Contact person:
Helena Holmström Olsson
  • Software Center
Responsible at Malmö University:
Helena Holmström Olsson
Project members:
Collaborators and other project members:
  • AB Volvo
  • Axis Communications
  • Bosch
  • CEVT
  • Chalmers University of Technology
  • DEIF
  • Ericsson
  • Grundfos
  • Jeppesen (Boeing)
  • Qamqom
  • SAAB
  • Scania
  • Siemens
  • Tetra Pak
  • Volvo cars
  • Wärtsilä
  • Zenseact
Time frame:
01 January 2021 - 31 December 2021
Research subject:

Project description


An accurate understanding of customer value is critical for business-to-consumer, as well as for business-to-business companies and successful companies are those that translate customer needs into value-adding functionality. However, due to the fact that customer needs evolve over time, as well as new technologies becoming available, companies need mechanisms that help them continuously monitor value and that support alignment of groups (e.g., developers, product managers, business and sales etc.) around key factors to optimize for.

As effective means for acquiring and leveraging insights about customer needs, as well as for assessing product performance and system behaviour, data-driven development practices are being increasingly adopted across domains. With these practices, companies collect, analyze and process data to understand product performance and customer preferences. Moreover, and as a mechanism to test hypotheses and value propositions, experimental practices such as e.g. A/B testing is gaining momentum. However, in order to make effective use of data for experimental purposes, companies need to know what factors they are optimizing for.

Data-driven and experimental development practices provide effective means for companies to adopt a customer and market-centric way of working. In online companies, controlled experimentation is the primary technique to measure how customers respond to variants of deployed software. Over the recent years, and due to increasing connectivity and data collection from products in the field, these practices are being adopted also in software-intensive embedded systems companies. In these companies, experiments are run on selected instances of the system or as comparisons of previously computed data to ensure value delivery to customers, improve quality and explore new value propositions.

However, to utilize the benefits of data-driven and experimental development practices, companies need to define what value factors to optimize for. For highly complex embedded systems with thousands of parameters, and with people at different levels in the organization having different opinions about the value of features or products, this is a challenging task.

Project goal

In this project, we support companies in their adoption of data-driven development practices and their overall transition towards becoming digital companies. By complementing our previous work on value modelling with work on business agility for continuous delivery and improvement of this value, we seek to support organizations in optimizing, prioritizing and focusing their development, delivery and improvement of systems. We develop new methods, techniques and tools that help companies align efforts and increase their overall business agility with the overall goal being to accelerate digitalization and help companies move towards continuous value delivery to customers.