Hospitality Industry Technology Exposition & Conference
Metro Toronto Convention Centre
Toronto, ON, Canada
Hospitality Industry Technology Exposition & Conference
November 14–15, 2017
harvardbusiness.org 15 June 2017
Karim Lakhani, Harvard Business School professor and co-founder of the HBS Digital Initiative, discusses blockchain, an online record-keeping technology that many believe will revolutionize commerce. Lakhani breaks down how the technology behind bitcoin works and talks about the industries and companies that could see new growth opportunities or lose business. He also has recommendations for managers: start experimenting with blockchain as soon as possible. Lakhani is the co-author of the article “The Truth About Blockchain” in the January-February 2017 issue of Harvard Business Review.
harvardbusiness.org 15 June 2017
There are many ways to put data to work, and companies, and especially their leaders, are advised to explore as many of them as they can. Each presents distinct opportunities for profit and competitive advantage, from product improvements to new revenue streams to possible industry game changers. At the same time, each presents challenges that must be experienced to be appreciated.
harvardbusiness.org 14 June 2017
jun17-14-hbr-Neasden-Control-Centre-01Neasden Control Centre for HBR The world has more data than ever before. In fact, it's estimated that by 2020, we'll produce 44 zettabytes every day. That's equal to 44 trillion gigabytes. One gigabyte can hold the contents of enough books to cover a 30-foot-long shelf. Multiply that by 44 trillion. That's a lot of data - too much for most companies to process. And yet front-line employees are still often left operating with data that's 'too little, too late.' Most organizations are challenged to extract meaningful insights from their customer data when they're drowning in so many data feeds. Data is not always shared efficiently. Many of the world's biggest companies operate in silos - for example, their customer service and sales departments do not share a customer relationship management (CRM) database, and employees don't collaborate around the customer to ensure a powerful customer experience. More often than not, employees in one de
harvardbusiness.org 7 June 2017
Management teams often assume they can leapfrog best practices for basic data analytics by going directly to adopting artificial intelligence and other advanced technologies. But companies that rush into sophisticated artificial intelligence before reaching a critical mass of automated processes and structured analytics can end up paralyzed. They can become saddled with expensive start-up partnerships, impenetrable black-box systems, cumbersome cloud computational clusters, and open-source toolkits without programmers to write code for them.
harvardbusiness.org 31 May 2017
Today’s leading organizations are using machine learning–based tools to automate decision processes, and they’re starting to experiment with more-advanced uses of artificial intelligence (AI) for digital transformation. Corporate investment in artificial intelligence is predicted to triple in 2017, becoming a $100 billion market by 2025. Last year alone saw $5 billion in machine learning venture investment. In a recent survey, 30% of respondents predicted that AI will be the biggest disruptor to their industry in the next five years. This will no doubt have profound effects on the workplace.
harvardbusiness.org 8 May 2017
In the near future, as artificial intelligence (AI) systems become more capable, we will begin to see more automated and increasingly sophisticated social engineering attacks. The rise of AI-enabled cyberattacks is expected to cause an explosion of network penetrations, personal data thefts, and an epidemic-level spread of intelligent computer viruses. Ironically, our best hope to defend against AI-enabled hacking is by using AI. But this is very likely to lead to an AI arms race, the consequences of which may be very troubling in the long term, especially as big government actors join the cyber wars.
harvardbusiness.org 28 April 2017
In the fictional world of the video game Watch Dogs, you can play a hacktivist who takes over the central operating system of a futuristic, hyper-connected Chicago. With control over the city’s security system, you can spy on residents using surveillance cameras, intercept phone calls, and cripple the city’s critical infrastructure, unleashing a vicious cyberattack that brings the Windy City to its knees.
harvardbusiness.org 27 April 2017
Earlier this year an alarming story hit the news: Hackers had taken over the electronic key system at a luxury hotel in Austria, locking guests out of their rooms until the hotel paid a ransom. It was alarming, of course, for the guests and for anyone who ever stays at a hotel. But it came as no surprise to cybersecurity experts, who have been increasingly focused on the many ways in which physical devices connected to the internet, collectively known as the internet of things (IoT), can be hacked and manipulated. (The hotel has since announced that it is returning to using physical keys.)
harvardbusiness.org 5 April 2017
Curiosity has been hailed as one of the most critical competencies for the modern workplace. It’s been shown to boost people’s employability. Countries with higher curiosity enjoy more economic and political freedom, as well as higher GDPs. It is therefore not surprising that, as future jobs become less predictable, a growing number of organizations will hire individuals based on what they could learn, rather than on what they already know.
harvardbusiness.org 31 March 2017
There is a tendency with any new technology to believe that it requires new management approaches, new organizational structures, and entirely new personnel. That impression is widespread with cognitive technologies — which comprises a range of approaches in artificial intelligence (AI), machine learning, and deep learning. Some have argued for the creation of “chief cognitive officer” roles, and certainly many firms are rushing to hire experts with deep learning expertise. “New and different” is the ethos of the day.
harvardbusiness.org 30 March 2017
In 1900, 30 million people in the United States were farmers. By 1990 that number had fallen to under 3 million even as the population more than tripled. So, in a matter of speaking, 90% of American agriculture workers lost their jobs, mostly due to automation. Yet somehow, the 20th century was still seen as an era of unprecedented prosperity.
harvardbusiness.org 15 March 2017
According to Korn Ferry unpublished data, there has been a 74% increase in the number of CIOs serving on Fortune 100 boards in the past two years. It’s no wonder CIOs are the fastest-growing addition to the boardroom: They can help address a host of issues of crucial importance to boards, including using technologies to create operational efficiencies and competitive advantage; identifying opportunities related to cloud computing, digitization, and data; addressing threats and risks associated with information security; and using their experience and judgment to oversee, question, and provide input on technology budgets.
harvardbusiness.org 15 March 2017
Look at the modus operandi of today’s internet giants — such as Google, Facebook, Twitter, Uber, or Airbnb — and you’ll notice they have one thing in common: They rely on the contributions of users as a means to generate value within their own platforms. Over the past 20 years the economy has progressively moved away from the traditional model of centralized organizations, where large operators, often with a dominant position, were responsible for providing a service to a group of passive consumers. Today we are moving toward a new model of increasingly decentralized organizations, where large operators are responsible for aggregating the resources of multiple people to provide a service to a much more active group of consumers. This shift marks the advent of a new generation of “dematerialized” organizations that do not require physical offices, assets, or even employees.
harvardbusiness.org 1 March 2017
Our global financial system moves trillions of dollars a day and serves billions of people. But the system is rife with problems, adding cost through fees and delays, creating friction through redundant and onerous paperwork, and opening up opportunities for fraud and crime. To wit, 45% of financial intermediaries, such as payment networks, stock exchanges, and money transfer services, suffer from economic crime every year; the number is 37% for the entire economy, and only 20% and 27% for the professional services and technology sectors, respectively. It's no small wonder that regulatory costs continue to climb and remain a top concern for bankers. This all adds cost, with consumers ultimately bearing the burden. It begs the question: Why is our financial system so inefficient? First, because it's antiquated, a kludge of industrial technologies and paper-based processes dressed up in a digital wrapper. Second, because it's centralized, which makes it resistant to change and vulne
harvardbusiness.org 22 February 2017
Practitioners and pundits alike have long debated which metric is best for assessing the performance of a service organization. Is the silver bullet customer satisfaction, net promoter score, customer effort score, or some other measure? While this debate is unlikely to be settled anytime soon, we’d submit that there’s no question what the worst metric is for service: average handle time (AHT), which is principally a measure of call length, or, more simply, talk time.
harvardbusiness.org 15 February 2017
feb17-15-157640301 The booming growth of machine learning and artificial intelligence (AI), like most transformational technologies, is both exciting and scary. It's exciting to consider all the ways our lives may improve, from managing our calendars to making medical diagnoses, but it's scary to consider the social and personal implications - and particularly the implications for our careers. As machine learning continues to grow, we all need to develop new skills in order to differentiate ourselves. But which ones? It's long been known that AI and automation/robotics will change markets and workforces. Self-driving cars will force over three thousand truck drivers to seek new forms of employment, and robotic production lines like Tesla's will continue to eat away at manufacturing jobs, which are currently at 12 million and falling. But this is just the beginning of the disruption. As AI improves, which is happening quickly, a much broader set of 'thinking' rather than 'doing' j
harvardbusiness.org 25 January 2017
What is the experience of a woman in corporate America today? She probably hears a lot about diversity initiatives from the leadership of her company, but she probably has precious little to show it, save a smattering of diversity days, mentoring programs, employee advocacy groups, and other gender programs. Boards and senior leadership at her company remain stubbornly male, and women continue to earn less than men for comparable work.
harvardbusiness.org 23 December 2016
In the early days of Twilio, the cloud communications platform company where I work, the company’s founders decided that priority number one was customer empathy. That’s not unique, of course. But as a company created by developers for developers, early on we all had the job of talking to customers constantly. When the company was younger, we worked in a small office where everyone knew everything that was going on.
harvardbusiness.org 29 November 2016
The early days of artificial intelligence have been met with some very public hand wringing. Well-respected technologists and business leaders have voiced their concerns over the (responsible) development of AI. And Hollywood’s appetite for dystopian AI narratives appears to be bottomless. This is not unusual, nor is it unreasonable. Change, technological or otherwise, always excites the imagination. And it often makes us a little uncomfortable.
harvardbusiness.org 24 November 2016
Over the past few years, much has been made of the rise of big data. And yet research from TDWI states that at organizations where 50% of employees have access to business intelligence tools, only 20% of that group actually use them. Part of the problem is that systems are often hard to use. Another challenge is low rates of data literacy.
harvardbusiness.org 17 November 2016
The year 1995 was heralded as the beginning of the “New Economy.” Digital communication was set to upend markets and change everything. But economists by and large didn’t buy into the hype. It wasn’t that we didn’t recognize that something changed. It was that we recognized that the old economics lens remained useful for looking at the changes taking place. The economics of the “New Economy” could be described at a high level: Digital technology would cause a reduction in the cost of search and communication. This would lead to more search, more communication, and more activities that go together with search and communication. That’s essentially what happened.
harvardbusiness.org 11 November 2016
A hundred years ago electricity transformed countless industries; 20 years ago the internet did, too. Artificial intelligence is about to do the same. To take advantage, companies need to understand what AI can do and how it relates to their strategies. But how should you organize your leadership team to best prepare for this coming disruption? Follow history.
harvardbusiness.org 9 November 2016
Many executives ask me what artificial intelligence can do. They want to know how it will disrupt their industry and how they can use it to reinvent their own companies. But lately the media has sometimes painted an unrealistic picture of the powers of AI. (Perhaps soon it will take over the world!) AI is already transforming web search, advertising, e-commerce, finance, logistics, media, and more. As the founding lead of the Google Brain team, former director of the Stanford Artificial Intelligence Laboratory, and now overall lead of Baidu’s AI team of some 1,200 people, I’ve been privileged to nurture many of the world’s leading AI groups and have built many AI products that are used by hundreds of millions of people. Having seen AI’s impact, I can say: AI will transform many industries. But it’s not magic. To understand the implications for your business, let’s cut through the hype and see what AI really is doing today.
harvardbusiness.org 3 November 2016
Marion Barraud for HBR The term 'big data' is ubiquitous. With exabytes of information flowing across broadband pipes, companies compete to claim the biggest, most audacious data sets. And businesses of all varieties - old and new, industrial and digital, big and small - are getting into the game. Masses of social, weather, and government data are being leveraged to predict supply chain outages. Enormous amounts of user data are being harnessed at scale to identify individuals among a sea of website clicks. And companies are even starting to leverage huge quantities of text exchanges to build algorithms capable of having conversations with customers. But the reality is that our relentless focus on the importance of big data is often misleading. Yes, in some situations, deriving value from data requires having an immense amount of that data. But the key for innovators across industries is that the size of the data isn't the most critical factor
harvardbusiness.org 2 November 2016
Three years ago, our venture capital firm began studying startups in artificial intelligence. AI felt misunderstood, burdened by expectations from science fiction, and so for the last two years we’ve tried to capture the most-important startups in the space in a one-page landscape. (We prefer the more neutral term “machine intelligence” over “AI.”)
harvardbusiness.org 2 November 2016
Many alarms have sounded on the potential for artificial intelligence (AI) technologies to upend the workforce, especially for easy-to-automate jobs. But managers at all levels will have to adapt to the world of smart machines. The fact is, artificial intelligence will soon be able to do the administrative tasks that consume much of managers’ time faster, better, and at a lower cost.