How Users Employ Workarounds in Software Forms

TL;DR

This study investigates how users employ workarounds when software forms misalign with data needs, using a descriptive user study across three instrumented apps (TA, HR, REG) and three widget categories (Open, Predetermined, Controlled). It identifies 920 workaround instances, characterizes workaround types (Data Adjustment, Functional Adjustment, Fallback, Data Loss), and links these to data quality and widget affordances, employing chi-square, Spearman, and Kruskal–Wallis analyses. Key findings show Functional and Data Adjustments yield higher data integrity, Open widgets support flexible but riskier input, and users develop systematic strategies that reduce effort over repeated misalignments. The work provides a publicly available dataset, practical design implications for detecting and mitigating workarounds, and directions for improving form design in low-code environments to better match user needs and preserve data quality.

Abstract

Workarounds enable users to achieve goals despite system limitations but expose design flaws, reduce productivity, risk compromising data quality, and cause inconsistencies. This study investigates how users employ workarounds when the data they want to enter does not align with software form constraints. Through a descriptive user study, we analyzed how workarounds originate and impact system design and data integrity. Understanding workarounds is essential for software designers to identify unmet user needs.

Figures (3)

• Figure 1: Distribution of the data misalignments across the 15 participants
• Figure 2: Characteristics of workaround types
• Figure 3: Widgets in workarounds ($n=898$)