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Developing survey instruments seems easy. You ask a question and get an answer... How hard can it be? Real hard it turns out. Over the last several decades, people scientists have done a bunch of really specialized, super boring [or interesting if you're like me] statistical testing and research to help increase their validity (i.e. are you measuring what you think you're measuring) and reliability (i.e. is it consistently measured?). For measures about people, this is called psychometrics. Psychometrics " is the field of study concerned with the theory and technique of psychological measurement, which includes the measurement of knowledge, abilities, attitudes, and personality traits. " The below flow chart is not meant for everyone… it assumes that you have familiarity with the statistics and general best practices behind survey development for latent variables. Otherwise you’re going to look at this and want to barf. Which may have already happened when you read latent variables. For you Quantoids out there, this is not meant as the end-all-be-all guide to survey statistics and the structural equation modeling (SEM) that follows. Survey analytics is part art, part science, and you can’t capture every nuance in one long, wordy, stats jargon-y, “infographic,” “flow chart.” The numerical guidelines we put in there are NOT hard and fast rules, rather common guidance referenced in the literature.