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January 25, 2017

Robots will fly planes, and humans won't be redundant

Posted by Sudip Singh (View Profile | View All Posts) at 5:40 AM

Robots will fly planes, and humans won't be redundant

The rapid convergence of operational and information technologies is decisively transforming the world of industrial production, often referred to as the Fourth Industrial Revolution. Consider the huge robotic arms in a decades-old manufacturing plant. Until recently, each arm was managed by a computer and did a simple precise pick and place task. No more. Now, thanks to plant-wide technological improvements, these robotic arms can all be connected to each other and work in tandem, completing a larger number of manufacturing tasks intelligently. To be sure, manufacturing enterprises are always learning to adapt to technological trends. But it is also a capital-intensive industry, with long life-cycles for processes. The industry is testing the promises of the Fourth Industrial Revolution where newer technology integrates with the aging infrastructure of a manufacturing facility.

It is interesting to note that in a recent survey that Infosys commissioned on AI adoption across industries, 29% of the nearly 275 respondents, in the manufacturing sector, confirmed that AI technologies have been fully deployed in their organizations, and these are also delivering up to expectations. 40% of the respondents viewed AI as being fundamental to the success of the organizations strategy.

Humans and Machines Collaborating

Those of us from the IT industry, with a focus on the manufacturing sector, will agree that while the rapid convergence of operational and information technologies is exciting, they must also be facilitated with care. My colleagues working for the retail sector can transform their business models within months, or install a store-full of beacons and sensors overnight. Industrial manufacturing, however, cannot afford a disruptive transformation like this. Being capital and machine intensive, the transformation of heavy industries has to be incremental, with minimal disruption, and measurable improvements.

In summary

In addition, the next generation of manufacturing relies heavily on earlier technological transformation to increase the life of existing infrastructure, improve productivity, and manage the retiring workforce. There exists today, a heavy dependency on individuals and original equipment manufacturers (OEMs) to maintain valuable equipment used in a factory. That is because the person maintaining the equipment is the only one who knows which component to change when a problem occurs and how to access that component. If that experienced employee were to suddenly leave, the specialized knowledge goes with him.

This dependency can be eliminated using technology. The transition would be completed when robots take over and start managing complex maintenance activities. The inherent benefits in automation include detecting parts in equipment not easily accessible to human workers. Factories would be able to get more from their existing assets with minimum disruption and downtime before retiring the assets.

Technology, is also eliminating the dependencies on specialized skills by improving operations through artificial intelligence. Still, the big question is what will happen to the human workers? Will they be displaced? The answer lies in looking back at the history of previous industrial revolutions and what followed them. The experts of todays manufacturing plants are sought-after resources when a new manufacturing plant is being set up. The smartest of the bunch will transition to new consultancy roles, rather than the predominantly operational ones. The same is true for factory workers who would be reskilled to handle the new technology that manages production.

Man Vs. Machine or Man & Machine?

The integration of human decision-making and an automated system is a complex task. Where, when, and to what extent humans and robots should both be included in the decision-making loop? Allocating functions between humans and computers is critical in defining efficient and effective system architectures. However, despite the recognition of this problem many decades ago, we've made little progress in balancing the allocation of roles. Until now, that is. Recent developments in automation has enhanced reliability, safety, payload capacity, dexterity, and flexibility, and enabled collaboration between human workers and industrial robots for manufacturing tasks that cannot be managed otherwise.

In a human-robot collaboration, the human operator controls and monitors production and the robot performs the physically strenuous work. Both contribute their specific capabilities: a decisive principle of Industry 4.0. The combination of a machines ability to conduct precise and repeatable operations with the human ability to see, feel, touch and think will increase efficiency, quality, and joint system capability to handle emergencies. The scenario I've described has created a new realm of industrial mass production and achieved significant economic and ergonomic benefits.

Robots: The Next Generation

When considering role allocation between humans and computers, it is useful to consider who or what can perform the skills and expertise-based behaviors required for a given objective and associated set of tasks. For many skill-based tasks, like flying an aircraft, automation generally outperforms humans. A new generation of intelligent industrial robots will learn from their human colleagues who will simply demonstrate the necessary actions. In other words, besides maintaining a stable trajectory on autopilot, next-generation robots will be able to take off and land a large passenger airplane, as well as taxi it to the appropriate gate.

The German robotics company KUKA has developed the first robot that is approved for human-robot collaboration. The KUKA LBR iiwa uses intelligent control technology, high-performance sensors, and state-of-the-art software technologies to enable completely new collaborative solutions in production technology. Even the most difficult tasks that have been previously performed manually can now be automated cost-effectively. The robots mobile platform, the KUKA flexFellow, can be individually deployed at whatever location and for whatever purpose, corresponding to production requirements.

The Future Belongs to Us

Organizations that will embrace advanced robotic technologies will continuously improve their top and bottom lines. How? By creating next-generation connected products and services. Automation technology will amplify the human potential to foster innovation and create exciting products.

January 20, 2017

Meeting the Youth Employment Imperative: Education and Entrepreneurship

Posted by Krishnamurthy Shankar (View Profile | View All Posts) at 2:13 PM

Meeting the Youth Employment Imperative

Global unemployment among youth is about 13 percent and the future of employment is in dire need of attention from political and business leaders. This was the prelude to an intense discussion organized by the Global Shapers, an initiative of the World Economic Forum, where I was a panelist. The discussion was part of their effort called 'Shaping Davos'. Be it Azerbaijan Hungary, Mexico or India, many countries are staring at a serious crisis of employment, not sometime in the future, but right here and now. For India, the imperative is to provide gainful employment to a large workforce that will add 1 million new people every month, for the next 20 years. Kuwait faces a similar 'youth bulge', compounded by the problem of unemployment rising with the level of education. Hungary is losing its best talent to 'permanent' brain drain.

But underneath their cultural nuances, the countries represented on the panel are grappling with the same issue - that of addressing an archaic and inadequate education system, and encouraging entrepreneurship to support the job requirement of the future. These are clearly the top two areas deserving executive attention.

The discussions on education reforms and the need for nurturing entrepreneurship have been on for decades. Unfortunately, the disparity between thought and action has perpetuated a paradigm that is no longer relevant to the aspirations of the millennials. The education system in many countries continues to value rote learning, rigid structures and conformist solutions over learning by doing, creative thinking and problem solving. One panelist observed that we are "busy creating solutions in the dark, without figuring out if they are relevant to the needs of today's youth." For instance, millennials have different aspirations from its preceding generations. For millennials, the true purpose of life is not to amass material wealth but to unleash their personal potential. So today we need to recalibrate the metrics of measuring educational success to include curiosity, creativity, thinking, empathy, collaboration and innovation. We also need to build education systems which promote lifelong learning.

Building entrepreneurship is more about creating the right culture than about providing infrastructure, systems and skills; many Governments are doing a commendable job with the latter and even private entities are setting up 'maker spaces'. It was the unanimous opinion of the panelists that the entrepreneurial spirit is a victim of culture and attitude - stability over flux, assured returns over unknown rewards, certainty over experimentation. But the biggest concern is the stigma attached to failure. One panelist quoted a popular saying that reflects the Hungarian attitude to any admission of ignorance, which goes somewhat like this, "If you stay silent you appear smarter."

We have to strike at the roots of such attitudes. A fellow speaker shared an interesting viewpoint acquired through experience: he said the antidote to fear of failure is extreme optimism, which is born when we instill resistance, persistence, and self-efficacy among young people. And the best way to do this is to connect them with role models they can identify with - typically people from their community or social milieu that they look up to.

Another point, is the need to improve the access to education and jobs for women. In India, for instance, the number of women in the rural workforce have been falling from 49% in 2005 to 36% in 2012. Hungary might sport better figures, but male dominance is very much the norm in the workplace. Gender inequality at school and work is a universal malaise that needs urgent attention.

So, who should be accountable for reforms in education? Governments no doubt, and industry to an extent. However, citizens also have a role to play - as students, parents, teachers, learners, and employers at different stages of life. They must take some responsibility for changing it. For instance, as employers, what is the criteria on which we recruit, merely good grades or on skills and merit?

These are monumental changes and difficult to implement. Finding the right direction is the most important part. Then we need to support this with the right policies, the right resources and the right execution. Here, technology can play a useful role by making education accessible to all, through mobile devices, and thus lowering the cost of education. Technology will also create the jobs of the future, and enable people to excel in them. With automation taking over an increasing number of mechanical jobs, technology will prepare the workforce to unlearn old skills and learn new ones. In doing so, it will force people to reimagine 'work'. That's a definite silver lining in the future of employment.

January 18, 2017

Data-driven Energy Ecosystems for a Sustainable Future

Posted by Rajesh K. Murthy (View Profile | View All Posts) at 2:55 AM

Data-driven Energy Ecosystems for a Sustainable Future

It is that time of the year when policy makers, business leaders and academicians meet to discuss global challenges at the World Economic Forum (WEF) Annual Meeting. Shaping the future of energy is one of the focus areas of the forum. In the context of energy, big data and digital technologies will drive new efficiencies and open up possibilities, thereby playing a pivotal role in its future. Leveraging data in newer and more advanced ways will be a fundamental driver in creating an energy ecosystem for a sustainable future. This ecosystem could be predicated on what The WEF Global Energy Architecture Performance Index Report 2016 calls the "Energy Triangle", which benchmarks energy systems against three primary goals: Economic Growth and Development, Environmental Sustainability, and Energy Access and Security. The question is, how can data-driven energy ecosystems help achieve these goals?

Economic growth and development

Economic growth, in many ways, is based on having a robust energy ecosystem that includes an appropriate mix of fossil fuels and renewables. Creating a sustainable future for such an ecosystem is often talked about in terms of increasing adoption of renewables and reducing emissions. However, I would like to emphasize another aspect of sustainability ─ a relentless focus on economic efficiency of energy. This is not just about energy savings across the utility value chain, but rather, a broad focus on efficiency across the energy spectrum - from exploration and production of Oil & Gas, to every aspect of generation, distribution, and consumption of energy.

In this context, there are critical questions that need to be addressed. How can we reduce the break-even price of oil by decreasing the cost of exploration, production and distribution, thereby reducing the impact of oil price fluctuations? How can we maximize recovery in conventional reserves, and formulate field depletion plans to extend plateau time, rationalize cost of midstream operations, and mitigate risks in energy trading? How can we reduce losses from generation to distribution? How can we optimize usage by empowering consumers and providing advanced monitoring techniques? How can we improve grid operations with better grid planning, voltage regulation, customer and field operations, and improved fault detection systems?

In summary

These perplexing questions are in some ways "use cases" for leveraging advanced digital technologies and for harnessing big data techniques. Increasing instrumentation, connected devices, rapid adoption of sensor technologies and the Internet of Things (IoT) network lead to better data collection and analysis, which in turn results in better and more efficient ways of managing demand-supply in the energy sector. The need of the hour is a well-defined and executed information and data management strategy that focuses on insightful analysis of data. Economies who adopt this - including the possibilities of predictive analytics, new frontiers in automation and big data, and advanced industrial control networks - improve their chances to strengthen a sustainable energy ecosystem.

Environmental sustainability

While energy drives economic development, it is also responsible for more than 65% of greenhouse gas emissions. The approaches to mitigating the environmental consequences of the production and consumption of fossil fuels continue to dominate discussions on climate change. Here again, data plays a pivotal role.

Rigorous data analysis drives automated environmental management systems and enables dynamic management of international environmental regulations. Further, it helps strengthen industrial safety. In this context, Infosys implements digital Environment, Health, and Safety (EHS) systems to minimize carbon footprint of organizations. Further, we are also a member of the Carbon Pricing Leadership Coalition (CPLC), an alliance of governments, corporations, and civil society to drive effective carbon pricing policy adoption and accelerate implementation.

Soil conservation and restoration with advanced chemical analysis and continuous monitoring is another area where a superior data management strategy can prove to be advantageous. Automated pollution control systems with mobile-enabled dashboards to track measurements ensure superior management of water, land and air pollution. This is another example of how digital technologies can drive a stronger energy ecosystem.

Energy access and security

Secure and reliable supply of low-cost energy holds the key to an equitable industrial and social ecosystem. A fine balance of physical, technological, societal, and regulatory elements is required to match global supply and demand. The growth of distributed generation of renewable energy has helped make progress in this direction. Needless to mention, digital technologies coupled with advanced data analytics can play a bigger role in ensuring sustainable growth and affordable energy.

With increasing adoption of smart meters, data can be leveraged to empower consumers in the context of electricity/power usage. A growing green conscience among today's power consumers, especially millennials, will make such a move very effective. Here again, there are enormous benefits to a data-driven approach. For instance, Infosys is working on employing advanced machine learning techniques to reduce errors and increase the generation efficiency for wind turbines in wind farms.

Statistical modeling and forecasting tools help eliminate functional and structural inefficiencies across energy systems. Use cases of functional modeling in oil and gas include predictive maintenance of pipelines and equipment. Further, predictive analysis can be applied to avert overload of the gridlock and outages, identify demand patterns and adapt the power generation capacity to this. In addition, renewable sources can be incorporated into the grid and managed appropriately using data. Advanced Artificial Intelligence (AI) techniques, including rules engines, can be applied to achieve optimal flow.

There is broad agreement that progressive nations need to focus on creating an energy ecosystem for a sustainable future. However, this is easier said than done - given the complexities in defining such an ecosystem. It consists of multiple sources of energy, different types of usage and consumption, different adoption levels, and different demand supply patterns - all of which stand exposed to geo-political and environmental risks, many of which are not in our control. However, a relentless focus on a data-driven approach to managing this can yield progressive benefits.

WEF always throws up intriguing questions and new answers. At WEF 2017, I am looking forward to how stakeholders will address various aspects of this complex energy ecosystem.

January 17, 2017

The Future of Consumption ─ A Closer Look

Posted by Sandeep Dadlani (View Profile | View All Posts) at 6:00 AM

Sense, Analyse, Engage: How to Successfully Monetize Your Fan Ecosystem (Part 1)

I have a friend who still has a Betamax player from the 1980s. During that decade he enjoyed picking up videos from the rental store to watch movies at home. After a while the rental store only carried tapes in the VHS format. About two decades later, the store, and many like it, closed. At that point, people were overwhelmingly choosing to order movies to watch on their DVD players.

Today, of course, that consumption mode has been largely replaced by movie streaming services. If you look at that vintage Betamax player, you will realize just how rapidly a seemingly healthy market can be disrupted. Technology has been impacting consumption - time and again.

What has changed, however, is that the new technologies are replacing not only physical labor and mundane jobs, but what our minds are capable of too. And unlike the three-decade transformation of home movie consumption, the pace and scale of technological change today is dizzying. Decades? Try months. The Internet of Things, mobility, artificial intelligence, robotics, virtual reality, augmented reality, chat-bots, sensors, and more recently, blockchain have precipitated new methods of consumption such as the sharing and the on-demand paradigms.

As organizations leverage technology to stay responsive to their customers, here are four considerations they would do well to address:

    In summary
  1. Sustainability in sourcing and producing goods:

    Catering to millennials is a double-edged sword. This youngest of consumer groups can be demanding in terms of instant gratification. But their other demands such as personalization and transparency about the provenance of the goods they buy have revolutionized the retail experience for the better. Blockchain, for example, is being embraced by a wide range of industries. To illustrate just how powerful and game-changing blockchain can be, let us take the example of the complex global fish market. With blockchain, a fisherman in Indonesia can record the date on which he caught the tuna and its quantity, and through the many trails in the global food supply chain, a shopper in the United States can, on her smart phone, verify the exact place, time, and circumstances in which the fish she is about to buy was caught. If a consumer at a supermarket can tell that the tuna was sourced irresponsibly, she won't buy it, causing a chain reaction that will impede questionable practices half a world away.

  2. Demand for an omni-channel experience:

    Bricks-and-mortar or online retail? How about both? Technology has given consumers the power to decide when, where and how they access a product. Indeed, omni-channel has become the new normal as digital natives (mostly millennials) demand insurance, banking, and retail products anytime, anywhere. The challenge for those consumer-facing enterprises is not only to figure out how best to deliver seamless services both online and in person, but also to respond to every subtle change in the fast evolving consumption patterns.

    Algorithms are recreating the retail store online through a virtual shopping assistant who makes recommendations based on past shopping history. But consider Amazon Go, a new type of grocery store, where you show up and walk around a beautifully laid out bricks-and-mortar location, pick out your food, and then walk out, while the groceries are delivered to your residence. Amazon, it seems, is leaving no stone unturned to make it fast and easy for customers. When their 30 minutes delivery through drones go into commercial operation, Amazon would have given new meaning to omni-channel. However, they are not about to stop here. Flying warehouses ("airborne fulfillment centers") are set to partner their drone delivery service, which is slated to crunch the delivery time further. So imagine sitting in a stadium, ordering a jersey and receiving the delivery before the game starts. This would definitely redefine omni-channel.

  3. Ensuring consumer privacy:

    Being able to unlock your door and turn on the climate control system in your house from your smart phone, right before you begin your drive home is a luxury offered by the Internet of Things. Yet a recent report by an international research firm, Parks Associates, reveals that 60 % American households with broadband connections are concerned about the security of smart home devices, with 45 % being very concerned. Sometimes it seems that technology, especially involving connected devices, has outpaced the ability to keep it secure. IoT will become a commercial success only when companies offer robust security measures as part of their smart home devices.

    Retailers are also on thin ice when it comes to privacy. Beacons and sensors detect when a customer enters a store and make shopping interactive through prompts and suggestions. In addition, data is also collected online. But how does a retailer use this information to offer a pleasant personalized experience with unknown quantities of information? The solution lies in ensuring transparency. Letting the consumer know when information is being collected and how it will be used, and giving him a choice to opt-in for a personalized interaction, and above all, establishing stringent security measures against hackers and data thieves.

  4. Reimagining the nature and quality of work for employees:

    With increasing automation, the question is, what will folks who are freed up as a result, do? How can they be reskilled to complement the automated tasks? A recent study on AI adoption commissioned by Infosys has revealed that for the full benefits of AI to be realized, investment in the workforce including new job creation, education, and skills development are critical areas. Majority of the respondents, 80% globally, said they will re-train and re-deploy employees with jobs impacted, and 84% plan to train employees about the benefits and use of AI.

    Of course we have positive experiences with job automation in history as well. In 1900, 40 % Americans worked the land as farmers. Today the country produces more food and grains than ever in its history, but thanks to automation, the American workforce is scattered across technology, banking, retail, healthcare, and other sophisticated sectors.

    With automation set to impact millions of jobs in the future, governments will have to take a closer look at new industries that can be developed and realign education to the new needs of these industries and technology. I see the private sector playing just as important a role here in helping governments plan the future needs of infrastructure and investment, sometimes for entire industries based on changing requirements.

And what better place for such discussions and collaborations to shape the global socio-economic agenda than WEF Davos, from where I write. This gathering of representatives from governments, corporates, start-ups, non-profits and other influencers from across the world, helps ensure a multi-stakeholder dialogue to evolve our world in a responsible and inclusive manner.

January 16, 2017

Five Ways in Which AI Is Changing Banking As We Know It

Posted by Mohit Joshi (View Profile | View All Posts) at 5:10 AM

Sense, Analyse, Engage: How to Successfully Monetize Your Fan Ecosystem (Part 1)

There was a time when every neighborhood bank in North America and Europe was acquired by or merged with a larger institution. By 2000, global mega-banks offered fewer choices to consumers looking for competitive interest rates and other services. But the too big to fail banks are now facing competition because of a resurgence of customer-friendly, local banks. There is an even bigger challenge: Technology companies have been applying for financial licenses that would allow them to enter the digital payments space.

As traditional banks grapple with the challenges posed by FinTechs, legacy constraints and traditional operational models, artificial intelligence (AI) is emerging as the savior. In a recent survey that Infosys commissioned on AI adoption across industries, 23% of the nearly 250 respondents, in the financial services sector, confirmed that AI technologies have been fully deployed in their organizations, and these are also delivering up to expectations; 47% of the respondents view AI as being fundamental to the success of the organization's strategy.

Here are five ways in which AI is changing the way banks and financial institutions are leveraging technology to engage and connect better with their customers.

  1. Intelligent digital assistants to amplify customer service

    As banking becomes an anywhere, anytime activity, Barclays chose to become even more responsive to its customers by developing an AI-enabled device to meet client's demand to transfer money. Embracing AI to simplify banking for its clients enables Barclays to offer some of the services which are staple at FinTechs.

    Then there's Nina, a Web assistant developed by Swedbank, a commercial bank serving customers across Sweden and the Baltic countries. According to officials at Swedbank, it's not uncommon for Nina to process 30,000 conversations focusing on 350 different queries each month. But the real proof of just how effective AI can be in improving customer service is that Nina had a first-contact resolution rate of 78 percent in the first three months of its operation.

  2. In summary
  3. Data-backed lending decisions

    Start-up lending platforms are opting for unconventional methods of credit score, beyond the traditional method, to lend, including information available from a person's online activities and interests. The online lender ZestFinance, which bills itself as a Big Data underwriter, utilizes advanced machine learning algorithms to price an applicant's personal credit risk. According to ZestFinance, its proprietary credit profiling system has improved the accuracy of their default predictions for one category of borrowers by 15 percentage points.

    While such P2P lending platforms are making it possible to include the traditionally unbanked population, they are also pushing traditional banks out of their comfort zones.

  4. Fraud detection through machine learning and pattern recognition

    It was five years ago (in 2012) that the prestigious trading firm Knight Capital Group had to assure its clients that all was well after a computer glitch caused a one-day loss of $440 million. Three years later, in 2015, the websites of companies as far ranging as United Airlines, the Wall Street Journal, and the New York Stock Exchange were all shut down for reasons that the institutions claimed involved maintenance. But many cybersecurity experts reckoned that the shutdowns were part of a coordinated attack.

    More recently however, banks are distinguishing themselves as places that are technologically sophisticated and capable of meeting the financial needs of digitally savvy customers, and they are doing this by putting security on top of the list. Some of the world's largest credit card issuers, HSBC and JP Morgan Chase & Co. among them, utilize AI to analyze buying patterns of their cardholders. Any anomalies are red-flagged, and preventive measures taken before a cyber-thief can do lasting damage. And it's about time too. A report by Forter and PYMNTS.com, the Global Fraud Index found that in the first quarter of 2016, $4.79 of every $100 in online transactions were considered at risk. That's up from $2.90 year-over-year.

    The answer to the cybersecurity problem, therefore, is for banks to increasingly collaborate with technology firms to identify and plug potential threats before they turn into a breach.

  5. Biometric identification through speech and image recognition

    HSBC uses biometric technology at data centers that can detect and recognize faces. There are other biometric technologies, such as retinal scans, that are becoming popular with financial institutions. Wells Fargo offers a stringent biometric authentication feature as enhanced security to their corporate clients. The solution involves the analysis of the whites of the eyes of the customer, including the unique red vein patterns before giving access to the banking app.

  6. Accelerated growth through digital channels

    While banks are turning to AI in a decisive manner to meet the needs of their consumers, they are also gearing up to address the competition from tech companies like Google and Apple, which offer payments systems. The investment bank Goldman Sachs has invested $15 million in the financial analytics company Kensho. The investment bank's analysts and arbitrageurs are able to receive real-time analytics through user-friendly dashboards and interfaces. Prior to leveraging Kensho, Goldman bankers had to spend time on researching companies and markets. Now those questions can be answered and analyzed with a couple of clicks.

    A financially-focused AI offering is Kasisto, which understands voice commands that are heavily laden with banking terms. The Web itself is where many of the most sophisticated AI-enabled banking services exist. Sites such as Betterment, FutureAdvisor (the result of investing giant Fidelity and brokerage house TD Ameritrade), Personal Capital, and WealthFront offer 'robo-advisory services' that ironically analyze data in order to offer extremely personalized wealth planning recommendations. Consumers are also finding that seamless digital connections to a bank's knowledge base can be attractive, personalized, and customized to their needs.

Throughout the financial services world, artificial intelligence, whether it is machine learning, deep learning, or a series of algorithms that can crunch an array of big data, is giving enterprises distinct strategic advantages. When a bank, brokerage house, lender, or payments system effectively uses AI, they run more efficiently and are able to connect more effectively with a segment of the population that will never be replaced by machines: their customers.

January 10, 2017

Technology Amplifiers for the Retail Customer Experience in 2017

Posted by Dinesh Bajaj (View Profile | View All Posts) at 3:53 AM

Amplify the Human Experience [Source: https://www.youtube.com/watch?v=7A7Ym09nJyo]

I find it extraordinary that shares of Amazon have a price-to-earnings ratio of 173.35. That is amazing for any stock, but Amazon's unique situation tells us something important about the retail success of the company. Especially when it comes to amplifying the customer experience. That is, investors in the stock market place a premium on Amazon's ability to innovate and make its website and associated digital devices and platforms a seamless, one-stop shop for today's plugged-in consumers. Why else would a company have such a high p/e ratio? The answer: Investors have confidence that the company will keep pushing the digital envelope.

As I prepare for the annual "Big Show" of the National Retail Federation, where Infosys is presenting a host of tech showcases, I can't help but give readers of InfyTalk a brief preview. I am constantly asked what I see as the top technologies that amplify a customer-centric retail experience. The fact is: You don't have to be a global retailing giant to harness these technologies. They are available to all, and if you are able to get the combination of technology with responsive customer strategy right, you could well be on your way to being the next big thing.

Here are my top technology bets for retail in 2017:

Big Data: Retail sales through digital channels grew by a significant 23% in 2015 and as more customers go digital and mobile, this growth trajectory will continue. As online buying increases, so does the digital footprint of customers, and it makes sense for retailers to gather data from a host of digital platforms so as to better understand their buyer. However, big data comes not without its own challenges. Some companies like Macy's have got closer to unravelling this mass of data when they were able to realize a 10 percent growth in sales, largely attributed to big data. However, analyzing millions of data points, nudging out hidden insights ─ like how weather patterns are linked to in-store buying behavior, or using data from web searches and social media conversations to predict a spike in demand for a particular product, and aligning decision making to these findings ─ is something retailers need to smoothen out.

Machine Learning and Analytics: It's well known that retailers - especially of the Big Box variety - use sensors, beacons, and wi-fi to know when a customer is either in the store or on the website, or both. One of the best developments of amassing all that consumer data is 'planogramming', which is the act of laying out a store to optimize a bricks-and-mortar experience. Retailers can work with consumer packaged goods companies to determine where, for example, their selection of laundry detergents should be displayed. And there is an organic way customers prefer to walk through a store that can be captured through machine learning and analytics. The in-store sensors and beacons relay important information about not only what she is buying, but how she progresses through the store. Websites are no different. There's a certain methodology to how each customer clicks through a site and loads items in the e-cart. Thanks to data from sensors, beacons and machine learning coupled with analytics, stores and websites can forecast inventory and experiment with pricing to improve the customer experience. To see how machine learning is being used in a highly sophisticated way, I can't help but look a little away from retail toward the transport industry. Here, Uber has effectively used machine learning on a large scale to better predict the travelling habits of its customers, improve its maps and even create algorithms for its autonomous vehicles. Retailers can definitely take a leaf out of Uber's approach.

Chat-bots: With retail online sales on the increase, combining visually rich apps and chat-bots are a great way to offer a personalized customer experience. These AI-powered bots can be integrated with sensors and message notifications to know when a customer is in the store and becomes accessible through a smartphone. Customers can chat with these animated bots, ask them where certain items are, or when a big sale is scheduled, or simply where the clothing department is located. An artificial intelligence (AI)-powered ultra-efficient chat-bot interface can reshape the way retailers do business as they work alongside human sales associates. After a particular point in the conversation, when it is clear what a customer needs, the human associate can take over from the chat-bot, and with a digital pad help a customer locate the right color or size, and afterwards -the digital device becomes a check-out kiosk too. North Face wanted to help customers on their website pick a jacket from an array of 350 options. The choice of jacket also depended on the weather and style preferred by the customer. North Face leveraged natural conversations through an intuitive, dialog-based recommendations engine to ask questions to their customers, better understand the need, deliver a highly personalized experience, and offer the most desirable set of jackets. Chat-bot technology got a huge fillip recently, when Jarvis was launched at Mark Zuckerberg's home. In all likelihood, AI chat bot assistants will truly power conversational commerce and enable customers to access a seamless omnichannel retail experience.

Blockchain: Today Millennials and gradually, the rest of the consumers as well, are becoming cognizant of the source of raw materials and manufacturing processes. The thrust is towards sustainability, and blockchain as a technology enables the development of a tamper-proof digital trail for a product. I meet more and more customers who are interested in how and where products are sourced, and today it is possible to know when, where and by whom cotton was harvested, for example; where it was warehoused; when and how it was processed; how it was transported to the garment factory; when, where and by whom the fabric was converted into a garment. A product that boasts of a fair trade, eco-neutral provenance commands higher prices and engaged customers - two things every retailer loves. Ascribe, a startup gives us a glimpse of blockchain in action as it lets artists upload their digital art, watermark the definitive version, and share it online. It simplifies the process of creators claiming intellectual property rights.

In conclusion, customers, whether millennials or not, are becoming digitally savvy and so retailers have the opportunity to capitalize on a host of AI-powered technologies to actively participate in the purchasing process and make it personal for their consumers.

January 5, 2017

Unlock The Hidden Monetization Opportunity In Online Gaming

Posted by Mohamed Anis (View Profile | View All Posts) at 1:56 PM

Online Gaming.jpg

In my last blog post, I outlined how technology can help sports related stakeholders analyze data and delve deeply into what, where, and whom to engage as the target audience. Using proprietary tools, sports event organizers can create a single e-commerce platform to target ads and personalize marketing on match day. An analysis of virtual attendance demographics means that fans get localized delivery of content across the world.

In this blog post, I'm going to discuss how technology can monetize sports making nearly every game an event to remember. Virtual attendance is an enormous development, but it is just the tip of the iceberg. Virtual gaming is now one of the most watched 'sport' in the world with events globally broadcast online and drawing millions of viewers. The 2015 League of Legends Finals, which took place at different venues across Europe, boasted a purse of some $2 million. The five-week long finals drew a total of 36 million viewers with the actual final at the Benz Arena in Berlin, drawing a peak of 14 million. The 17,000-seat capacity venue was sold out in record time. Compare these numbers with the 2014 sell-out final in Seoul, which drew more than 60,000 fans. Even real sports players are getting in on the act with the Brooklyn Nets' basketball player Jeremy Lin sponsoring his own 'e-gamer' team.

How do technology companies fit into the virtual gaming world?

In the virtual gaming world, we can now do what we have accomplished with real sports: sense, analyze, engage, and monetize. We can analyze real-time and historic player statistics and data, a player's in-game performance levels in certain situations, a player's and team's history and, of course, the fans - their digital and physical engagement and locate trends related to them during the event. With this depth of data, we can deliver rich and meaningful real-time insights to fans, gamers, sponsors, and (where allowed) betting agencies, adding value and knowledge to all stakeholders.

With more than 51.8 million players in America alone, the online fantasy sports industry expected to generate 2.6 billion in entry fees in 2015 . The leading players in America Fan Duel and Draft Kings cover many sports, but most traffic comes through the NBA, MLB and NFL games. In Europe, the Premier League's official game draws 3.5 million players with millions more playing on other unofficial platforms. With such huge numbers to engage, and vast amounts of data and history from each sport, technology can help analyze and provide rich insights and trends to the fantasy sites and sponsors. Doing so would increase the appeal for the sport and draw more fans to the platform, it will also increase revenue for the platform and 'eye balls,' if you will, for the sponsors and brands.

Number crunching the monies

To give you a sense of just how transformational technology in sports can be, let's go from online gaming into the stadium for a bit.

This illustration is of a sixth-ranked Premier League team, which focused on monetizing in-stadium game highlights and replays, through virtual reality. Here is the math:

  • Number of home matches a year: 25; match day attendance: 45,000; number of unique fans a year: 337,500; number of mobile fans a match: 1 million; number of TV fans a match: 2 million; number of engaged mobile fans at a match: 100,000
  • For the physical fan during one match, there are 4,500 buyers of the VR priced at $2.50 a match for each device, which is $281,000 over the course of one season
  • For the digital fan during one match, there are 50,000 buyers of the VR priced at $2.50 a match for each device, which is $3.1 million over the course of one season

To help sports organizers uncover newer revenue streams, Infosys uses a combination of technologies to provide services inside and outside the stadium, all on a single platform; Skava for compelling digital experience, IIP (Infosys Information Platform) for rich insights on fan behavior and game data, and Ooyala, a cloud-based video platform for smart publishing, analysis and advertising. This offering is a powerful demonstration of how fan and player experiences, and monetization models are being transformed. A case in point being our engagement with the Association of Tennis Professionals World Tour as their official strategic technology and data partner.

Locating newer monetization opportunities

The above example is that of an established sport with a global audience and fan base. But in the near future, where are the niche opportunities for monetization likely to be? I foresee them in three areas: betting, online gaming, and fantasy sports. Betting is experiencing a massive growth in innovation, excitement, and is drawing more crowds than ever before. These are regular people, not stereotypical gamblers but younger and more diverse audiences who have been brought up gaming online and have now matured into online gambling.

With players and teams alike we see a massive opportunity for data mining around past and current performance, form, aversion to weather, rivals, stadium conditions, home or away, and being able to provide a richer insight into future performance in a real-time environment. Imagine your team is playing, it is half-time, it has begun to rain, and one of your stars has used up all his penalties.

We could analyze past data along these parameters and access insights into how the team has performed in such an environment before. This can provide bookies with information to adjust their odds with greater precision. Discerning fans could have a better understanding of how the team might perform in such conditions by leveraging real-time data and thus experience a more exciting and immersive event.

In a nutshell, the aim is to entertain and engage fans, and increase revenue and insights for the club and sponsors without distracting the fans with unwanted content. We can achieve monetization by providing genuine value in the right context. The transformation of the sports ecosystem is real and is happening now, and as with any game, the stakeholders with the smartest moves are the ones who will win.

January 3, 2017

Sense, Analyze, Engage: How to Successfully Monetize Your Fan Ecosystem

Posted by Mohamed Anis (View Profile | View All Posts) at 3:30 AM

Sense, Analyse, Engage: How to Successfully Monetize Your Fan Ecosystem (Part 1)

I envy the ancient Romans. They had a world-class coliseum right in the middle of their capital city, and spent hours watching gladiators contest and chariots race. It was a great way for citizens to get away from the drudgeries of day-to-day life and enjoy the excitement. A trip to a stadium today is not much different. Except that there are jumbotrons and audio announcers vying for the attention of fans that until recently were exclusively focused on the playing field.

Broadcasters largely drive the at-home experience for sports aficionados, but in a hyper-connected world where fans are increasingly turning to tablets and large smartphone to take in a game, they have a newer opportunity to connect with this expanding market. Broadcasters offer third parties access to their viewers' attention and data, and have thus created a revenue stream through their loyal fan base.

An anachronistic mind-set and a fear of soaring technology costs dissuade many stakeholders in the sporting industry, including clubs from comprehensively digitizing their fan experience. But the reality is that technological rewards and fan satisfaction far outweigh the costs. It also has a measurable, positive impact on revenue. Why else do you think consumer-facing businesses like for example the retail industry, are developing their own chat bots that are designed to better engage consumers and nurture loyalty? According to experts, today's chat bots, instant messaging platforms, and sophisticated artificial intelligence tools can create seamless interactions between company-owned machines and customers.

Should the sports industry be any different? Absolutely not, and as we witness the gradual shift towards digitization of the fan experience and creative disruption of the sports ecosystem, it is a combination of 'sense', 'analysis' and 'engagement' that will create a robust revenue channel.

Sense, Analyze, and Engage

When I say 'sense', I refer to the ability to determine the pulse and sentiment of sports persons, fans, and sponsors. Analysis refers to deep diving into data to understand the actions of fans, and engagement refer to locating ways that were once unimaginable to connect with fans. For example, through data driven platforms and artificial intelligence. This enables sports clubs to monetize their fan experience through real-time advertisements and videos based on analysis, insights, and leaderboards, before, during, and after the event. The core aim being to constantly add value and richness to the sporting experience.

So what is the process by which technology can revolutionize and monetize sports while exciting the current fan base further? The answer lies in bringing old fans back, attracting new audiences, and creating a set of digital native fans.

Ideally, the activities around sense, analysis, and engagement should be implemented by a single provider and be accessible to fans, sponsors, and media on one easily navigable, integrated, and efficient platform. This is where solution-based IT companies like Infosys offer game-changing insights and implementations for monetizing sports in new ways. For instance, we can sense player stress, strain, and recovery with wearable technology like Whoop, or apps which offer video-based sensing. We can also sense the physical, transactional, and social traits of fans.

We can analyze the stress, strain, and recovery of players, and convert that into insights for fans. We can also analyze fans to help build profiles, create segments, and run digital marketing and monetization campaigns.

The final step before monetization is engagement. We know whom to engage (targeted to specific needs), when to engage, how to engage (which channel - app, Web, video content, physical billboards), what to engage (content, tickets, merchandise, ads), how to track results, and which players, sponsors, betting companies and betters should be in the loop.

Monetize every sports experience

This combination of sense, analysis, and engagement leads to monetization on an integrated e-commerce and socially active platform. So how can the sports ecosystem be divided and made accessible to every stakeholders needs, under a single platform? There are several ecosystems in any sport: fan, sponsors, club, advertisers, broadcasters, and gaming and betting. Each ecosystem has differing analytical and data needs.

Let's pick as an example, the fan ecosystem. Within this ecosystem, there are different zones, which can be monetized by providing the desired value-add to the fan. For example: tracking physical & digital fans (WPP, Google), engaging fans (Facebook, Twitter), club marketplace (Club website, store), in-game (merchandizing, refreshments), hyper-personalized mobile advertising and gamification (real-time games and leader boards with prizes).

A key strength of technology is that it can allow sports organizers to analyze data from various sources and delve deeply into what, where, and whom to engage in the target audience. It can tie a number of fan zones onto one e-commerce platform, create targeted ads and market based on match day and virtual attendance demographics, offer 'premium spot' auctions at different high-impact visibility points in the match, and localize delivery of content across the world.

(In my next blog post, I'll discuss some specific tools used to make nearly every sports match an event to remember.)

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