Innovative ideas for embedded products are typically collected and prioritized during the roadmapping and requirement management process as part of the yearly release cycle. This cycle is usually determined by manufacturing concerns of the hardware. Feedbacks on innovations from real customers are collected only on new product models, if collected at all.
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 (link to Ries, link to Bosch}, 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.
The innovation experiment system focuses on incremental innovation according to the framework by Henderson and Clark. The short iterations of experiments are primarily aimed to refine and extend established designs. Improvement occurs in individual software parts, but the underlying design concept remain mostly unchanged, even if there is nothing that prohibits the evaluation of e.g. architectural innovations as well.
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