Data Revolution - Michael Toedt - ebook

Data Revolution ebook

Michael Toedt

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Data is everywhere. There is no way to stop, deny or avoid it. Big Data is the next economic revolution. After the triumphant success of the Internet, the capabilities of managers to use the endless and steadily increasing amount of data will split companies into those who know what they do, and those who just guess. There will only be winners or losers. Managers need to understand that we are on the verge of a new economic era. The more they listen and learn, the higher the chance to win the data race. Why is Big Data so important? Big Data can help companies to increase their revenues, improve their profit margins, reduce risks and cut costs. Intelligent use of data supports customer acquisition, allows for higher prices, minimizes the risk of unprofitable investments, improves profit margins, supports the direct distribution channels, and helps to bypass expansive third-party vendors. It also generates customer loyalty and eventually helps to reduce technology, administration and payroll costs. There are manifold reasons to take a deeper look into Big Data. 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.

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DATA

REVOLUTION

How Big Data Will Change the Way of Doing Business

Michael Toedt (Editor.)

1st Edition

Data Revolution Michael Toedt Copyright: © 2014 Michael Toedt published by: epubli GmbH, Berlinwww.epubli.de ISBN 978-3-7375-1689-1

Contents

Introduction

Part A: Data Revolution – Michael Toedt

1. Just A Hype?

2. Big Data Stories

2. 1. The Google Flu Map

2. 2. Selling Without Owning

2. 3. Pregnant Without Knowing

2. 4. $750.000 for No Reason

3. Things You Should Know about Big Data

3. 1. The Definition of Big Data

3. 2. The ROI of Big Data

3. 3. Loyalty Programs – A Good Way to Collect Data

3. 4. Where Data Comes from – The Customer Journey

4. Big Data in the Hotel Industry

4. 1. The Reality of Hotel IT

4. 2. The Big Data Warehouse - The Heart of Big Data

5. Big Data – the Next Step in the Evolution of Marketing

5. 1. Data Security and Data Protection

5. 2. Big Data Marketing

5. 3. Communication: Content and Timing

5. 4. Communication Frequency and the Boomerang Effect

5. 4. 1. Response-Functions to Measure the Result of Marketing

5. 4. 2. How Consumers React To CRM Activities – Marketing Becomes Measureable

5. 5. The Value of Communication Channels

5. 6. The Change of Market-Research and Decision-Making

5. 7. The Social Media Pitfall

6. Changes in the Organizational Structure

7. Conclusion

Part B: Expert Views

7. Good or bad hotel customer from a sales perpective?

7. 1. Introduction

7. 2. Segmentation

7. 3. Codes

7. 4. USALI: structure of accounts

7. 5. Conclusion

8. Turn „Big Data“ Into Big Business

8. 1. Intro

8. 2. The Circle of Trust

8. 2. 1. Get Them Talking More: How to Increase Review Volume via Surveys

8. 2. 2. Making Sense of It All & Bringing Calm to the Chaos: Online Reputation Monitoring

8. 2. 3. Shout It From The Rooftops: Marketing A Hotel’s Success

8. 3. Big Brother Is Watching

8. 4. The “Hospitality Gene”

8. 4. 1. Hospitality Gene: The Beast

8. 4. 2. Hospitality Gene: The Blessing

8. 4. 3. Hospitality Gene: The Payoff

9. „Big Data“ What does Data Protection Law say?

9. 1. Introduction

9. 1. 1. A Brief Overview of Data Protection Law and „Big Data“

9. 1. 2. A Glance at the EU Provisions

9. 2. Which Law applies to Hotels in different Countries?

9. 3. The Prohibition Principle and the Separation of a Process into individual Steps

9. 4. Important

9. 5. What are the Solution Strategies?

9. 5. 1. Solution 1, Consent:

9. 5. 2. Solution 2: Waiving Personal Data

9. 6. Deleting Data & „Big Data“: an insoluble Problem?

9. 7. How does this relate to the Deletion Principle?

9. 8. What may happen in Case of Violations?

9. 9. But who is liable?

9. 10. Conclusion

10. Who cannot handle Data, successfully kills his business

10. 1. Survival of the Fittest

10. 2. Relevance matters

10. 3. Data know how as corporate asset

Index

About Michael Toedt

About Toedt, Dr. Selk & Coll.

Further Publications

Literature

Introduction

Data is everywhere. There is no way to stop, deny or avoid it. Big Data is the next economic revolution. After the triumphant success of the Internet, the capabilities of managers to use the endless and steadily increasing amount of data will split companies into those who know what they do, and those who just guess. There will only be winners or losers. Managers need to understand that we are on the verge of a new economic era. The more they listen and learn, the higher the chance to win the data race.

Why is Big Data so important? Big Data can help companies to increase their revenues, improve their profit margins, reduce risks and cut costs. Intelligent use of data supports customer acquisition, allows for higher prices, minimizes the risk of unprofitable investments, improves profit margins, supports the direct distribution channels, and helps to bypass expansive third-party vendors. It also generates customer loyalty and eventually helps to reduce technology, administration and payroll costs. There are manifold reasons to take a deeper look into Big Data.

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. In the very near future, the prosperity of a company strongly correlates with its ability to manage and use customer data. Data can be used to enhance existing and to 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 service at the different points of interaction and sale.

Huge volumes of data are generated through the increasing use of social media and smart phones, as well as the continuous digitalization. The growth is exponential. This phenomenon is referred to as Big Data.

Experts agree that the Big Data phenomenon will have a significant impact on the structure of organizations and the way companies will work and interact with their customers. Many managers and organizations are still not aware of this fact, or fail to implement the changes, which are necessary to leverage Big Data. The lack of competence and knowledge and the lack of sufficient IT skills within the senior management prevent most companies from generating value from the available assets. The data is usually collected in data silos, which sit in the different departments and are not connected at all. The reason lies in the past decade, IT decisions were mainly driven by operations and were not based on an overall consumer oriented strategy.

One central goal of Big Data is to provide added value to the customer. Thus, it seems logical that the marketing department takes the lead in Big Data initiatives. This, however, requires profound analytical and technology skills on the management level, as well as additional competencies and responsibilities. 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.

Increase of profitability by up to 100%

Big Data can help especially hotels to push direct distribution, which results in higher profit margins. Therefor, Hotels should start using Big Data in order to counter-act the loss of business to costly third-party vendors. 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 provides an evaluation of the significance of Big Data and targets managers on a senior level and everyone who is interested in this topic. Many examples help to show the current situation and to explain the changes, which are necessary to deal with the challenges associated with the current revolution of doing business – the data revolution.

Part A: Data Revolution – Michael Toedt

1. Just A Hype?

“The Internet is among the few things humans have created, but do not truly understand. It is intangible and constantly changing, growing and getting more complex with each passing second. It is a source of tremendous good and potentially dreadful evil,we are just beginning to witness on the world stage.”

Eric Schmidt, CEO of Google, wrote this in his book “The New Digital Age - Reshaping the Future of People, Nations and Business”.

By replacing the term “Internet” with “Big Data” it can be described where we are right now:

Big Data is among the few things humans have created, but do not truly understand. It is at intangible and constantly changing, growing, and getting more complex with each passing second. It is a source of tremendous good and potentially dreadful evil, we are just beginning to witness on the world stage.1

When we talk about Big Data, we talk about the steadily increasing volume of data and the opportunities, which comes with it. Critics say that Big Data is not a new topic, but only a new and trendy marketing term created by software and consulting companies. The press is full of articles and everyone talks about it. Especially since Edward Snowden Big Data has become a topic with a negative connotation. Snowden used to work for Booz Allen Hamilton, a consulting firm hired by the US National Security Agency (NSA). In June 2013, he disclosed thousands of classified documents that he acquired as an insider working for the NSA. The release of confidential NSA material was the most significant leak in US history.2 The basis for Snowden’s release was the fact that after 9/11 the NSA had started to collect data from almost everywhere. The data volumes and sources as well as the possibilities made people and governments all over the world feel insecure, and have resulted in worldwide protests against the NSA and the US government.

Since Snowden has been in the news over months Big Data has become the talk of the town. Hearing about the practices of intelligence services around the world, people started to question what companies can do with data and how this may change our lives in the future. Big Data has become a buzzword and many people talk about it without knowing much about it.

Figure 1: Google Searches on „Big Data“3

Companies have always collected data, but a lot has changed including the pace with which data is generated and collected, and the vast number of sources where data can be pulled from. Our life has become digital and without even knowing we leave our digital footprints everywhere we go. These facts have led to an exponential growth of data in the past years. The basis of Big Data is the amount of data available and the possibilities that come with it.

The technological achievements of the last decades have built the foundation for the current revolution. The development of powerful database management systems and network capabilities, decreasing costs for hardware, software and storage, the triumphant success of the Internet and its evolution through social media are responsible for the current changes. In addition to Facebook and other social media platforms, mainly the launch of the iPhone in 2007 has led to the explosion of data. The Steve Jobs and Apple achieved to revolutionariz the mobile phone market. From a more or less unemotional device with no additional functions, the mobile phone has turned into a status symbol with multi-media functions providing Internet access everywhere and at any time. This connectivity enables to collect and to use data.

Worldwide, about 1. 8 billion mobile phones have been sold in 2013, 53% of which, and growing, were Smart Phones.4 Today, even the youngest in our society - 80% of the ten to thirteen year olds and still 33% of the six to nine year olds - possess a mobile phone. It has become normal to grow up with a smart phone and a computer. No wonder that 82% of the kids under 13 are computer-savvy and almost 60% use the Internet on a daily basis.5

The triumphant success of smart phones led to the creation of billions of mobile applications, which cater to the users’ needs and provide for entertainment for all situations. The small programs are just a fingertip away and are available for almost all aspects of life. The side effect is, however, that they track and store everything the user does. Many apps are free, but actually, the user pays a price, just in a different currency. The currency is data and the price is the amount of data the app collects. The provider uses the data to learn about the user, a knowledge he will try to capitalize on in the future.

In 2012, Facebook took over Instagram a photo sharing and social media community with 30 million users at the time. The purchase price was about $1 billion,6 a ridiculous amount for a company with only 13 employees. In addition to the unique functionalities of Instagram, the motivation of Facebook for the take-over was probably a different one and most likely had something to do with the data Instagram collects with each transaction by a community member. With each picture taken the GPS coordinates and further data including date, time, and the name and type of the device with which the photo was taken, are collected. The GPS tracking tool shows on a map where the picture was taken, which is a nice and helpful feature for users.

Where this can lead to shows the following example. In summer 2014, during the Ukraine crises, however, the Russian government was at a loss to explain the following. Alexander Sotkin, a Russian soldier, took several selfies and posted them on Instragram. Against the firm assureances of Russian politicians that no Russian soldiers supported the separatists in the East-Ukraine, the map view on Instragram clearly showed that the pictures were taken on Ukraine territory.

Figure 2: Russion Soldiers in the East Ukraine reveiled by Instragram7

This example shows that some features have the potential of being more than just a technical gimmick. The GPS coordinates of pictures taken can be used for instance to gain a deeper insight into the travel habits and movement patterns of the users. This knowledge is extremely valuable for targeted communication and marketing activities. Marketing managers are willing to pay a fortune for this data, as it enables them to offer their products and services at the right time and at the right place to a relevant micro-segemented audience. The collection of data brings them closer to fulfilling this ultimate goal of marketing.

Big Data – a game changer

Is Big Data just a hype? This question is raised in almost every panel discuission. The clear answer is no. Big Data is a revolution, which comes with the massive collection of data in all life situations. The numbers are impressive and every manager should realize that a big change is happening. The question every manager needs to answer sooner or later is how he can drive value from Big Data, and what it means for him, his skills, his job, and his life?

Figure 3: What happens today?8

The figure above indicates what is happening around us on a single day in July 2014. Almost 3 billion internet users were online, 95 billion emails were sent, 1. 6 million blogs were written and 292 million Tweets were sent. This, however, just reflects a very small portion of the overall data volume.

Every year, the volume of digital data increases by 35-50%. Companies process about 1,000 times more data than a decade ago.9 Every two days as much digital data content as from the beginning of civilization until 2003 is created.10 According to a McKinsey study, companies with over 1,000 employees store on average 235 terabytes of data11. One terabyte equals 1,024 gigabyte. Since bytes are abstract to many people, the following numbers put it into the right perspective. In 2000, about 25% of all information worldwide was available digitally; this number had soared to almost 98% in 2013. 12

The Volume of Data is Increasing by 35-50% Per Year

In January 2014, Facebook, one of the main social media players, counted approx. 27 million users in Germany, compared to approx. 5 million four years earlier. 13 Overall, Facebook had 1. 23 billion users worldwide with a daily activity ratio of 62%.14 These users create about 2. 5 billion pieces of content, 2. 7 billion “Likes”, and 300 million pictures every day.15 And these are only the numbers for one single source!

90% of All Data has been Generated in the Past Two Years

It is hard to believe but 90% of all data available worldwide has been generated in the past two years. By the end of 2020, the available data will have increased by the factor 50, compared to 2009. 16 Looking at these numbers one thing is for sure: the current development of Big Data cannot be stopped and Big Data is not just hype.

Figure 4: Exponential Growth of Data Volume17

We are still in the early stages of the Big Data Revolution and companies and managers still have some time to prepare themselves. This will be completely different in five years from now. Consumers will have the choice and there will be a natural clearing of the market.

Existing global players will disappear and new ones will take over. Like Kodak denied the role of digital photo´s may companies will loose the change process. Big Data will act like a catalysator for managers who are not willing to adapt the necessary changes.

2. Big Data Stories

The following true stories will help to get a glimpse of what data is able to deliver and will lift any doubts that we already live in a digital Big Data world. Schoenberger and Cukier wrote in their NY Times Bestseller, “Big Data refers to things one can do at a large scale that cannot be done at a smaller one, to extract new insights or create new forms of value, in ways that change markets, organizations, the relationship between citizens and governments, and more.“18

2. 1. The Google Flu Map

Google is the dominant search engine. Data is their core business. A good example for what Big Data is able to deliver is the so-called Google Flu Map. By analyzing search queries Google realized that they are able to predict where a flu breakout will occur. Based on the number of search queries Google is able to calculate the flu activity worldwide almost in real-time.

Data analysts at Google compared query counts with traditional flu surveillance systems and found that certain search queries are popular exactly during the flu season. By counting how often these search queries occur, Google can estimate the flu frequency in different countries and regions around the world.

Figure 5: Goolge Flue Map19

Governments, phycicians, and pharmaceutical companies can react much faster on a flu breakout by using the Google Flu Map. Traditional flu surveillance systems look at the past and are therefore always behind the current situation.

2. 2. Selling Without Owning

Walmart is the largest retail company worldwide. Its annual revenue of approx. $450 billion is higher than the GDP of four-fifths of the world’s countries. The idea of Walmart was to record each single product through a system called Retail Link. With this tool, the suppliers of Walmart were able to monitor each sales transaction. Based on this knowledge Walmart forced the suppliers to take care of the stockage, i.e. they were able to outsourc the maintenance of the stockage for certain products. In that case, the supplier owns the product until the point-of-sale. This brought the financial risks down to a minimum.20 The smart usage of data is one of the reasons for Walmart’s success.

2. 3. 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 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 enables the link between the customer and the purchased products) in order to create individualized marketing campaigns. The project started in 2002. Revenues had skyrocketed from US$ 44 billion in 2002 to US$ 67 billion in 2012. Of course, not all of the success can be attributed to the direct marketing activities using Big Data, but Target is definitely doing something extremely right.21

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.

Figure 6: Traget - A “Big Data“ Success Story

“Take a fictional Target shopper named Jenny Ward, who is 23, lives in Atlanta and in March bought a cocoa-butter lotion, a purse large enough to double as a diaper bag, zinc and magnesium supplements and a bright blue rug. There’s, say, an 87 percent chance that she’s pregnant and that her delivery date is sometime in late August. What’s more, because of the data attached to her Guest ID number, Target knows how to trigger Jenny’s habits. They know that if she receives a coupon via Email, it will most likely cue her to buy online. They know that if she receives an ad in the mail on Friday, she frequently uses it on a weekend trip to the store. And they know that if they reward her with a printed receipt that entitles her to a free cup of Starbucks coffee, she’ll use it when she comes back again.”22 This is quite scary and the following true story a result of it:

“A man walked into a Target outside Minneapolis and demanded to see the manager. He was clutching coupons that had been sent to his daughter, and he was angry, according to an employee who participated in the conversation. “My daughter got this in the mail!” he said. “She’s still in high school, and you’re sending her coupons for baby clothes and cribs? Are you trying to encourage her to get pregnant?” The manager didn’t have any idea what the man was talking about. He looked at the mailer. Sure enough, it was addressed to the man’s daughter and contained advertisements for maternity clothing, nursery furniture and pictures of smiling infants. The manager apologized and then called a few days later to apologize again. On the phone, though, the father was somewhat abashed. “I had a talk with my daughter,” he said. “It turns out there’s been some activities in my house I haven’t been completely aware of. She’s due in August. I owe you an apology.”23