It cannot be stated enough: Germany’s good economic shape is largely based on its famous “Mittelstand” — hidden champions of the middle-class who produce world-class industrial goods and machinery. Startups have had a hard time entering the market so far, as the industry is very innovative in itself and provided no immediate target for easy-to-execute business models. It still remains hard to crack — but with true innovations from experienced teams and the internet of things as the industry’s driving force, we see the potential for startups to become highly successful in this attractive and strong market.
SaaS solutions
Generally speaking, a software frontend is needed in order to enable the end user to work with the data generated by the smart sensors distributed across the production floor or embedded in specific machines. Without the analysing and steering interface, the collected data would go to waste. Intelligent software solutions which draw on the connectedness of production equipment might e.g. manage maintenance cycles based on a lifecycle analysis, enable remote technical servicing, enforce and monitor production plans, dynamically calculate the capacity of production lines or manage autonomous industrial vehicles. The challenge for startups here is to manage the specifics of each B2B client — even though there will never be a “one-size-fits-all” solution, startups have to find a way to reduce implementation complexity in order to scale their businesses. This can either be achieved by focussing on very specific applications or by making the software highly adaptive to each customer’s needs — plus (even better) adding a great UX that enables customers to customize the software themselves.
API connection layers
In order to uncover the data treasure piled up by remote sensors on the production floor, a middleware layer is needed for the above-mentioned SaaS solutions to access the sensor data. Sensors are produced by different manufacturers, use different transmission technologies and generate data in different formats. Unifying and standardizing these data in a common backend system dramatically enhances the interaction between the SaaS layer and the first-party data, especially when those are provided seamlessly via an API.
Integrated digital solutions
New solutions use sensor data and combine them with state-of-the-art technologies in order to create whole new kinds of production tools. Our interest was particularly caught by the application of augmented reality for precise manual work or for setting up and adjusting various machines, such as CNC lathes. There are many more interesting concepts where sensor data are directly applied to the physical tool — e.g. intelligent gloves — however, we as Project A are seeing ourselves as a software investor. Our investment focus might include hardware as an enabler — still, we will only be investing if the software is the actual core of the business.