Data Analytics – what is it and how does it benefit business?

“I’m a mathematician by nature...”

...says Prof. Alexander Martin, and it’s impossible to overlook his enthusiasm for the subject. At Fraunhofer IIS, he is tasked with driving data analytics forward, and indeed, nothing would suit him better. For only by applying mathematical methods and models is it possible to harness the full potential of the data that is collected and collated every day. This is how companies end up with the best solutions for their processes, organization and business models. And when mathematicians talk about the “best solution,” they mean it literally – and have the numbers to prove it.

In this interview, Alexander Martin explains what data analytics is and how companies benefit from it.

“At the end of the day, these processes are all about the bottom line.”

How does data analytics benefit business? Prof. Alexander Martin explains in this interview.

Prof. Martin, what is data analytics?

Data analytics covers all processes and methods for analyzing data.

Who needs data analytics and why?

The principal users of data analytics are industrial companies that work with data, either by gathering it or generating it themselves in a move to convert it into added value for their business. They may be looking to improve their processes, ready their organization for the future or develop new business models.

What are the typical sectors?

Typical examples include logistics and supply chain management, so that’s transport, storage and intralogistics. But data analytics methods are also needed in manufacturing, energy management and finance.

What commercial benefits does data analytics offer business?

At the end of the day, these processes are all about the bottom line; whether we’re talking about production planning or making it possible to better manage individual machines. But it’s also about finding ways to serve customers better, faster, more efficiently and more cost-effectively. Proper data analytics can make improvements in all these areas, which in turn adds value.

How can data that was gathered in the past – meaning data that describes the past – say anything meaningful about the future?

Of course you can’t expect data analytics methods to work miracles, to predict the future or to allow us to develop disruptive, in other words entirely new, approaches as if out of thin air. But many processes get repeated, for instance in manufacturing, and that is something we can use to make accurate forecasts. Properly analyzing this kind of data allows companies to realize sooner when a machine will break down or when a battery will need replacing. This dramatically reduces downtime and adds value.

Combining forecasts results in synergy and learning effects. So instead of halting the production process to replace only one part that has just or is about to fail, you can also change out all parts, including on other machines, that will likely need to be replaced soon anyway. Overall downtime drops as a result. This also allows companies to gain new insights into the overall process and make continuous improvements to it.

Prof. Martin, thank you for your time.

Prof. Alexander Martin

Prof. Alexander Martin develops data analytics models and methods that are absolutely cutting-edge. The aim of his research is to solve general mixed-integer linear and non-linear optimization problems relating to applications in areas such as transport and logistics, finance and energy management.

He is currently working to establish the ADA Center for analytics, data and applications, in which Fraunhofer IIS will collaborate with Friedrich-Alexander-Universität Erlangen-Nürnberg, Ludwig-Maximilians-Universität München and other research partners.