Читать книгу Big Data - Challenges for the Hospitality Industry - Michael Toedt - Страница 6

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.