WWWH Data Science: Why use data science?

In the previous article, we learned what types of problems are a good fit for a data-science solution.

Now we will tackle the why: we will discuss the main reasons for using data science in the industry, and how companies benefit from using the power of data to improve their performance.

Data is everywhere

The digitization of information enabled contemporary companies to amass massive volumes of information about their operations and customers. This information has traditionally been analyzed and handled by human experts, but with the current volumes of data "analysis by hand" becomes impractical or in some cases impossible. This creates a need for an automated and machine-assisted analysis process.

Data science enables a company to make use of one of their most important assets: data. By leveraging data a company can quickly gain important competitive advantages and outperform its competitors. Let's discuss some of the most common reasons companies nowadays are starting to integrate data science in multiple parts of their decision-making process.

Build on top of facts, not hunches

Backing important strategic decisions on hard-data offers important competitive advantages over following 'hunches' or opinions. Understanding the direct results of your actions can let you correct the things you are doing wrong, or guide you into doing more of what you are already doing well.

Traditionally, you had to wait until a specialized team performed the number-crunching to understand the current state of the company. Well, 'current' might not be the right word because by the time you got the reports, many things had already changed. Automated data gathering and analysis let you have a clear understanding of the current state of the company without having to wait until it's too late.

Having a continuous flow of insights not only lets you make decisions before it's too late, but it also helps you evaluate the results of individual actions. As a result of applying data science to their own operational data, organizations can understand better where a company currently stands and where it's heading. This will enable the company to keep up with trends and make better decisions at a time when they matter the most.

Protecting yourself from the bad guys

In the previous article, we talked about outlier detection. Companies can use these techniques to identify fraudulent transactions or malicious attempts in real-time and assign specialized agents to investigate the problems.

The same techniques can aid security professionals to protect the company from hackers and malicious software. By detecting abnormal network behavior you can react and prevent attacks in real-time. Banks and other financial entities make heavy use of these techniques, and it has dramatically improved the security they can offer to their clients.

Turn insights into profit and customer satisfaction

Understanding consumer behavior lets you optimize profits and customer satisfaction in different ways:

  • It can uncover counterintuitive customer segments and let you adapt your offer to satisfy their demands.
  • For supporting cross-selling and offering customers items they might not know about and can benefit from.
  • Understand tendencies in purchasing patterns and stock accordingly to prevent shortages.
  • Understand relations between products customers purchase together and create your layout to put those products close to each other to motivate extra purchases.
  • Discover customer personas that let you understand how to adapt your products to satisfy their needs and wants.
  • Create marketing campaigns tailored for specific sub-segments of the userbase and automatically evaluate their performance.

Using data to power company decisions can dramatically increase a company's profitability. Using a data-driven approach lets you make the right offerings, at the right time and to the right people. It is not only important for making your current processes more efficient, but it can also uncover new market opportunities that have been hidden in the data all along.

These are just some of the most common ways to improve a company's profitability with data. Every year organizations discover new ways to use the power of data to offer better services and remain competitive in an increasingly data-driven world.

It's time to get creative

Companies that adopted a data-driven approach have started to benefit from improvements in multiple ways. What's more, there are lots of new market opportunities for the application of data science, some of them incredibly profitable (Google is basically a data-driven advertisement company).

If you are the owner of a business, there are lots of open opportunities in the data you've been collecting. If you are a developer or a person interested in data science, there is a lot of profit to make in a world flooding with data. In the following years, businesses will continue extracting value from their data in ways currently we can't even start to imagine. The demand is high, and the opportunities almost endless.

Now that we understand why companies care about data science, let's talk about the final topic of the series: how can you apply data science to generate value? The next article will outline the typical lifecycle of a data science project.

What to do next

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  • This series on the MIT Essential Knowledge series books on data science and machine learning. These and other very helpful books can be found in the recommended reading list.
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Budapest, Hungary
Hey there, I'm Juan. A programmer currently living in Budapest. I believe in well-engineered solutions, clean code and sharing knowledge. Thanks for reading, I hope you find my articles useful!