Develop successful digital products and bring them to market – as quickly as possible, thank you very much! Something along these lines could be the inofficial mission of many digital units that are currently being established across all industries as innovation incubators for existing businesses. No company can afford to be left behind by the competition. So what better plan than to become an innovation leader of the own industry? But how can product development of digital units keep up with this rapid pace?
The Build-Measure-Learn principle is a continuous process used in the development of digital products. It involves three steps:
In Step 1 (Build), the team can develop a simple prototype at the start of the project. A prototype can be built faster and cheaper than a fully functional product and allows the team to gather feedback from users early on. This allows them to incorporate it directly into further product development. After prototyping, a Minimum Viable Product (MVP) can be developed first, which contains the basic features that make it a minimum version of what would already sell.
The Build-Measure-Learn principle developed by Eric Ries is closely associated with the Lean Startup movement. He explained that startups are more successful when they test ideas at a very early stage of product development, before too much time and money is invested in developing a full-blown product that in the end does not provide enough added value for the user.
However, the principle is no longer only relevant for startups. It has now established itself as a proven method for product development in companies of all sizes. By focusing on user feedback and continuously learning from user behaviour, companies can ensure that their products meet customer needs and are continuously improved.
By applying the build-measure-learn principle, digital units can increase the speed of development of their products and speed up the process from initial idea to market launch significantly. Continuous measurement and learning from user behaviour allows for constant improvement of the product and ensures a better overall user experience. By identifying problems early on, and then adapting the product quickly, costly mistakes can be avoided. This ultimately leads to a cost-efficient, lower-risk development process.
The development of data-based business models is an important step in leading the printing and packaging industry into the digital future – a mission that Koenig & Bauer’s Digital Unit has derived from the company’s “Exceeding Print” strategy. In the future, a new product called Koenig & Bauer Analytics will combine production data from multiple sources in a single interface and enable users to create complex analyses in the simplest possible way – a helpful tool for unlocking hidden potential for improvement in print and packaging production.
Koenig & Bauer is realising their new Analytics product according to the Build-Measure-Learn principle. Based on assumptions and customer needs, a simple click dummy was first created that already showed the future design appearance and allowed the user to click through the interface – in that phase without real-life production data. This simple prototype was discussed with test customers. Based on the feedback, the first functional version of the product has been created, which will soon be made available to the first hand-picked customers for testing. The market launch for Koenig & Bauer Analytics is planned for later this year.
“By consistently applying the Build Measure Learn Cycle, we were able to test our prototype with our customers and know exactly what we need to implement in the MVP. We therefore didn’t have to base our decision on assumptions and could go into implementation with common objectives. This saved us lots of discussions and probably also expensive changes in the product later on.” (Alexander Stern, Product Owner)
