Since more and more embedded products also are connected, it is conceivable to develop, deploy and measure usage on new software in iterations which lengths are determined by the speed of the software development teams instead of the setup of the manufacturing process, going from years to weeks. Such
an innovation experiment system (IES) would utilise feedback from real users of the embedded products in a scale comparable to the entire customer base.
The notion of continuous innovation is not new, but the concept is novel in the embedded domain.
The driver for having such an IES is that business and design decisions should be based on data, not opinions among developers, domain experts or managers. The company running the most experiments among the customer base against the lowest cost per experiment outcompetes the others by having the decision basis to engineer products with outstanding customer experience.
Chapter 11 presents three architectures to support IES for mass-produced devices with embedded software, which together with an infrastructure capable of collecting and analysing the data. Case VI implemented the thin client architecture for innovation experiments from chapter 11 and ran an experiment
collecting data from 7 users.
The conclusion is that it is technically feasible to implement an IES with the architecture defined in chapter 11, and that the measured data can support conclusions about implemented designs. The main contribution is the architecture for innovation experiment systems for embedded software. The concept of innovation experiment systems in this domain is completely new and the architecture is the first of its kind.
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