Digitalization is one of the mega-tends of our time. By 2020 the worldwide volume of data is predicted to reach over 44 trillion Gigabytes, a ten-fold increase over 2013. The challenge is therefore set for businesses to filter, target and bring forward relevant information out of the daunting mass of data and make something useful out of it in a timely manner. For example, finding new trends and technological advances that would lead to real-world competitive advantages. Currently, to monitor the business climate businesses must invest large amounts of time and capital. This has a much more detrimental impact on the small and medium-sized enterprises (SMEs) than on their larger competitors, because of smaller amount of resources they have for investing in the professional implementation of scanning their environment.
The Goal of the research project RADAR is to create an environmental scanning system that can take large sources of data, analyze and detect the relevant signals, trends, technologies and new relationships that could be used as an advantage, or find disruptive changes in the company’s environment in real time.
For the Goal to be achieved, the combination of existing techniques from the fields of machine learning, applied statistics and semantic analysis of large amounts of data that can be initially combined in a theoretical model. From this theoretical foundation, a new software can be created that scans the business environment, and through self-learning mechanism, automatically adapts itself to the given examination context.
With the creation of a cloud-based environmental scanning system, companies of all sizes and industries can observe their respective environments with great accuracy and minimal capital allocation. As a result, they will be able to react quickly and create forward-looking strategies that allow them to respond to challenges successfully. The cooperation of the development-partner the “Bayern Innovativ” will grant RADAR the institutionalization through cooperative agreements that will be successful in actively circulating the results over the projects life.