Data-driven service design: When qualitative data meets quantitative data

How to combine quant and qual data for added value? At this workout, hosted at Informaat, three speakers shared their experiences doing quant-qual research and design with different companies.

Data-driven and fact-based design has received more and more attention in business in recent years. For service designers, who by education mostly focus on qualitative aspects, this is an interesting trend. A reason for the increased interest may be that data simply get more easily and readily available so there is a much greater affordance to indeed support qualitative data with quantitative facts. On the other hand with the uprising of in-house design teams, service designers may find themselves in a more complex stakeholder playing field forcing them to corroborate their qualitative insights with quantitative data. Anyhow, this leads to some interesting questions. For instance, How to go about combining the two? What are the challenges you face as a designer? How does it impact the design process? What can be the added value of combining the two?

To feed the discussion about this we invited three speakers to share their experiences.


Lex Dekkers (ABN AMRO) shared his work on the development of ‘Gradefix’: a service that allows for a quick overview of your financial situation when you’re buying a house. He explained how they used quantitative and qualitative data from consumers iteratively through all phases of development of the service to finetune and optimize the experience.

Second on stage was Erik Roscam Abbing (Livework).  Erik talked about a project for OHRA (health insurances) where they worked with customer intelligence experts to gather existing quantitative data such as NPS and map that onto customer journey maps. This allowed them to create a much more customer centric view of their data. After that they continued to create both qualitative research based customer journey maps and data based journeys. This approach resulted in hi-res personas and customer journey maps that were used a lot in value proposition development.
In the second case Erik presented about Europcar he showed how they generated quantitative data themselves to support qualitative research and to prototype simple business cases. A video recording of this talk will soon be made available here. 

The last speaker of the evening was Wouter van der Hoog (Hoog+Diep) who presented about a project for their client Roche (a Swiss healthcare and pharmaceuticals company). Roche asked of its contracted parties to gather and use both qualitative and quantitative data from the start. Wouter shared his lessons learned.

We ended the formal part of the evening with a Kahoot in which we were asked to vote on quant-qual statements (see below) and discussed the statements afterward.


  • You need qualitative data to know which quantitative data to gather.
  • It is very unwise to make decisions based on qualitatitive insights alone.
  • Customer research should only be done by specialized research departnments.
  • Quantitative data that cannot challenge qualitatitive insights is of little added value.
  • You need quantitative data to help focus and scope your qualitative research.
  • Numbers help to create convincing lies.

Besides being a nice experiment with Kahoot (great fun!), this spurred discussions during the drinks and networking.

Thanks presenters, audience and organizers. Co-creating experiences is fun and will change the world for the better ;-)


Cheers,

Marie de Vos (TomTom), Esther van der Hoorn (Aegon), Froukje Sleeswijk Visser (Delft University), Susanne van Mulken (Informaat)


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