Data Science


   07 Apr


   05 Minutes

As we always say, Data is everywhere, and we are increasingly producing more and more of it.

The explosion in data growth has sparked a new industrial revolution, with companies taking the information and using it to build smarter services that help us understand and navigate the world around us.

Service is a product of the 21st century. In the 20th century, businesses took the world by changing it with products. There are companies that still think of themselves as builders of things and that state their gross margins, operating profits, and other measures of success solely in terms of “the product”. However, a select group of companies have already stepped forward and changed the modus operandi. For example, big technology companies such as Meta, Google, and Amazon, are building intelligence into the products themselves. In other words, they are selling services rather than anything physical. Thanks to the data insights that come from the Internet and new technologies, these companies create a whole new level of value for buyers. They achieve true intimacy with their customers.

But it’s not just these technology giants who are using data to improve processes. Businesses of all shapes and sizes have figured out how to capitalize on it by extracting the insights it contains and selling them back to us. The truth is, these data and tools are available to anyone and have never been more convenient, and nearly every business can benefit from putting them to work.

In short, the necessary technologies, while critical to the task, are well-known established by this point. This is not a dazzling future speech. Instead, in most companies, the biggest challenge is getting top management to take a fresh view of the nature of the business. Companies at the forefront of knowledge services have different views on their purpose and how to make money, but they are gradually taking this new route.

What are smart or intelligent services?

What makes them “smart” services? Well, in addition to selling us data, businesses use advanced technologies like artificial intelligence (AI) and big data analytics to extract insights from data and make our lives richer, easier, or less frictional. Thus, it creates an entirely new kind of value for customers.

For example, apart from the instantly accessible library of content they provide, Netflix and Spotify use artificial intelligence to gain a deeper understanding of their clients. They use data to learn about us to decide which TV series we’re most likely to watch and what music we might love to listen to. Likewise, Google also uses AI to gain a deeper understanding of what we’re looking for and ranks the possible results in the order we’re most likely to find them useful.

This is the basis of what is called a “smart service.” Not only is there a huge amount of data you can search to find what you need, but there are also tools and applications that can help you get the most out of them. The smartest smart services often find ways to use the data they generate to continue creating entirely new revenue streams. For example, Google and Meta’s advertising services incorporate what they’ve learned about us when searching and browsing the Internet, allowing advertisers to place ads on the home screens of people who match their customer profiles.

Any company can create intelligent services for customers

As you can see, smart services have already revolutionized many markets and industry areas. Indeed, it is difficult to imagine a business or consumer services area that would not be affected by the rise of AI and big data on the scene.

Thinking about the business opportunity associated with a networking product is a highly creative process. To find your opportunities, start by looking at your product life cycle. What actions does the customer take to acquire, own, use and dispose of it? Then check the adjacency. For each of these activities, what else is the client near or in contact with while performing this activity? Finally, after examining the opportunities offered by these different activities and neighbours, combine the most economically attractive elements into a common opportunity. Each of these steps requires further explanation.

Similarly, there are two possibilities when you look at the opportunities available to your company. Opportunities can be pursued on their own, as most elements of an opportunity can be directly related to the product life cycle. Or you need to partner with someone else, as the opportunity may be primarily adjacent. The direction you take will help you determine the type of business model you should adopt after connecting your product.

This all means that today’s innovation capabilities are the main difference between businesses and competitors when it comes to leveraging data and new technologies. In many cases, access to budget and technical skills and infrastructure is no longer an issue. This means more equal competition and more opportunities for good ideas to reach the world. This is great news for businesses and consumers!

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Did you like this post? Check this article that explains how data science is applied in the energy industry.

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