The Contingency Model of Data Mesh

Not even in the digital world can it be denied that since time immemorial there has always been a dynamic interaction between technology and organization, where the former never can deterministically deliver a certain result if it is dissonant with the latter. As a starting point for the article, it is shown how there are still remarkable "trends" of organization even today, where selected organizational models not always are based on the most appropriate model given a certain context, technology or a specific goal (so-called contingency model), but instead is following the discourse of what other companies, researchers or consultants currently see as the most "modern". Parallel to becoming increasingly clear how the digitalization of recent years now is exploding into a new era of data disruption, it is argued that we are seeing exactly the same process in the data area as well -- with an increasingly strong trend from monolithic setups in data lakes, to a more distributed data setup adapted to local stewardship, so-called data mesh. The article draws attention to how in this context it becomes even more hopeful how we now can see the first indications of a more fruitful approach than the "latest trend" in the field, where we in a similar way as within organizational research can discern the first embryo to a contingency model also for data setups. The article argues that this will most likely be one of the most crucial prerequisites for a data-disruptive success in 2022 and beyond.