Fear of innovation in German companies
“Failure isn’t an option” they say in many German companies. Yet a “culture of failing” and courage for new risks can absolutely be worth the trouble and boost innovations. Still, failure in the job is often regarded as a massive flop and tabooed.
According to Adobe’s “Digital Roadblock” study marketing experts from the UK, France and the USA assess the future quite differently compared to marketing experts from Germany.
The study proves, that German companies are afraid to take risks and face changes. For fear of failing a smaller readiness to assume risks is exhibited.
However, through Christopher Nolan’s ‘Batman Begins’, we already know, that failure can have positive aspects: As a child Bruce Wayne falls into a well. Hereupon, his father gives him a piece of wisdom: “Why do we fall, Bruce? – So we can learn to pick ourselves up.” This metaphor accompanies him on his path of life – failures happen to better us. Arianna Huffington, non-fiction author, journalist and co-founder of Huffington Post realized that as well. Whenever she looks back on her bumpy road to success, she likes to quote her mother: „My mother said failure was a stepping stone to success.“
For effectively serving integrated digital communication ways, marketing roles must be thought and casted anew. That doesn’t just cost money – it’s also necessary to strike new paths and asks for a certain readiness to assume risks. Often, the go-to formula is: Hiring new employees with new perspectives and a willingness to take risks. Thus, longtime employees can feel threatened in their position. Almost like a vicious cycle: Motivated by the fear of failing, new employees are being hired to think differently, employees who could eventually replace the “old” ones.
Often, it’s just about finding new ideas and innovations. However, coming across fresh, new ideas isn’t always that easy. In these cases, trend research tools can support companies. The AI Pythia, supported by a neural network analyzing big data, is exemplary. By analyzing Google search queries as well as other sources, trends can be identified in advance. Thereby, companies can save time and win certainty over their product development.
Still, what are neural networks?
Artificial neural networks are self-learning systems, which can improve themselves on their own. They are inspired by the human brain and based on its biological structure. A neural network consists of a model of connected neurons, called units. With its combination and arrangement issues can be resolved computerized. Fundamentally, there are different kinds of neurons: Input neurons receive information from the outside world. Hidden neurons represent intern information patterns and are located between output and input neurons. Output neurons pass information as result to the outside world. The different neurons are connected by edges. Thus, output of one neuron can be input for a different neuron.
Where to find neural networks?
Neural networks are applicable in many ways. For instance, they are being used for image recognition. If you search for ‘cat‘ on Google, Google can display thematically similar pictures, so, more pictures with cats.
For humans it might seem natural to identify a cat, however a computer doesn’t recognize a cat, but only color values for each pixel, usually three for each RGB color.
Through machine-based learning, with the help of many comparative values a computer can learn how to identify a cat on a picture.
Before a neural network can make reliable decisions, it must be trained. With the help of preset teaching materials, the network will be trained according to certain rules. Those rules indicate, how teaching materials are supposed to affect the network. By continuously comparing target and actual state the network learns how to combine neurons reasonably.
Next to image recognition further application areas of past years are autonomous vehicles as well as – through us – trend research. While autonomous driving is still in its infancy, trend research is already being used intensively.
For example, our AI Pythia, which can do very precise trend research for future trends. Her algorithms deal with collecting, controlling and analyzing huge amounts of data, which are being evaluated with an artificial neural network. Instead of just calculating complex as-is states, which would be too large for the human brain, she can create forecasts. Therefore, Pythia recognizes trends and creates forecasts, which can provide a relevant competitive advantage.
The future is already here
As Adobe’s “Digital Trends 2019” study shows, the number of big companies using AI grew by 50 % compared to last year. Artificial intelligence can help minimizing the risk for possible mistakes. The AI Pythia creates trend forecasts for future demands. For this reason, interested companies can improve their products development.