The term “Big Data” is new, first articulated in the early 2000s by industry analyst Doug Laney, when he introduced the concept of the 3Vs – volume, velocity, variety. “Volume” refers to the high amount of data currently collected by companies. “Velocity” is related to the speed with which data flows and must be treated. Finally, “Variety” is included because of the different formats available for data, coming from the most different sources. Thus, “Big Data” is a term that describes the large amount of information that surrounds a company on a day-to-day basis. The growing possibility of cloud storage facilitated the manipulation of such information, thus allowing the creation of new and more complex types of analysis.
The use of "Big Data" provides insights into the most varied areas of a company. I bring an example, from the automotive sector: by monitoring the commands used by drivers in vehicles, it is possible to understand the behavior of users and the reactions of the car, enabling the development of improvements. If the company is present on social networks and has a website, knowledge is gained about the profile of customers interested in the brand, which components are most accepted and which are the demands of the target audience. Regarding the operational part of the company, it is possible to use sensors to track the performance of machines, optimize manufacturing routines and even monitor the health and stress of employees.
In logistics, through analysis of large and complex data samples, the various parts of the Supply Chain are architected, delivering a comprehensive view of the business, highlighting the bottlenecks of the operation and enabling the use of this data to obtain better results. Among the attack points of “Big Data”, one of the main ones is the issue of route optimization. Dynamically and in real time, “Big Data” manages to generate intelligent routes that take into account the history of shipments, traffic and weather conditions, the existence of holidays or special events, the probability that the customer will be available for receipt, between others. In this way, it takes the issue of improving routes to another level, reducing fuel consumption and CO2 emissions, reducing the time spent on trips in addition to the number of vehicles used, impacting on variable transport costs, as well as on costs with labor. Not to mention the improvement in the level of service delivered to customers, who receive their purchases more quickly.
A bolder application of big data analysis is early delivery, patented in 2014 by Amazon. From the study of data that report the purchasing behavior of consumers, it is possible to predict a demand before it occurs and to take products to the end of the logistics chain, in order to reduce the delivery time in case the order happens. Buying patterns, preferences explicitly expressed in surveys or questionnaires, demographic information, search habits, wish lists are some of the data sources for this strategy to be implemented.
It is clear, therefore, that the availability, analysis and interpretation of data become a very important asset in the improvement of a company. There are many applications of "Big Data" in a company, including in the various areas of the Supply Chain, whether in communication between the links in the chain, in forecasting demand, in transportation, in inventory management, in customer segmentation, or in any other way. other. As a result, the logistics chain is transformed, becoming more transparent, in addition to being more automated, optimized and with reduced inefficiencies and risks, improving the level of service delivered to customers and reducing costs. The insights from these analyses, added to those not related to a company's logistics operation, are responsible for helping in strategic decision-making and allowing the visualization of new business opportunities, giving companies competitive advantages.
Sources:
How Big Data & Analytics Are Changing The Logistics Sector -> https://datafloq.com/read/big-data-analytics-changing-logistics-industry/4593
Big Data: Challenges and Opportunities in Logistics Systems -> https://www.researchgate.net/publication/321385181_BIG_DATA_CHALLENGES_AND_OPPORTUNITIES_IN_LOGISTICS_SYSTEMS
What is the impact of Big Data in the Transportation & Supply Chain Industries? 11 possibilities with Big Data -> https://cerasis.com/big-data-in-the-transportation/
The impact of big data on route planning -> https://www.amcsrouting.com/newsroom/blog/the-impact-of-big-data-on-route-planning/
7 ways Amazon uses Big Data to Stalk You -> https://www.investopedia.com/articles/insights/090716/7-ways-amazon-uses-big-data-stalk-you-amzn.asp
Amazon Patents “Anticipatory” Shipping — To Start Sending Stuff Before You've Bought It 'https://techcrunch.com/2014/01/18/amazon-pre-ships/
Marina Pomaleski
He has been part of the ILOS Team since 2018, working on projects focused on Logistics and Supply Chain. His experiences encompass major players in the cement, polymers and consumer goods industries, as well as retail companies. Types of projects carried out at ILOS: Transport management, transport contracting strategy, advice on the impacts of setting minimum freight levels, fleet sizing, process mapping and optimization, reduction of return rates.
