Event history analysis is an increasingly common technique used by social scientists to analyze change over time. Conducting such analyses often relies on the availability of historical information provided by survey respondents, for whom it may be challenging to recall events that occurred months or years in the past. As a result, when developing a survey that collects information conducive to such an event history format, there are several competing survey design priorities to consider. One goal may be to collect enough data to meet the analytic needs of a diverse set of data users. An additional goal may be to provide sufficient response options for respondents to easily and accurately convey their experiences over broad spans of time. Yet another goal may be to provide a suite of features (e.g., event history calendar, validations, cross-checks) that minimize recall error and encourage similar experiences across modes. Still another goal may be to ensure that the survey is conducted as efficiently as possible in order to minimize the response burden for respondents. For this large, nationally representative longitudinal study of recent college graduates, it was necessary to balance these competing priorities when developing items designed to elicit a history of employment, unemployment, and job search activities in the four years after college graduation. Here we examine the impact of this balance using such metrics as survey timing data, item-level nonresponse, comparisons to responses from an earlier wave of the survey, and comparable estimates from benchmark data sources. We will offer suggestions for survey designers based on lessons learned during the design and implementation process.