If you search for the term “data analyst” or “data scientist” on the major job search engines, you will find that this relatively new career field is in high demand. Industrial and logistics companies are often behind the thousands of these types of advertisements. But why are so many specialists who deal with data on a full-time basis needed, especially in companies where everything primarily revolves around the production and distribution of goods? The answers are obvious: digitization, big data, and Industry 4.0. Digital transformation has long since swept through most industries, but small- and medium-sized businesses, in particular, still have a long way to go to catch up. So now is an excellent time to take a close look at the tasks of data managers.
The Diverse Tasks of Data Analysts
In addition to the very consumer-oriented examples of digitization, such as the explosion in online retail during the COVID-19 pandemic, the topic of Big Data in Industry 4.0 should by no means be ignored. The mechanical engineering, automotive, and electrical industries have relied on digitized supply chains, data warehouses, and end-to-end processes for years. Large amounts of data are required to implement these new processes successfully, and even more data are created during their execution. Managers, consultants, and optimization specialists in industry have long since ceased to be traditional engineers and have become digitization experts, software developers, and IT specialists.
The fact that the job of a data analyst in supply chain management or the logistics department of an industrial company includes analyzing data is self-explanatory, but collecting and evaluating data is not enough to help any company. From the information obtained, correlations must be established, intelligent decisions derived, and solutions developed to continuously improve value chains. Why is this important? Our world is changing rapidly, and not just in online retail. Those who miss the boat in industry and do not react quickly enough to market needs will hardly stand a chance in the international market.
In addition to the ability to improve facts with the help of mathematical optimization and artificial intelligence, interdisciplinary responsibility also lies with data experts, such as:
- Facilitating a network of IT experts, engineers, and consultants;
- Leading optimization projects and calculating efforts and costs;
- Managing system implementations and user onboarding;
- Developing key performance indicators (KPIs) and tracking methods.
It quickly becomes clear that in addition to technical skills and a basic understanding of industry, communication and interpersonal skills are also necessary. Empathy, a quick grasp, strong communication skills, facilitation skills, and a strategic mindset are requirements that frequently end up in data analyst job postings.
How Do I Become a Data Specialist?
The ideal combination to become a sought-after professional in the industry is a basic engineering education coupled with advanced data analytics training. So, if you are already an engineer, then a postgraduate program such as a Master of Science Data Analytics and Decision Science at RWTH Business School would be something to seriously consider. With the combination of Machine Learning and Operations Research modules and management electives such as “Start-up and Growth Management,” you will acquire a broad knowledge base. An included internship and soft-skill training in Career Service offer opportunities for you to complete your job profile and make you the perfect candidate for today’s job market.
After four semesters, you will be able to intelligently interpret data in logistics or supply chain departments and implement important optimization processes, thus contributing to your company’s economic success.