Design thinking has become a common approach to address the complex, dynamic, and ambiguous societal problems that philanthropies seek to address. However, there has been limited research on how different types and sources of data can lead to innovation at different phases of the design thinking process. 

In the article “Data in design: How big and thick data inform design thinking projects,” by Marzia Mortati, Stefano Magistretti, Cabirio Cautela, and Claudio Dell’Era published in Elsevier’s Technovation journal on April 3rd, 2023, the authors explore how big and thick data can provide value for design thinking projects with complex and ambiguous problems. To accomplish this, the authors conduct a series of case studies on how design thinking projects have used big and thick data (i.e. qualitative or ethnographic data) in different ways. 

A few takeaways from this piece: 

  • Using only thick or big data in complex design thinking projects with dynamic and ambiguous problems is no longer sufficient. There is a need to combine numerous types and sources of data throughout the problem finding, framing and solving processes. 

  • Big data must be complemented by thick data to understand the meaning or context behind different trends and build empathy with the end user and beneficiaries. In particular, thick data is needed to “explain some of the underpinning reasons for user preferences, habits, and unmet needs” (P.g. 10).

  • Big data plays an important role in design thinking decision making processes. It can be used to validate qualitative insights, balance evidence- with values-based decision making, and gain consensus when making decisions with many stakeholders. 

  • Combining big and thick data in design thinking processes can minimize biases in both types of data. 

The authors conclude by recommending several areas for future research to expand the scope of these findings to new industries and geographic locations.

Learn more about the case studies by reading the full article here.