reports, account opening operations, KYC, etc. AI is transforming the banking industry with data-driven processes and decision making to automate tasks such as billings, credit scoring, compliance reports and so on. This not only reduces the dependence on tedious manual processes but also creates mechanisms to reduce errors. These errors not only make the organisation less efficient but also has financial ramifications.  UBS, as an example, has introduced robots to its workforce, mainly at the back offices, designed to execute more manual and repetitive tasks. This essentially means meeting the right tasks with more speed and accuracy.

Fraud Management

AI improves with data and learns behavioural patterns. Banks are utilising this data or claims management and fraud detection. The AI platform evaluates on certain parameters such as when and how a customer typically accesses services and manage their money – more importantly, how they do not. They are designed to flag transactions with missing information and can alert the bank staff to irregular transactions and suspicious activities to prevent fraud. Increasingly this is evolving a chain of an automated process, without the involvement of banking staff or customer complaints.

Banks have a difficult job delivering better service while remaining compliant, and AI-driven AML and KYC initiatives, helps prevent fraud, and flag suspicious activities such as money laundering.

Market Trends

Current Focus on AI – The banking industry’s focus on customer service and automating manual processes is reflected in the top AI solutions that they are currently adopting. Chatbots and virtual assistants are being improved through natural language generation (NLG) and speech analytics capabilities. Process automation through RPA is being integrated into the organisations’ digital journeys due to its relative ease of deployment and measurable ROI.

Current & Planned Adoption of AI Solutions in Banking

Current & Planned Adoption of AI Solutions in Banking

Future Focus on AI – Banks will continue to focus on CX and strengthening the capabilities of their customer service team through AI. Niche solutions such as facial recognition will also improve their front-end operations, especially in customer identity authentication. Banks will also go beyond customer management to asset management, with AI-enabled IoT systems.

What’s Next?

AI is fast evolving and there are some excellent opportunities for banks to explore on what AI has to offer. Banks are working on feeding data into AI systems with advanced algorithms to better understand their customers and improve their services. Banks should focus on getting quality inputs on inquiries, interactions, transactions or another way that can collect insights.

Consumers are looking for operations and systems that are simple to operate and directed towards them. The greatest potential for AI in banking is to deliver personalised and automated services to consumers in a cost-effective and efficient way.

AI is allowing banks to do quicker operations at much lower cost, what remains to be seen is how banks further leverage AI to extend its products and services offerings.

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Automation Versus AI
Automation Versus AI – Building the Business Case for 70% Accuracy

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I ran several roundtables over the past few weeks speaking to business and technology leaders about their AI investments – and one factor came up many times – that it is hard to build a business case for AI because 70% accuracy was not good enough…

What this means is that companies have thousands of things to automate. Most of those automations in the short-medium term will deliver 100% accuracy using RPA and other simple automation tools. Every time you run that process you know the outcome.

Along Comes AI and Machine Learning

These dumb processes can now learn – they can be smart. But originally they won’t deliver 100% accuracy. They might only deliver 60-70% to start with – climbing perhaps to 90%. The benefits of these smart, learning processes can amaze – costs can fall, processes can improve, outcomes can accelerate. But traditionally we have built technology business cases delivering 100% accuracy and outcomes.

So we need a new way to think about AI and a different language to use about the way it works. The people who sign off on the business cases might not understand AI – they will come to the business case with the same lens they use for all technology investments (and evidently – all business investments). We also need to be better at selling the benefits to our leaders. CEOs and Managing Directors in the roundtables are surprised to hear that AI won’t deliver 100% accuracy – they said unless they know more about the capability, savings and outcomes that the solution might drive, they are unlikely to fund it.

Make Your Dumb Processes Smart

I take this as good news. It means we have moved beyond the hype of AI – the need to “do AI in our business” that drove many of the poorer chatbots and machine learning projects. It means that businesses review AI investments in the same way as any business investment. But it also means we can’t over-promise or under-deliver on AI. Woodside did this with their initial foray into AI, and they are still playing catch up today.

While there are many opportunities to use “dumb automation” and save money, reduce or redeploy headcount – or have employees focus on higher value activities or make real differences to customer experiences – there are as many opportunities to make dumb processes smart. Being able to automatically read PDF or paper-based invoices – processes usually done by humans – could be a huge saving for your business. OK – maybe you can’t redeploy 100% of the staff, but 70% is still a big saving. Being able to take human error out of processes will often help to save money at two steps on the process – automating the human input function up front and also getting rid of the need to fix the mistake.

Start Your AI Journey With The Low Hanging Fruit

Ecosystm’s Global Ongoing AI study has shown that most businesses are focusing their AI investments on internal initiatives – on reducing process time, cost savings and driving productivity – which makes the most sense today. They are the easier business cases to build and the easiest benefits to explain.

 

Perhaps AI is also a chance for businesses to acknowledge that “efficient” does not always mean “good”. Many of the processes we automated or coded to ensure 100% compliance don’t give customers or employees what they are looking for. And maybe making the customer happy 70% of the time is better than not making them happy at all…

If you’d like to dig deeper into Ecosystm’s reports exploring the data from our ongoing AI study – check them out here (you’ll need to register if you have not already – it is free to register, but some content is premium):

4 Vendors Emerge as Leaders: Understanding the AI Vendor landscape

Use Cases Drive AI Software Adoption: Understanding The Industry Landscape

 

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Singapore invest-more in digital-technology
Ecosystm Snapshot: Singapore to invest more in digital technology R&D

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The future of food, medicine, and digital technology has been marked as prime research targets to maintain Singapore’s competitiveness in the coming years. Recently, Singapore Government convened a panel discussion on the Research, Innovation and Enterprise (RIE) 2020 plan where Singapore’s Finance Minister Mr Heng Swee Keat delivered an update on Singapore’s science and technology research plan.

Mr. Heng conveyed that more than S$500 million is set-aside to shape up the artificial intelligence systems and to fulfill the nation’s cyber-security requirements. The fund will also improve Singapore’s supercomputing capabilities and the deployment of automation and robotics.

A further $144 million will be allocated towards food research to increase sustainable urban food production, and another $80 million will be contributed to the cell-therapy research in the biopharmaceutical sector.

How Singapore will benefit in terms of technology from this announcement?

The Government has clearly spent a lot of time to determine how to get Singaporean companies to invest in research that can benefit the country, and identifying areas that the industries can benefit in return.

Investment in Digital Technology

The Government believes that it is important to invest in the areas of Artificial Intelligence, Supercomputing and Robotics and hope that there will be more success stories for these industries.  The S$500 million set aside will aim to increase the funding already set back in the RIE 2020 for the Digital Intelligence.

Speaking on the subject, Mervyn Cheah, Principal Advisor ,Ecosystm, says that “The Government aims to entice more Industry to invest in R&D in Singapore. PM Lee has mentioned that the industry today is investing just 1.2 to 1.4 of Singapore’s GDP in R&D in Singapore, and he wants the Industry to do more. It is a bit like playing roulette you place your bets on many numbers and hope that one of them will blossom and give you the returns and success.  It is not possible that all R&D will come to fruition practically.”

Scenario for Businesses

The RIE 2020 is an initiative taken by the Singapore Government to make the nation a hub for R&D. By setting aside funds for both local industries and MNCs the government hopes that the industries will be able to invest and grow.

“There are a number of new start-ups being created as Singaporeans start to recognise that the government is putting in more R&D funding.  At the same time, existing businesses will expand to take advantage of this announcement” says Cheah.

What to Expect – RIE2020

Currently, the local Industries in Singapore do not have a large appetite for investing in R&D in Singapore although there is a 50% spike from 2016 to 2018. The government’s aim is to invest in the Science, Engineering, and Biomedical fields industries, with the intent that they can increase their revenue.

Cheah says “the Government is looking at getting Multi-national Corporations (MNCs) to invest in Singapore for their R&D and believes that the industry can do better.  So, the Government (National Research Foundation under the Prime Minister’s Office) is pushing the Industry to do more, and on their pro-active part, they have announced setting aside another S$700 million R&D funding to A*STAR, to the Singapore Food Agency, and other R&D agencies, with the hope that the Industries will further spend R&D in Singapore.”

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