Big Data

Challenges for the
Hospitality Industry

Michael Toedt

2nd Edition

ISBN 978-3-8442-7593-3

Copyright © 2013 Michael Toedt.
All rights reserved

1st Edition April 2013
2nd Edition December 2013
by Toedt, Dr. Selk & Coll. GmbH, Munich, Germany

Text © Michael Toedt
Coverdesign: Karin Toedt

Published by epubli GmbH, Berlin, www.epubli.de

Limit of Liability/Disclaimer of Warranty: This book is designed to provide information and motivation to our readers. The publisher does not intend to render any type of psychological, legal, or any other kind of professional advice. The content of each article is the sole expression and opinion of the author, and not necessarily that of the publisher. No warranties or guarantees are given by the publisher’s choice to include any of the content in this volume. Neither the publisher nor the individual author(s) shall be liable for any physical, psychological, emotional, financial, or commercial damages, including, but not limited to, special, incidental, consequential or other damages. Our views and rights are the same: You are responsible for your own choices, actions, and results.

CONTENT

Abstract

1. Introduction

1.1. The Increasing Amount of Data

1.2. From Data to Knowledge or from Big Data to Big Insight

2. Big Data in the Hotel Industry

2.1. Pregnant Without Knowing

2.2. Data throughout the Customer Journey

2.3. The Reality

3. Changes Required

3.1. Changes within the Organizational Structure

3.2. The Central Data Ware House - The Heart of Big Data

3.3. IT Investments

3.4. Big Data and Customer Relationship Marketing (CRM)

4. Conclusion

Literature

Index

About the Author

About Toedt, Dr. Selk & Coll.

Further Publications

FIGURES

Figure 1: Search for "Big Data" on Google

Figure 2: Growth of Data Volume by the Year 2020

Figure 3: From Data to Knowledge (own image)

Figure 4: The "Hotel Customer Journey"

Figure 5: Tagging Function in the CRM Software dailypoint™

Figure 6: Areas affected by Big Data

Figure 7: Big Data Changes in Organizational Structure

Figure 8: Increase of Data in the Next Years

Figure 9: Big Data IT Architecture (own image)

Figure 10: Hotel Software Map

Figure 11: List of different IT-Systems

Figure 12: Prerequisites for CRM

Abstract

The Power of Big Data and its Influence on Daily Business

Customer Data is the salt of our modern times.

In medieval times, merchants in the Mediterranean accumulated extreme wealth by trading in spices such as salt. Nowadays, the prosperity of a company strongly correlates with its ability to manage and use customer data. Data management can help to differentiate products and services from those of competitors and thus make a company far more competitive and profitable.

Data can also be used to enhance existing and create new products and services (co-creation), to market the right services at the right time through the right channels, and to provide a personalized and individualized service at the different points of interaction and sale.

The increasing use of social media and the continuous digitalization lead to the creation of an enormous amount of data. And the data volume will grow exponentially. This phenomenon is referred to as “Big Data”.

Experts agree that the phenomenon of Big Data will have a significant impact on the structure of organizations and the way companies will work and interact with their customers. Especially since 2011, the interest in the topic is soaring. The follow figure shows the searches on Google for the topic “Big Data” since 2007.

Figure 1: Search for "Big Data" on Google[1]

Nevertheless, many managers and organizations are still not aware of this fact, or they fail to implement the changes that are required to leverage Big Data.

Due to the lack of competence and knowledge about modern marketing tools combined with insufficient IT understanding within the senior management most hotel companies fail to generate value from the enormous amount of available customer data.

Today, customer data is collected in data silos, which sit in the different departments and are not connected. In the past decade IT decisions were mainly driven by Operations and not based on an overall marketing consumer strategy.

The heart of Big Data is to provide added value to the customer. Thus, it seems logical that the marketing department should take the lead in Big Data initiatives. This, however, requires profound analytical skills and technology understanding from marketing managers, as well as additional competences and responsibilities.

The use of Big Data can positively influence the quality of marketing initiatives and interaction with customers. The quality of marketing within a Big Data environment goes beyond appealing design. It is characterized by a real-time content delivery process, which provides offers and information to the recipients based on their individual needs.

For a hotel Big Data can help to push direct distribution which can result in higher profit margins. Hotels should start using Big Data in order to counter-act the loss of business to costly third-party websites. Big Data can help to secure the competitive advantage and to increase profitability by up to 100%.

The biggest obstacles are the lack of expertise within the senior management and the reluctance to implement the necessary technical, organizational, structural and HR changes.

This book gives an evaluation of the significance of Big Data for the hospitality industry and describes the key areas for successful implementation. It is addressed to both academic researchers as well as hotel operators.

1.  Introduction

Find your Way into Big Data

1.1.  The Increasing Amount of Data

dropping storage costs and the triumphant success of social media have led to an exponentioal growth of data over the Past years.

The volume of data is increasing by 35%-50% each year. Today, companies process about 1,000 times more data than a decade ago.[2] According to a McKinsey study, companies with over 1,000 employees in fifteen out the seventeen economic sectors in the US store on average 235 terabytes of data[3]. One terabyte equals 1,024 gigabyte. The phenomenon of a constantly growing amount of data is called “Big Data”.

The volume of data is increasing by 35%-50% per year.

Facebook, one of the dominant social media players, generates 2.5 billion pieces of content, 2.7 billion “Likes” and 300 million pictures every day.[4]

90% of all available data has been generated in the past two years.

90% of all available data has been generated in the past two years. By the year 2020, available data will have increased by the factor 50 compared to 2009.[5] The following diagram shows the growth rate calculated by IDC plus a calculated exponential trend line.

Figure 2: Growth of Data Volume by the Year 2020[6]

Big Data is considered a new aspect of economy, which will take over a central part of the modern organizational theories (OT). Taylor, Weber or Fayol represent the classical approach of organizational theories where emphasis is on bureaucracy and administration. In the neoclassical approaches individual and group behaviors play a central role. The modern theories focus on organizations as systems which continuously adapt to the environmental changes. One of these modern theories is the social technical approach according to which an organization consists of people, technical systems and the environment. Big Data is an environmental change an organization has to adapt to.

McKinsey considers Big Data a new type of corporate asset.

McKinsey considers Big Data a new type of corporate asset, which will cut across all business units. It will function like a powerful brand does and thus represent a key basis for competition.[7] According to a 2012 IBM study, 1,700 marketing experts agreed that Big Data will significantly impact their work environment.[8] It is assumed that companies using Big Data will be able to increase their profit margins by up to 60%.[9] The impact on the hotel industry is considered even higher due to the expanding share of indirect bookings and the linked commission payments.

The possibility to increase profit margins should help to draw the attention of the senior management to this topic. Further benefits are the enhancement of decision-making processes as well as the qualitative improveent of products and services. The prerequisite is, however, the ability to utilize Big Data.

1.2.  From Data to Knowledge or from Big Data to Big Insight

Big Data is characterized by:

volume (huge amount of data)

velocity (data should be available almost in real-time), and

variety (structured and unstructured data from different sources has to be collected and linked).[10]

These three elements indicate the complexity of the topic but two essential aspects are missing in most Big Data definitions, which is veracity, and value.

veracity (correctness of the collected data)

 value (link of the data between the different data sources – tagging)

Cleaning and linking of data are often ignored or underestimated.

The complexity of cleaning and linking the growing amount of data, which comes from different sources, is often ignored or underestimated. Although the quality of the collected data is one of the key factors of success, the complexity of data management in general is highly underestimated[11].[12] Adriaans, Zantinge state that “without the right data there is little gold to be mined; here again, we must apply the rule ‘garbage in, garbage out”.[13]

According to a 2010 study only 40% of SAP users trust the data they have in their system, 47% have an average trust level, and 7% have no trust at all.[14] These numbers can be applied to the hotel industry.

The above figure shows the process from generating data to cleaning and analyzing it in order to generate information. The growing amount of data helps to continuously improve information about the relevant business areas. These three interrelated steps are the basis for qualitative decision-making processes, from real-time automatically triggered marketing activities to long-term strategic decisions.

Big Data can also be described by the “OODA-Loop”. OODA stands for Observe-Orient-Decide-Act. This cycle has its roots in the military, but can be easily adapted to the topic of Big Data.[15]

The concept is simple: Managers should observe the available data sets by applying analyzing models and reporting tools, then orient themselves, and take a decision based on the findings. The final action is the result of a complex and data-driven decision-making process, which reduces the risks of failure.

Data quality is one of the key factors for the successful implementation of a Big Data initiative.

2.  Big Data in the Hotel Industry

Great Opportunities for Quality Management, Service Improve-ments and Direct Distribution

2.1.  Pregnant Without Knowing

The following is a true story from outside the hotel industry and shows the power of Big Data. “Target” is a US reseller for all kinds of commodity consumer goods such as baby supplies, furniture, electronics, toys etc. Like other companies Target faces the challenge that customers usually only come to the store when they need a certain item they associate with Target. In order to increase revenues the customers had to be to convinced that Target is the only store they need. This is hard to achieve through classical advertising, as shopping habits are engrained and difficult to change. Therefore, Target started to analyze the available customer data (everything is stored under a so-called guest ID which allows the link between the customer and the purchased products) in order to create individualized marketing campaigns. The project started in 2002. By 2010 revenues had skyrocketed from US$ 44 billion in 2002 to US$ 67 billion. Of course, not all of the success can be attributed to the direct marketing activities using Big Data, but Target is doing something extremely right.[16]

Analysts at Target found out that women who purchase about 25 different products are potentially pregnant. This led to the creation of a pregnancy prediction model.

“Take a fictional Target shopper named Jenny Ward, who is 23, lives in Atlanta and in March bought cocoa-butter