Interviewer: Hello everyone, today we have invited Mr. Lai Yao to join our CDA holder interview! Yao Lai can say hello to everyone! 
Guest: Hello, I am Lai Yao, a graduate of Shanghai Lixin College of Accounting. I worked in Jingdong as a logistics data analyst, and Wallace was responsible for data analysis under the President's Office, directly responsible for the President's Office. Daily responsible for data analysis of logistics supply chain, through data analysis, optimize the whole chain link of supply chain, reduce procurement and logistics costs. I am honored to be interviewed by a CDA holder.

Question 1: I see that you have a lot of experience in data analysis in logistics industry in your work experience, what does this position do specifically? Can you give me an actual case?
Guest: Yes, I'll take a simple example from my previous work experience in Jingdong. According to the current level of big data accumulation, the sales and categories of goods in a city, a region, and specifically in each office building can be predicted.
Therefore, we can predict the next month's logistics demand, and then recruit drivers in advance, optimize logistics routes, and prepare goods in advance in the city's front warehouse.
Many people will feel that Jingdong logistics is very fast, and in first-tier cities like North China, Guangzhou and Shenzhen, orders can be placed in the morning and delivered in the afternoon after work. This is achieved through countless data analysis modeling, commodity purchase forecasting, and advance stocking of logistics front warehouses. I am based on historical purchase data, analysis of urban purchase potential, frequently purchased commodity brands, types, the purchase probability of goods in advance stock in the front warehouse. At the same time and Jingdong Mall advertising push related colleagues cooperation, according to the advertising push to predict the purchase situation, advance stocking, to achieve the morning order, the afternoon delivery of the noble service.
On the other hand, the warehouse capacity is limited, how to use the inventory in a high efficiency, and timely return of slow-moving goods to the large warehouse, are the issues we have to analyze and consider.

Question 2: Logistics supply chain management how to do a good job of data analysis? For example, how to solve the problems of inaccurate demand and difficult inventory management?
Guest: First of all, we have to admit that human management ability is limited, and only by relying on data analysis can we break through the limitations of people themselves. It is impossible for people to remember all the inventories and every entry and exit. That's why the value of data analysis was born.
To do data analysis well, we must first understand data and business, how the data is generated, what is the value behind each data, and what state it represents in reality. Changes in data correspond to changes in reality. For example, a decrease in inventory may be a sale, or it may be a stagnant return to the manufacturer.
After understanding the meaning of data and business, the problem of inaccurate demand can be solved. For example, if the boss feels that the inventory is high, before understanding the data, he has no concept of inventory and will only look at different types of inventory by category and field. After understanding the data, you can ask the boss what kind of inventory is high, why do you think the inventory is high, which categories of inventory can be adjusted, how much it costs, and why should it be adjusted? Is there a large number of promotions next, to empty the warehouse, or the current warehouse stagnant goods to be returned first? This time there is a program in the brain, it will be easy to solve.
Similarly, as long as there is enough understanding of the business, the difficulty of inventory management is also very easy to solve. With textbook standard solutions for inventory management and strong data analysis capabilities, you can put various inventory management solutions directly on the ground.

Question 3: What are some of the more popular supply chain data analytics techniques?
Guest: We are currently looking at applying cognitive technologies, such as artificial intelligence (AI), to supply chain processes. Cognitive technologies can understand, reason, learn, and interact like humans, while having the power and high speed to do so. This advanced form of supply chain analytics is leading the way to a new era of supply chain optimization. It can automatically sift through vast amounts of data to help companies improve forecasting, identify inefficiencies, better meet demand, drive innovation and pursue breakthrough ideas.

Question 4: Has your CDA certification helped you in your work?
Guest: Of course it has. Although I use a lot of data analytics knowledge and techniques in my daily work, my work is very fragmented. The process of getting the certificate helped me to sort out the knowledge of statistics and neural network, and the overall knowledge ability is more systematic, which is equivalent to sorting out the knowledge once again.
On the other hand, the ability is in place, but the enterprise may not understand your ability. The certificate itself can let enterprises understand your ability positioning again, which is still a great help to annual salary bargaining.

Question 5: The Rexel Group is the world's largest distributor of low-voltage electrical appliances, so what competencies or skills should you have if you want to receive an offer from your department (position)?
Guest: There are 2 main skills, one is the ability to quickly understand business logic, and the other is the ability to produce your own data analysis reports.
The core skill is statistics, able to handle a large amount of data, while using charts to show data, these are the skills that must be learned in the CDA must be tested. Next is programming, such as python and other data processing languages. After all, the amount of data is really large, pure excel processing, itself prone to encounter excel performance bottlenecks. The last is the data presentation, is a variety of BI reports to use, such as powerBI, FanSoft BI these data presentation and analysis software.
To do a good job of logistics information management system, the most important point is that the demand must be clear. And in the demand, the data plays a key role. For example: the amount of goods received, delivery, inventory and so on, through the depth of combination with big data to enhance the supply chain strength. The collection and analysis of user demand information, pay attention to the user experience, and achieve a full range of data value mining, thank you for sharing Lai Yao, we will see you next time!