{"id":3691,"date":"2021-08-02T08:44:48","date_gmt":"2021-08-02T12:44:48","guid":{"rendered":"http:\/\/blog.daed.com\/?p=3691"},"modified":"2024-07-11T10:59:15","modified_gmt":"2024-07-11T14:59:15","slug":"user-centered-design-phase-2-define","status":"publish","type":"post","link":"https:\/\/blog.daed.com\/?p=3691","title":{"rendered":"User-Centered Design: Phase 2 Define"},"content":{"rendered":"

This is the second in our series that\u2019s diving into the User-Centered Design (UCD) Process. In this article, we\u2019ll be walking through the second phase of UCD, which is <\/span>Define<\/span><\/i>.\u00a0\u00a0<\/span><\/span><\/p>\r\n

\"The<\/p>\r\n

In the first phase,<\/span> <\/span>Discover<\/span><\/i><\/a>, you\u2019ll have conducted secondary and primary research to learn everything that you could about your users, their goals, and the obstacles in their way. In the <\/span>Define<\/span><\/i> phase, you\u2019ll process and analyze all of that information, transforming it into a knowledge base that is filled with research insights and design implications that will help generate solutions as you move on to the next phase.\u00a0<\/span><\/span><\/span><\/p>\r\n

While<\/span> Discover<\/span><\/i> relied on generative or expansive thinking, <\/span>Define<\/span><\/i> relies on <\/span>evaluative thinking<\/span><\/i>. Evaluative thinking is what you do when you analyze information and then use that information to evaluate and refine theories and discoveries. This is the type of thinking that helps you narrow in on a solution that will meet your users\u2019 needs.\u00a0<\/span><\/span><\/p>\r\n

The first step in <\/span>Define<\/span><\/i> is to analyze your data; however, it\u2019s nothing like analyzing quantitative data. At Daedalus, we use a process called<\/span> affinity sortin<\/span><\/i>g, an interactive process in which we sift through all of what we saw and heard during our research, looking for trends and solitary\u2014but interesting\u2014findings.\u00a0<\/span><\/span><\/p>\r\n

Affinity sorting isn\u2019t a difficult process, but it can be a bit time-consuming. We first capture relevant observations from our research on <\/span>affinity cards<\/span><\/i>, which can be post-it notes, index cards, or printouts\u2014anything that can be easily moved around and repositioned. Relevant observations can be direct quotes from users you interviewed, observations you took note of in the field, as well as any relevant pictures you may have captured. We draw them from visit reports, debriefing notes, videos and photos from the visits, and interview transcripts.<\/span><\/span><\/p>\r\n

For example, here are some observations and quotes from research we conducted in a dialysis unit a few years ago<\/span>\u00a0that were later turned into affinity cards.\u00a0<\/span><\/span><\/p>\r\n

\"A<\/p>\r\n

When creating affinity sorting cards, there are a few key things to keep in mind:\u00a0<\/span><\/p>\r\n