# Quality Assessments By:: [[Brian Heath]] 2022-10-20 Quality is a particularly elusive idea. Most people can identify quality when they see it, but most people cannot define it. Is the essence of a high-quality car the same as a high-quality event? Is something that is high quality to me the same thing as high quality to you? How much more are you willing to pay for high quality over medium quality? These questions highlight the problem with quality as a relatively defined idea of excellence. In the data and analytics world, the goal may be to create high-quality data analyses. This is an impossible and neverending task. Partly because of the relative nature of quality, but also because the audience that defines quality may have no clue how to judge analysis quality. If you consider that most analysis produced by a professional is well beyond the average consumer, most people are unqualified to assess the quality of that analyses. Yet, they do it all of the time. They say, "this doesn't feel right," or "how can I trust this thing" to indicate their quality assessment. It does not feel excellent to them. So, what makes something excellent when you don't know anything about it? For example, I don't know what makes a watch excellent, but I believe a Rolex watch probably has some of that excellent quality. I infer this from the pricing, the brand name marketing, and the way other people show off their watches. Here I'm using heuristics to save me the time and energy to figure out what makes an excellent watch. Notice that pricing, marketing, and other social dynamics don't say anything about the quality of the watch in any mechanical sense. These heuristics are used by most people who do not know a subject area: price, word-of-mouth, and status. If you are attempting to create high-quality analysis, consider how you can use these heuristics to further your cause. Perhaps you should charge more for the work, or show statistics about how many hours were spent on the analysis. Maybe you could share all the great work you've done elsewhere and highlight the great wins of the past. Perhaps highlighting how the analysis is customized exclusively for them to have a competitive advantage is the way to go. Maybe go with all three? If you are proud of your work and the customers are incapable of judging it fairly, utilizing these tried and true methods is a viable path to quality analyses. #### Related Items [[Analytics]] [[Quality]] [[Heuristics]] [[Data]] [[Marketing]]