Hello. I'm Jang Saetbyeol, News Square columnist. I will introduce you to some interesting big data use cases in several different areas. You may be familiar with the term 'big data' through the news, ads or technological trend reports you may have seen over the past few years. Some of you must be wondering about the potential of big data and perhaps want to know more about it, but it can sometimes seem like there a few opportunities to do so. To help you make sense of it all, I will share with you some interesting cases.

 Although we can look at famous cases from other industries, I think you will be better able to relate to cases that are within the scope of Amorepacific's business. I will therefore bring you to cases that transcend our business ranging from planning through production, quality control, retail, marketing and customer management and cases of both success and failure from using big data.

 And this first column will tell how big data is being used in the area of planning and production, which are the first step in any business.

 Song Gilyoung, vice president of Daumsoft who proudly calls himself a mind miner, says in his book Do Not Imagine that insight doesn't come from imagination. He strongly insists that we must see through the real desire of people that they don't tell, the real chance that's beyond our eyes. Known as one of leading big data analysts in Korea, Song has experience of supporting his words. His point is not to imagine what customers would like. Instead, observe them.

 What comes to mind when you think of being single? Someone who enjoys his/her single life, traveling abroad several times a year and having a nice brunch at high-end restaurants on weekends? Or, perhaps eats fast food most of the time, stays home and watches TV during weekends?

 In the past, many companies came up with low-priced home appliances for singles, assuming that they must be broke. For example, 'Tongkeun (meaning big-sized and generous) TV' priced at KRW 500,000. But, contrary to their expectations, singles were magnanimous enough to buy themselves a monitor at up to KRW 3 million instead of Tongkeun TV. Customers that actually showed an interest in Tongkeun TV were not singles, but married men with not a lot of money in their pocket because of many expenses.

 To give one more case of why we should observe customers, not imagine them, 'Baby Care Washer' is a near failure. This small-size washing machine designed for baby clothes came across low demand caused by a sharply decreasing birth rate. The manufacturer thought of a way to cope with the crisis and it was to target single-member family with less clothes to wash. And, at the last stage, they outsourced social media analysis; the answer they got from the analyst was not to sell. What do you think is wrong about their imagination about customers?

 Based on the observation of single-member families using social media, they found two things where they have gone wrong. First, most single-member families live in one-bedroom houses and/or serviced apartments equipped with a built-in washing machine. And, obviously they don't even consider buying washing machines, regardless of size or price. Second, the lifestyle of single-member families is very different from what they have imagined. Singles don't need to do laundry everyday, but 1-2 times a week are good enough. It means that there will be many clothes to wash in one go.

 You may have questions: why were they being so daft that they derived their own conclusion from their imagination, instead of asking customers what they need? Do we really need to use big data for the indirect observation of customers? Big data is helpful for understanding customers because it gives the answer that they might not even know. Data answers vague questions like, "What do I want?" or "What it means to be myself?"

 The graph below shows when women fix their makeup according to a study using social media. You can see women tend to do a makeup touch-up at 10:00 a.m. after getting to work, 1:00 p.m. after lunch and 4:00 p.m. before they leave the office. One question is, why do they fix their makeup at 10:00 p.m.? It is quite interesting how not one, but many people show such a similar pattern on different days. Why do you think they refresh their makeup at 10:00 p.m.?

 Data answers to the question, again this time. The reason based on the most talked-about words was, don't be surprised: selfie. This analysis clearly demonstrates the need for proper observation. Do you think you could have found 10:00 p.m., if you have asked people when they fix makeup? Or, do you think they would answer why they do it at such a late time at night? They may not be open about their reason for that because they find it a little bit awkward, or they are not aware that they even do it. It is the same with us sometimes getting surprised at 'My Recent Searches,' 'Most Searched Words' and 'Most Visited Website' provided by social media.

 That is why it's important to observe customers through data in which their behaviors and actions are recorded. Doing so helps us understand their preferences and tendencies, even those they do not know themselves.

 The number of convenience stores in Korea reached 33,000 at the end of October 2016. You must have seen many convenience stores on your way to work or near home. Now that the market is now almost saturated, the focus has shifted to customer transactions, experience and quality. And the answer to the question of how to lead customers to purchase is found in social media data – called 'buzz' – and thousands of receipts per day; it is said that a single convenience store brand makes an average of five million receipts everyday.

 As explained above, big data is now used in more traditional manufacturing business, as well as high-tech industries, for the development of new goods and services. It is especially put into good use in financial services. Korean credit card companies are striving to lure customers by using big data in the course of product development after the decrease in the number of credit cards issued since March 2014.

 In fact, Shinhan Card released new series 'Code Nine' with 18 codes, nine each for men and women based on the analysis of 22 million members and their purchasing behavior. Credit cards almost tailor-made for each customer recorded over million issues in only five months after their release and, last year, there were five million cumulative issues. This is considered a particularly successful case of using big data in the shrinking credit card market.

 More and more companies are seeking the answer as to what, when and how much they should make through data. Three years ago, the Korean TV series My Love from the Star created a sensation across Korea, China and ASEAN countries and many products enjoyed increased demand thanks to that. Among all, YSL sold a surprising number of lipsticks at 100 million a month and the key to such great success was the big data-based production system.

 YSL observed a surge in searches for its product before and after each episode was aired and, using the sales prediction model based on search trend data, it made products ready for sales. It also ran all the facilities and systems, even the systems of its partners, after it found that it would not be able to meet the demand with its usual production, retail and logistics channels. As a result, it recorded the maximum yield in the shortest time ever. It identified the sales channel through which sales were made most by considering the geographical features of different provinces across China and managing inventories in such a way that all demand would be met on time. In the end, it set a record of 100 million lipsticks sold a month, which used to be only 2,000–3,000 lipsticks per month. In fact, it sold 300 million lipsticks in three months after the first episode of the TV series was aired.

 Today, I introduced some successful cases of using big data in the area of planning and production, which together represent the beginning of the business value chain. I find it interesting how many products and services loved today have in fact been developed based on data and I hope that you all found that interesting to learn as well. I believe that if we can find the unspoken wants and needs of customers before they do, we will be able to create beauty that truly impresses and appeals to their emotions.

 In the next column, I will share more intriguing cases of big data use in connection with our business.