**7. Conclusion**

In the last decade, many technological innovations became readily available for warehouse operators across the globe. It is a challenge for any warehouse operator to select the most fitting and efficient technologies to stay competitive among other factors on the market. The change towards networked and intelligent operations is ongoing and the pressure to innovate is one of many driving factors. Maturity models can mark an important waypoint in this challenge since they allow an efficient qualitative as-is analysis of operations and are able to support the development of integrated roadmaps. In this light, the authors aimed to develop and test such a maturity model in a practical environment.

For the development of the maturity model, we built on the recommendations by DeBruin et al. [9] and considered relevant literature and expert interviews to validate and ensure reliability and rigor of the maturity model. By using a single case study, we initially deployed and tested the maturity model and the application procedure for the good receiving process from unloading trucks to storing the goods.

The maturity model for the future of warehousing integrates maturity dimensions of process, technology and organization, which is postulated by industry 4.0. The model describes in detail the maturity in five levels, in two dimensions and subordinated categories. In total 32 elements.

The application of the model in a single case study results in a correct, comprehensive and intuitive reproduction and representation of the actual warehouse situation landscape.

The new model includes and considers aspects from industry 4.0 approaches such as autonomy and organizational design. By this, our model outlines a more holistic approach to the digital transformation of warehousing as part of an autonomous value chain. We have tested the model on a single case study in Switzerland, which does not allow to make assumptions on any other industries, company sizes or countries. Even we may recognize low maturities and gaps for each company, there is no indication of reasoning to invest for achieving a higher level. The context-specific application of the model may rise drivers and hurdles for continuous warehouse developments.

For warehouse management as a socio-technical system that considers people, process, technology and organization, the application of the model gives opportunities for improvement in a holistic way: maturity in logistics processes, technology and organization. Using this model as a starting point to design the transformation roadmap for the warehouse of the future gives awareness about the interrelationship in multiple dimensions. Even if we do not know exactly the interrelationships between the dimensions, it makes clear that digital transformation in logistics is more than implementing technology. It will affect management processes as well as roles, rules and according technical and collaborating skills.
