Why you should do data analytics?

Data analytics is complex, and identifying patterns takes a lot of work.
But data analytics is crucial for your economic success. According to IBM’s 2014 innovation survey, companies that apply big data and analytics are 36 percent more likely to outperform their data-incompetent peers in revenue growth as well as operating efficiency. IBM’s survey also outlines that outperforming companies are 79% more likely to use data analytics tools. To sum it up, outperforming companies are much more likely to have the capabilities to produce actionable insights out of data.

At this point, mention should also be made of the study from McAfee and Brynjolfsson (2012). The authors analyze 179 large US companies and find that data-competent companies are about 5% more productive and 6% more profitable than their less data-competent competitors.

Here are some examples of how data science can your businesses to grow:

Probably most important “customer insights“: You can use various techniques in order to analyze customer data and find out more about their behavior, preferences, and buying patterns. Such information can help you to create marketing strategies, improve customer service, and develop new products and services.

Second, you can use data science to generate “predictive models“. These models can help you to future outcomes and mitigate risks and possible inefficiencies for various business processes.

Third, data science can be used for the “improvement/development of products“. Results can help you to identify new markets.

Last, data science can also help you to find clues about “fraudulent activities“.

In summary, data science can help you when it comes to making better decisions and increasing efficiency as well as revenue growth.

Literature:

McAfee, A., Brynjolfsson, E., Davenport, T. H., Patil, D. J., & Barton, D. (2012). Big data: the management revolution. Harvard business review, 90(10), 60-68.