• Operationalization: the definition and operationalization of indicators used to be solely geared towards the specific information need of a customer at that moment. Moreover, much less data was publicly available. Nowadays we take the (ample) available data as a starting point and see to what extent we can reuse this data for multiple stakeholders.

 

• Collection: in the early years Dialogic collected primary data as part of almost all of our research projects. Today, we are increasingly shifting our focus from the collection of primary data towards the (meta)analysis of secondary data.

 

• Analysis: used to be one-off and top down, that is, guided by a specific ex-ante hypotheses. Nowadays we often work bottom up in parallel, that is, starting from the data and (ex-post) deriving relevant research questions from the patterns that we find in the data (data mining). Furthermore we increasingly do analyses (near) real-time. This enables us to publish the most recent data.

 

• Presentation: with regard to the presentation of research results we see a rather speedy transition from traditional static paper reports to dynamic online data portals. It is for this reason that Dialogic has developed its own platform in-house through which analysis meets presentation. The platform has evolved into a modular system with a growing repository of components for data collection (e.g. through APIs, application programme interface, and survey modules), data analysis (e.g., dozens of advanced statistical techniques), data visualisation (an extensive library of charts, including GIS, geographic information system, modules) and publishing (e.g., tailor made modules for paper or on-screen presentations, and for mobile devices and tablets)

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