Bricolage: A data collage at the front end of innovation
How do you structure unstructured, undisciplined and generally unruly data and convert it into meaningful results? It is not uncommon for organizations to be confronted with data from multiple studies done over a period of time. The creation and internal understanding of this diverse research can represent a substantial investment of both time and money. Worse yet, data sources can be radically different, coming in from technology, market research, strategy and others. These diverse data sets all have value in contributing to the “informed intuition” of the organization but they often do not lend themselves to driving an innovation project. Indeed this hodge-podge, bricolage, of seemingly disconnected and irrelevant data can even distract and disrupt an innovation effort.
Chris is currently writing a chapter of this subject. Many of you have worked with him on this, the fuzziest part of the Fuzzy Front End. He calls it the “Qualitative Cluster Analysis”. It is that point in discovery where all information comes together and is synthesized into potential opportunity areas. The chapter will be a step by step guide on how to gather, prepare, massage and report out the findings in a way that enhances innovation and does not drag the team into data black hole.
Process components will include:
- The nature of data
- Structuring diverse nominal data for analysis
- The importance of bias vs. informed intuition
- The basics of an affinity sort
- Converting affinity buckets into qualitative clusters with definition (meaning in the bricolage)
- Selecting vs. eliminating
- Moving from qualitative clusters to a testable hypothesis
- Qualitative testing and the building of a formatted future story
- What is your communicable truth
- Application to discovery and informing the charter
This is a recurring segment every issue that explores how to gather, prepare, massage and report out findings in a way that enhances innovation
Publication January 2017 is scheduled. Chris would enjoy hearing about your synthesis experience, the good, the bad and the ugly… and as always volunteer readers are welcome.
