Data Science to Analyze Relationships between Companies
Big Data has currently become one of the newest allies to infer relationships between companies, competitors and suppliers, since the analysis of large volumes of data can reveal missing or relational aspects between different sectors within organizations, where they can complement each other.
The set of networks in which companies participate are considered as a resource for them. Each company participates in different networks and their position in them is what differentiates them. A company’s relationships behave as a resource that is at the basis of the heterogeneity that allows them to support a sustainable competitive advantage.
When we talk about Big Data we refer to datasets or combinations of data whose volume, complexity and speed of growth make it difficult to collect, manage, process or analyze them using conventional technologies and tools, such as relational databases, statistics or visualization packages, within the time required to make them useful.
With today’s most advanced Big Data tools it is possible to understand different types of business behaviors of companies in all types of industries.
Also see: “Big Data to Understand Consumer Mobility“
How can we take advantage of large volumes of information to analyze our competitors and their business relationships with suppliers or customers?
One way to identify various types of business relationships is, for example, to define the coordinates of various distribution centers, then locate them on a map and cross-reference them with mobility data on the people who move between these centers on a daily basis. By crossing and analyzing these layers of information via big data management techniques, relationships between competitors, suppliers, customers and others can be inferred.
Anonymized location data from different mobile devices can define trends over a specific period of time. The use of big data in records that cell phones generate at every moment, allows increasingly accurate estimates of the levels of traffic received by a logistics complex and then analyze their relationships with commercial establishments in the area and other distribution centers.
This is just a fragment of a business solution, which can be more detailed and in-depth, since it is possible to combine the anonymous records generated by the various mobile devices with other types of complementary information.
You may be interested in: “Big Data and Business: Answers to Unknown Questions“
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