Big Data Demand Signals

How Machine Learning Identifies Demand Signals Across Multiple Disparate Data Demand Sources

By Ravneet Bhandari Chief Executive Officer, LodgIQ | October 23, 2016

Big data, more than a buzzword, has by now become a conundrum that we, consumers and providers of information, try to crack and make sense of it. Essentially, we know that data is becoming larger with wider access to complex algorithms and connections. The onion metaphor – the peeling back of many layers - can be used to reflect the multifaceted aspects of machine learning technology. These swaths of data or rather layered strings of data sets turn these complex entities into a more accurate view of customer demand for the hotelier.

What is Machine Learning?

As a sub-field of computer science and artificial intelligence dealing with building systems that autonomously learn from data, machine learning allows companies to sift through remarkable amounts of information and make empowering recommendations.

Netflix utilizes it to make viewing suggestions, and Facebook uses it to populate your feed with trending video and content selections. The technology introduces mathematical modelling into the process of identifying patterns and making decisions. Then, it adapts and "learns" from all the data signals collected over time and optimizes its decision-making based on all previously inputted data.

The learning ability is what makes this technology powerful by becoming a faster and more efficient version of itself. In all, there are four types of machine learning styles, supervised, unsupervised, semi-supervised and reinforcement. The first three are all slightly different permutations of the same idea, the only major difference relates to whether there are specific desired outputs programmed in. Reinforcement learning maximizes performance though determining an ideal behavior, such as when a computer gets better at playing an opponent in an online chess match.

What's in it For the Hotelier?

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Eco-Friendly Practices: Corporate Social Responsibility

The hotel industry has undertaken a long-term effort to build more responsible and socially conscious businesses. What began with small efforts to reduce waste - such as paperless checkouts and refillable soap dispensers - has evolved into an international movement toward implementing sustainable development practices. In addition to establishing themselves as good corporate citizens, adopting eco-friendly practices is sound business for hotels. According to a recent report from Deloitte, 95% of business travelers believe the hotel industry should be undertaking “green” initiatives, and Millennials are twice as likely to support brands with strong management of environmental and social issues. Given these conclusions, hotels are continuing to innovate in the areas of environmental sustainability. For example, one leading hotel chain has designed special elevators that collect kinetic energy from the moving lift and in the process, they have reduced their energy consumption by 50%  over conventional elevators. Also, they installed an advanced air conditioning system which employs a magnetic mechanical system that makes them more energy efficient. Other hotels are installing Intelligent Building Systems which monitor and control temperatures in rooms, common areas and swimming pools, as well as ventilation and cold water systems. Some hotels are installing Electric Vehicle charging stations, planting rooftop gardens, implementing stringent recycling programs, and insisting on the use of biodegradable materials. Another trend is the creation of Green Teams within a hotel's operation that are tasked to implement earth-friendly practices and manage budgets for green projects. Some hotels have even gone so far as to curtail or eliminate room service, believing that keeping the kitchen open 24/7 isn't terribly sustainable. The May issue of the Hotel Business Review will document what some hotels are doing to integrate sustainable practices into their operations and how they are benefiting from them.