The Guide to Automating Time Studies

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Learn the roadmap for transforming and automating your time study capture.

For years, many organizations have relied on paper forms, spreadsheets, email reminders, and manual workflows to manage time studies. Those approaches may be familiar, but they also create an unnecessary burden. They ask already busy people to stop, remember, classify, and report how they spent their time, even when much of that information may already exist across scheduling, payroll, time and attendance, communication, billing, core business systems (e.g., EHR, CRM, ERP, or case management tools), or other enterprise systems.

That is the opportunity automation creates. Instead of treating the time study as a manual reconstruction exercise, organizations can use existing data, business rules, analytics, and AI-supported classification to build a more accurate picture of how time is spent. The goal is not simply to digitize the old process. The goal is to reduce reliance on recall, minimize administrative burden, and move toward time studies that are more continuous, contextual, and defensible.

With the right foundation, time studies can evolve from manual, episodic workflows into a more automated, connected process. Existing data can reduce manual entry and reliance on recall. Automation can streamline repetitive tasks. Analytics can reveal patterns and performance. AI can support classification, mapping, and interpretation. And governance can ensure the resulting data remains accurate, explainable, and defensible.

This guide outlines a practical roadmap for that evolution. I hope you find these insights useful. Our team would be thrilled to partner with you and support your transition to fully automated time studies.