In the past few months, in addition to my usual travel around the United States, I have had the pleasure of visiting both Europe and Asia to meet with customers and discuss analytics and big data. It was very interesting to me how similar the conversations were regardless of where I was in the world. Everyone wants to know what other parts of the world are doing with analytics.
In the past few months, in addition to my usual travel around the United States, I have had the pleasure of visiting both Europe and Asia to meet with customers and discuss analytics and big data. It was very interesting to me how similar the conversations were regardless of where I was in the world. Everyone wants to know what other parts of the world are doing with analytics. People always assume others are ahead of them and are doing more exciting things with data. In reality, most organizations around the world that follow a similar business model are doing the same types of analytics for the same reasons.
The fact is that math, statistics, analytics, and data don’t really speak a given language or belong to a specific culture. They are more universal in nature. A trend graph in China will look exactly the same as a trend graph in Spain. An average will be computed in India the same way as an average in Germany. A transaction record in Japan will have the same information as a transaction record in Brazil.
On top of that, businesses really are far more similar than they are different. A wireless company in Asia is providing the same services as a wireless company in North America. A retailer in Europe is providing the same services as a retailer in South America. As a result, many of the business problems are the same as well. The same business problems invariably lead to the same data and analysis needs.
The net result is that we have businesses of a similar nature around the globe capturing data of a similar nature for a similar purpose. The business problems that need addressed are also similar. So, the analytics themselves end up being very similar. It really is true that big data and analytics are global in nature.
Of course, there can be differences. Most notably, regulatory environments and cultural customs may cause deviations from the norm for a given country. Usually these deviations will be incremental, however, and won’t completely change the fundamental problems and approaches.
The moral of this story is that an organization should take comfort in the fact that its peers around the globe are solving the same problems and facing the same issues that it is. This means that terrific case studies, lessons, and best practices can be searched for more widely than many assume.
Better yet, a company on the other side of the globe is probably much happier to share information with you than one that you compete with locally. Consider setting out to befriend some peers from another country. It may be intimidating and uncomfortable at first, but once you realize how much you have in common, it will be easy for friendships and sharing to take hold.
It isn’t that I ever assumed that approaches to big data and analytics would be different around the globe. However, I never had the opportunity to interact with so many different organizations dispersed around the world in such close succession. I found myself surprised at how very similar the conversations were. It makes total sense, but it took the opportunity to experience it first hand to hammer it home for me. Hopefully this blog will help you take time to consider how you can benefit from acknowledging the global nature of analytics and big data.