How Much Data is Created Every Minute?

Posted by Neil Spencer

The Internet has become a place where massive amounts of information and data are being generated every day. Big data isn’t just some abstract concept created by the IT crowd, but a continually growing stream of digital activity pulsating through cables and airwaves across the world. This data never sleeps: every minute giant amounts of it are being generated from every phone, website and application across the Internet. The question: how much is created, and where does it all come from?
To put things into perspective, this infographic by DOMO breaks down the amount of data generated on the Internet every minute. YouTube users upload 48 hours of video, Facebook users share 684,478 pieces of content, Instagram users share 3,600 new photos, and Tumblr sees 27,778 new posts published. These are sites many people around the world use on a regular basis, and will continue to use in the future. The global Internet population now represents 2.1 billion people, and with every website browsed, status shared, and photo uploaded, we leave a digital trail that continually grows the hulking mass of big data. See where else big data is coming from in the infographic below

The Big Data Fairy Tale

By Roel Castelein

Fairy tales usually start with ‘Once upon a time ...' and end with ‘... And they lived long and happily ever after'. But nobody explains ‘how' the heroes live long and happily ever after. Big data (analytics) promise to transform your business, but just as in fairy tale endings, big data will not explain ‘how' to transform your organization. In my view, big data might spark some behavioral change or open people's minds, but it will not transform organizations. At best, big data evolves organizations. Let's look at the concept and a concrete example to draw conclusions.


What big data analytics does is take a bunch of data, analyze and visualize it, and then derive insights that potentially can improve your organization or business. Based on these insights the actual transformation can begin, but it requires more than just big data. Let's have a look at a classic example of data analytics; the reduction of crime in New York under Mayor Giuliani with the help of CompStat.

CompStat is a data system that maps crime geographically and in terms of emerging criminal patterns, as well as charting officer performance by quantifying criminal apprehensions. The key to success was not the data or analysis, but that the organizational management that used the data and analysis was effective. Processes, structures and accountability were setup to drive the transformation. In weekly meetings, NYPD executives met with local precinct commanders from the eight boroughs in New York to discuss the problems. They devised strategies and tactics to solve problems, reduce crime, and ultimately improve quality of life in their assigned area. CompStat tracked the results of these strategies and tactics, and whether they were successful or not. Precinct commanders were held accountable for the results.

Drawing upon my own experience, I know how difficult an organizational transformation is. Even if you have the data and the analysis that shows things need to change, it requires much more than data analysis. Let's assume that the data uncovers opportunities for improvement, either in reducing cost or in increasing revenue. The next step is to design the changes in processes, in people's roles, in org charts and in the systems. This usually entails a two pronged approach; communicate the change in org charts, processes and roles, and engrain these changes in the systems to track the change results. This tracking creates a feedback loop, necessary to manage the transformation.

Another challenge in the big data transformation message is finding the right people. Ideally the team leading the transformation needs to understand an organization's data, enriched with outside data, then know how to do data analysis, and once the results are there, strategically communicate the change to get everybody on board. Next, the transformation team needs to set up a tracking and feedback process that holds participants accountable for the transformation results. And when participants do not play along, have an escalation process in place, with the possibility for punitive measures.

In the same way that Giuliani fired one of the precinct commanders when he showed up drunk at the first CompStat meeting, big data systems require a complementary management philosophy to ensure whatever transformational insights are derived get implemented and controlled.

So, when the advertisements claim that big data will transform your business, remember that big data brings the potential for transformation, not the actual transformation. That still requires commitment and hard work, just like ‘living long and happily ever after'. That's why they are called fairy tales.

Time to Invest: Predicting What’s Next for Technology in Hospitality

Time to Invest: Predicting What’s Next for Technology in Hospitality


3/1/2012

Douglas C. Rice


One of the biggest challenges for any technology executive is predicting the landscape of toolsets and IT infrastructure that will be available in the future. If you make the right choice, today’s investments may last for 10 or even 20 years. In contrast, the wrong choice could force you to replace core elements of your systems strategy in half that time, or less.

The hospitality industry is largely a consumer of these building blocks, which include such things as network protocols (think TCP/IP), materials (silicon, copper, fiber), data protocols (SQL, ODBC), operating systems (Linux, Windows, iOS, Android), and presentation and messaging protocols (HTML, SOAP). These are not developed for hospitality; rather they serve a wide variety of consumer and business needs. The building blocks just referenced are familiar names in the industry now, but how can you determine what the building blocks of the future will be?
One of the best lessons I learned from a wise person many years ago was that if you want to predict the future, find out where the big money is being invested. In technology, this means learning where the industry giants are investing their billions in research and development (R&D) – companies like Microsoft, Intel, Apple®, Cisco, Google, Oracle, IBM and AT&T, to name just a few. When many of them invest in the same building blocks, you can count on those building blocks becoming mainstream and supportable for many years to come. If you were watching these barometers, you foresaw the end of the mainframe era. You also saw the Internet coming years before the dot-com boom began, and you anticipated the mobile app revolution.



A Window to the Future

One of the great privileges I enjoy from the vantage of running on of the hotel technology industry’s largest trade associations is frequent opportunities to see the world from the vantage point of many different industry technology leaders, including those that focus on hospitality, as well as those serving the broader technology space. HTNG’s regular face-to-face meetings of industry technology leaders offer great insights into where technology industry leaders expect to go in coming years, and how hospitality technology providers view those trends. These insights provide clues as to which investments will be future proof and which will be risks.

The Cloud

Despite that no one really even agrees on the meaning of the word, there is no question that the cloud is by far the biggest area of investment. Microsoft, Amazon, Force.com, Apple, and now even networking companies like Cisco are placing huge bets on moving complexity and cost up the wire, away from the user and into data centers where they can benefit from scalability, shared support resources and load balancing. You can argue that much of the money being spent is on marketing hype rather than technology, and there is undoubtedly some truth to that point of view. But these companies would not spend money on marketing if they didn’t expect sales, which means they expect to deliver product. We are only in the early days of the cloud revolution currently, but the amount of money these companies are spending ensures that it will catch on.
One of the most important aspects of this, from a hospitality perspective, is the development of cloud service brokerages. In an industry where the dozens of different systems controlling a hotel must be mashed together from different parties – at a minimum this includes the building owner, the management company and the franchisor – if services are going to be cloud based, there must be cloud-level interoperability. Brokerage services can be thought of as cloud-based middleware that ensure robust and reliable communication between cloud-based systems operating in different clouds. They are what will enable a cloud-based CRS running in the Force.com cloud, for example, to easily connect with a cloud-based PMS running on Microsoft Azure. They can also allow a hotel company to engage a single vendor to manage the aggregation, integration, customization and governance of cloud services. Intel is one of many companies making big investments in the cloud services brokerage arena, which by definition are independent of any single cloud services provider.
This is good news for hospitality. It holds the promise of relieving the hotel owner of responsibility for managing the operation and integration of premise-based systems, with associated costs for deployment, equipment and maintenance performed by on-site or locally based staff. There is a healthy debate as to which technology services must remain premise based to avoid major problems in the event of network outages. But the number of hotel technologies that are proving to be robust in cloud deployments – at least in parts of the world with good Internet access – are growing every year as obstacles are overcome. There is a distinct possibility that every aspect of hotel technology except for end-user devices and portions of the network infrastructure may ultimately move to the cloud.



Mobility

Turning from infrastructure to hardware, it’s hard to deny that the big money is moving to mobility. Apple may have been the first of the megacompanies to figure this out –arguably, they became a megacompany by doing so – but other giants like Samsung, Microsoft and Amazon have also been leading the charge. Tablets have not yet fully replaced PCs in business travel, but the gap is narrowing rapidly. Indeed, the form factor of notebooks is getting smaller as that of tablets gets larger. We are fast approaching the day when the difference between the two is the presence or absence of a paper-thin keyboard.

For hospitality, this creates both opportunity and challenge. Mobility gives us the ability to communicate with our guests and staff in real time. This capability can be used to both define new service models and revenue streams, and to improve existing ones. Today’s challenge is that mobility requires massive investment in wireless infrastructure and bandwidth. (More about that challenge in the third trend.)

The key takeaway for hospitality is that when you invest in user interfaces, it will typically be wise to design for mobile devices first, rather than for PCs. Certainly this is true for applications that face guests, but also for staff-facing applications where the staff is or could benefit from being mobile. This includes a large proportion of front-of-house, back-of-house and guest-facing hospitality applications.

Don’t bet on a particular operating system, the leadership in this area will change based on competitive dynamics outside the control of anyone in hospitality. Multiplatform toolsets such as HTML5 are widely supported and are becoming de facto standards for deployment of applications across multiple platforms. While not yet perfected in all environments, it’s the clear winner in overall investment by mobile operating system and device manufacturers.



Cellular Offload

Mobile devices create the need for massive bandwidth. iBAHN collects extensive data on these trends, which it has generously shared with the industry, and the data is downright scary: bandwidth requirements are roughly doubling every year, with mobile devices leading the way.

Many hotels have shortchanged the investment in upgrading bandwidth and supporting Wi-Fi infrastructure, believing that the migration of mobile devices to 4G/LTE cellular technologies will solve the problem by ultimately reducing or eliminating Wi-Fi. But a look at where the megacarriers are investing proves this assumption completely false.

Carriers such as AT&T, Verizon and Sprint realized in 2007 to 2008 that the data tsunami was coming, and there was simply not enough cellular radio spectrum for them to outrun it, even given future advances in cellular technology through LTE and beyond. Carriers such as these and their counterparts in other countries know they cannot satisfy the demand for mobile data with cellular technologies, at least not in densely populated areas. Their strategies for satisfying the need are based on moving cellular traffic to terrestrial networks – meaning Wi-Fi. Virtually all major carriers in developed countries are aggressively investing in what they call offload, meaning they are building out or gaining access to Wi-Fi networks, and enabling their devices to roam onto these networks automatically. If you have an AT&T smartphone and leave wireless enabled, and walk into a Starbucks, McDonalds, American Airlines Club room or Hilton-branded U.S. hotel, you have probably already experienced this. These few examples exemplify the economics: in congested areas, it is far cheaper for a cellular carrier to build or fund a Wi-Fi network, than to install an additional cell tower and/or buy additional spectrum.

This is good news for hotels, because it means that cellular companies have an economic reason to help fund hotel Wi-Fi networks. In New York and San Francisco, where cellular coverage is saturated, some carriers have gone so far as to offer free Wi-Fi networks to certain hotels, because it was the least expensive option for them to satisfy the needs of their customers. Hotels in less congested areas won’t get free Wi-Fi networks anytime soon, but many hotels can now find, at a minimum, willing investment partners to help offset the cost of a Wi-Fi network in return for the ability to route cellular traffic through it. In remote areas, the cellular network may be sufficient to meet consumer needs. Urban and suburban hotels are well positioned to benefit from this trend, but will need to forge appropriate alliances with carriers to do so. Over time, carriers expect roaming models to develop, enabling phones from different carriers to offload to a single Wi-Fi network, with payments to the provider of that network based on traffic volumes or other factors.

There are many risky bets in technology, but a few safe ones. When you are making decisions on investments, strive to determine the major trends, and then invest in solutions that align with those trends. If you aren’t looking at the cloud, expecting the user interface to migrate to mobile devices, or thinking about how your hotel can benefit from carrier investments in Wi-Fi, you’re probably missing the boat.



Douglas C. Rice is the executive vice president and CEO of Hotel Technology Next Generation.







www.htng.org

Information Managment Concepts

Following the behavioral science theory of management, mainly developed at Carnegie Mellon University and prominently represented by Barnard, Richard M. Cyert, March and Simon, most of what goes on in service organizations is actually decision making and information processes. The crucial factor in the information and decision process analysis is thus individuals’ limited ability to process information and to make decisions under these limitations.

According to March and Simon [1], organizations have to be considered as cooperative systems with a high level of information processing and a vast need for decision making at various levels. They also claimed that there are factors that would prevent individuals from acting strictly rational, in opposite to what has been proposed and advocated by classic theorists

Instead of using the model of the economic man, as advocated in classic theory, they proposed the administrative man as an alternative based on their argumentation about the cognitive limits of rationality.

While the theories developed at Carnegie Mellon clearly filled some theoretical gaps in the discipline, March and Simon [1] did not propose a certain organizational form that they considered especially feasible for coping with cognitive limitations and bounded rationality of decision-makers. Through their own argumentation against normative decision-making models, i.e., models that prescribe people how they ought to choose, they also abandoned the idea of an ideal organizational form.

In addition to the factors mentioned by March and Simon, there are two other considerable aspects, stemming from environmental and organizational dynamics. Firstly, it is not possible to access, collect and evaluate all environmental information being relevant for taking a certain decision at a reasonable price, i.e., time and effort [2]. In other words, following a national economic framework, the transaction cost associated with the information process is too high. Secondly, established organizational rules and procedures can prevent the taking of the most appropriate decision, i.e., that a sub-optimum solution is chosen in accordance to organizational rank structure or institutional rules, guidelines and procedures [3] [4], an issue that also has been brought forward as a major critique against the principles of bureaucratic organizations.[5]

According to the Carnegie Mellon School and its followers, information management, i.e., the organization's ability to process information, is at the core of organizational and managerial competencies. Consequently, strategies for organization design must be aiming at improved information processing capability. Jay Galbraith [6] has identified five main organization design strategies within two categories — increased information processing capacity and reduced need for information processing.

1.Reduction of information processing needs
1.Environmental management
2.Creation of slack resources
3.Creation of self-contained tasks
2.Increasing the organizational information processing capacity
1.Creation of lateral relations
2.Vertical information systems
Environmental management. Instead of adapting to changing environmental circumstances, the organization can seek to modify its environment. Vertical and horizontal collaboration, i.e. cooperation or integration with other organizations in the industry value system are typical means of reducing uncertainty. An example of reducing uncertainty in relation to the prior or demanding stage of the industry system is the concept of Supplier-Retailer collaboration or Efficient Customer Response.

Creation of slack resources. In order to reduce exceptions, performance levels can be reduced, thus decreasing the information load on the hierarchy. These additional slack resources, required to reduce information processing in the hierarchy, represent an additional cost to the organization. The choice of this method clearly depends on the alternative costs of other strategies.

Creation of self-contained tasks. Achieving a conceptual closure of tasks is another way of reducing information processing. In this case, the task-performing unit has all the resources required to perform the task. This approach is concerned with task (de-)composition and interaction between different organizational units, i.e. organizational and information interfaces.

Creation of lateral relations. In this case, lateral decision processes are established that cut across functional organizational units. The aim is to apply a system of decision subsidiarity, i.e. to move decision power to the process, instead of moving information from the process into the hierarchy for decision-making.

Investment in vertical information systems. Instead of processing information through the existing hierarchical channels, the organization can establish vertical information systems. In this case, the information flow for a specific task (or set of tasks) is routed in accordance to the applied business logic, rather than the hierarchical organization.

Following the lateral relations concept, it also becomes possible to employ an organizational form that is different from the simple hierarchical information. The Matrix organization is aiming at bringing together the functional and product departmental bases and achieving a balance in information processing and decision making between the vertical (hierarchical) and the horizontal (product or project) structure. The creation of a matrix organization can also be considered as management's response to a persistent or permanent demand for adaptation to environmental dynamics, instead of the response to episodic demands.

Source: Wikipedia