Michael Toedt - Data Revolution

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.

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. 9Every two days as much digital data content as from the beginning of civilization until 2003 is created. 10According to a McKinsey study, companies with over 1,000 employees store on average 235 terabytes of data 11. 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

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. 13Overall, Facebook had 1. 23 billion users worldwide with a daily activity ratio of 62%. 14These users create about 2. 5 billion pieces of content, 2. 7 billion “Likes”, and 300 million pictures every day. 15And these are only the numbers for one single source!

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. 16Looking 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 Volume 17

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.

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

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 Map 19

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.

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. 20The smart usage of data is one of the reasons for Walmart’s success.

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