Bank Fraud: Using Technology to Combat Loss af Revathi Subramanian Big Data Analytics: Turning Big Data into Big Money af Frank Ohlhorst Big Data, Big Innovation: Enabling Competitive Differentiation through Business Analytics af Evan Stubbs. Using Big Data Analytics: Turning Big Data into Big Money af Jared Dean Win with Advanced Business Analytics: Creating Business Value from Your Data af Jean Paul Isson og Jesse Harriott.
Contents
Case Study from Infor: Analytics Opportunities in Operations 343
Case Study from IDeaS: Meetings and Events Revenue Management 349
Why Dynamic? 367 Appendix 4 Chapter Questions 377
As Kelly explains in this book, data is often not the sexy part of analytics. In my experience, and as Kelly describes in this book, data is the key to successfully creating a strategic analytics culture.
Acknowledgments
I also appreciate the support and inspiration from Ted Teng, a consummate #hotelieforlife whose dedication to advancing the industry and the people in it has been an inspiration to us all. I greatly value my relationship with the global team at HSMAI, who have been great advocates for the education and advancement of the hospitality industry, as well as great supporters of mine.
About the Author
Njena raziskava je bila objavljena v Cornell Hospitality Quarterly, Journal of Pricing and Revenue Management, Journal of Hospitality and Tourism Research in Journal of Service Management. Kelly je tudi avtor knjige Hotel Pricing in a Social World: Driving Value in the Digital Economy.
Building a
Strategic Analytic Culture in
Hospitality and Gaming
The difference is in the flexibility of the data structure and the speed of access to information. Resources across the organization must be empowered and incentivized to act in the best interest of the enterprise, not just their departments.
Data
Management for Hospitality
What kind of data, data visualization, and analytic capabilities does the average hotel or casino have?
Considering the volume of performance, market, user and customer generated data created on a daily basis, as the demand management map in Figure 3.14 displays, hotels are extremely high data producers. In 2016, the current trend is to convert existing historical reporting into "visuals" due to the growing influence of business intelligence solutions such as QlikView and Tableau. This of course reflects, especially in Europe, the highly fragmented and independent nature of the.
The impact of this is that most data is collected, stored and analyzed in Excel with very little focus on visualization. Analytics capabilities are typically outsourced to third-party vendors, such as prescriptive tools like Rate Shoppers or first- and second-generation predictive tools like Revenue Management Systems. However, these are typically limited to one data source or channel, too focused on historical performance as the primary driver, and used for a limited or specific subset of the organization's audience.
The average hotel or casino should be able to define a technology and distribution landscape that looks like the one in Figure 3.15, but probably looks more like the one in Figure 3.16.
When you have conversations with your clients, what kinds of capabilities tend to be on their roadmap?
However, they typically rely on data from a single source (PMS), focus only on historical performance, and are too generic to appeal to all stakeholders (commercial, operations, finance, management, ownership, asset management). What are the most sophisticated companies doing in the field of data, data visualization and analytics.
What are the most sophisticated companies doing in the area of data, data visualization, and analytics?
Where do you think the biggest opportunity for hotels and casinos is in this area? What are most companies missing out on?
Data becomes the glue of an organization, and I see it as the job of current leaders to fix that. The bigger opportunity for hotels and casinos is to implement data aggregation and analytics tools, not just to create more fancy management reports (just a by-product), but to also enable them to act on a much wider range of data sources.
How do you advise your clients to get started in this area?
The goal for the team is to review this exercise and discuss how easy it was to visualize the findings and present the data in a cross-dimensional way that immediately gains understanding and promotes action.
What kind of data should hotels and casinos focus on collecting for maximum impact?
What kind of technology would you recommend for a typical hotel and casino to support their data, data visualization, and
It is up to you to make sure that you maintain the neutrality of the data. Recently, the term "citizen data scientist" has become a popular way to describe the persona enabled by the access to data analytics I describe in this chapter. There is an interesting blog post on this topic, titled "How the Citizen Data Scientist Will Democratize Big Data," at.
Stephen Few, “Save the Pies for Dessert,” Perceptual Edge, August 2007, www .perceptualedge.com/articles/visual_business_intelligence/save_the_pies_for_. Portions of this chapter taken from Kelly McGuire, Telling a Story with Data, Hotel Business Review, www.hotelexecutive.com/business_review/3723/telling-a-story- with-data. From HSMAI Insights video series "How will revenue management look different in 2020?" www.hsmai.org/knowledge/multimedia.cfm?ItemNumber=22136.
Bernard Marr, "How the Citizen Data Scientist Will Democratize Big Data," Forbes, 1. april 2016, www.forbes.com/sites/bernardmarr howthe-citizen-data-scientist-will-democratize-big-data/#257f316e4557.
From Reactive to Proactive
Decision Making
Advanced Analytics in Action
What insights can hotels gain from review and rating data?
How important is reputation management?
Why can review and ratings data be challenging to analyze?
From your experience, what is the typical hotel or casino doing in the area of text analytics and reputation management?
What are the most sophisticated hotels and casinos doing?
The top performers on TripAdvisor and those who achieve the best results focus on reputation improvement. They have a much broader approach to guest feedback, which includes what is being said about their brand online with direct feedback from guests. Hotels get this feedback by sending customized guest satisfaction surveys—after the guest checks out, but also while the guest is still on the property—so that if there's a problem, they have time to fix it before the guest leaves.
We see organizations that make a cultural shift to become more guest-centric and ensure the right people get the right information achieve tremendous results in improving guest satisfaction and online reputation.
When you talk to hotels and casinos about reputation management and text analytics, what capabilities are they
For example, Jurys Inn operates 31 hotels in the UK and Ireland, and they have successfully created a guest-centric culture across the entire organization, which they called the Happy Guest Program, to increase the engagement of all employees. We have seen that hoteliers want to avoid information overload and only want to see feedback that is relevant to their department. Therefore, it is important to provide the ability to create custom views depending on the user's role in the organization.
For example, a household manager can use advanced text analytics to identify key concepts of cleanliness that are going up or down and, more importantly, understand why. Hoteliers also want to be able to use insights from text analytics to make forecast improvements based on factors such as seasonality. By providing the ability to analyze feedback on specific data, hoteliers can identify issues that have occurred in the past and use this information to plan and improve future periods.
Where do you think this area is headed over the next few years? What opportunities are on the horizon?
Most analysis programs extract datasets from the database, perform the "math", and then dump the datasets back into the database. For hosted solutions, you can pay all hardware and software costs up front plus an ongoing maintenance fee for the solution. Over the life of the solution, this can be significantly more than upfront software costs for an on-premises solution.
Real-time engines typically work by understanding the context of the interaction and looking up a result or analytics result that is matched with an offer or communication sent back to the guest in the moment. The action that the guest takes as a result of the interaction is recorded in the database so that future actions can be improved. You'll hear a lot more about this issue as the Internet of Things becomes mainstream, so it's important to be aware of the possibility.
The formula for the standard deviation is the square root of the sum of the variances.
Analytics for Operations
It's helpful to note which ones have the controls (light gray) and which control the guest (dark gray). The input for a queuing formula is generally the number of servers, serving time, and guest arrival pattern. The output includes the number of guests that can be served in a given time period and the length of the wait time, if any.
However, one of the biggest decisions to make is what the queue is like. Waiting guests line up at the back of the queue and are served in the order they come in. Guests check in and are given an indication of the order in which they will be served (Figure 5.7).
This is annoying for guests and makes them pay much more attention to the length of the wait. They do extensive modeling of the service process before implementing new designs or technologies. There is a reference to a white paper summarizing the discussion at the end of the chapter.
Analytics for Marketing
The way in which hospitality and gaming companies must engage their guests and patrons, as well as the opportunities to communicate the brand promise and brand value, has changed fundamentally. This means that loyalty programs must be designed with enough value to the guest that they are willing to allow this information to be collected. Many hospitality and gaming companies are working on ways to incorporate brand experiences into their loyalty programs so that guests are exposed to the brand while collecting points.
This revelation, driven by the casino's analysis of the data collected by the card program, drove their business strategy. Social data is useful at the brand level, property level, and individual guest level. Hotels and casinos can track reputation at the brand level or for an individual property.
Remember that social data is public data, so hotels and casinos can also collect reputation data from a competitive set and benchmark their reputation positions in the market, for an individual property or for a brand. .
