Data- and Value-Driven Software Engineering with Deep Customer Insight

There is a need in many software-based companies to evolve their software development practices towards continuous integration and continuous deployment. This allows a company to frequently and rapidly integrate and deploy their work and in consequence also opens opportunities for getting feedback from customers on a regular basis. Ideally, this feedback is used to support design decisions early in the development process, e.g., to determine which features should be maintained over time and which features should be skipped. In more general terms, the entire R&D system of an organization should be in a state where it is able to respond and act quickly based in instant customer feedback and where actual deployment of software functionality is seen as a way of fast experimenting and testing what the customer needs. Experimentation refers here to fast validation of a business model or more specifically validating a value hypothesis. Reaching such a state of continuous experimentation implies a lot of challenges for organizations. Selected challenges are how to develop the “right” software while developing software “right”, how to have an appropriate tool infrastructure in place, how to measure and evaluate customer value, what are appropriate feedback systems, how to improve the velocity of software development, how to increase the business hit rate with new products and features, how to integrate such experiments into the development process, how to link knowledge about value for users or customers to higher-level goals of an organization. These challenges are quite new for many software-based organizations and not sufficiently understood from a software engineering