Students from the Digital Enterprise Management (DEM), Artificial Intelligence and Information Management (KIM) and Information Management Automotive (IMA) degree programmes were involved. They were supported by professors from the three universities and future lecturers from UMI.
Design Sprint meets Artificial Intelligence
The aim of the workshop was to analyse the customer onboarding process at the Ugandan logistics company Beyond Logistics and to optimise it with the help of digital, AI-supported solutions - from quotation preparation to pricing. The methodological basis was a design sprint, which made it possible to develop, test and refine user-centred prototypes within just a few days.
A particular highlight: the daily integration of customer feedback. Representatives from Beyond Logistics accompanied the entire process, provided valuable feedback and enabled the students to gain a deep understanding of real challenges.
"The level of engagement with the customer was surprising - it wasn't just about developing solutions, but really understanding the needs and building a bridge between academia and industry," said one feedback.
Learning in diversity
The participants worked in interdisciplinary and international teams - an aspect that was particularly appreciated:
"It was a pleasure to work with people from all over Africa and Europe - understanding how they work and learning from them was a real eye-opener."
“Different students from different institutes, with different approaches and expertise, working in a new field - and still achieving brilliant results together.”
Outlook: Continuation planned in Kampala
The results were convincing: After the presentation of the final prototypes, Beyond Logistics was delighted. It was jointly decided to organise a follow-up workshop in Kampala in October 2025 to further develop the ideas and proof-of-concepts developed and put them into practice.
Read more about the project here: https://www.hnu.de/forschung/projekte/projekt/digital-logistic-services-and-entrepreneurship-dlse
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