This user's frustration is a textbook case of a system that looks automated but isn't. They built a pipeline: Microsoft Form writes to Excel, and a daily cron job reads that Excel via Graph API. It should work. It doesn't. The data is stale until someone manually opens the file in a browser. That is not automation. That is a chore dressed up in code.
What we see here is a design assumption that has become a hidden tax on productivity. Microsoft Excel, for all its capabilities, is still fundamentally a desktop application at heart. When data arrives from a Form, it lands on the sheet, but the internal calculation engine and the connected data model do not refresh unless the application is "awake." The Graph API reads what is on the sheet, but if Excel hasn't been told to re-evaluate, it serves up yesterday's truth. The user's cron job is faithfully fetching a snapshot of a file that is technically in a sleep state. The disconnect is not with the API call; it is with the underlying assumption that a cloud-connected file is an active, live database. It is not.
The practical alternative the user needs is to break the dependency on Excel as the live intermediary. Since Power Automate is off the table, the most direct path is to write the Form responses directly into a data store that is always active. A simple option is to have the Microsoft Form trigger a small script, using something like a PowerShell script running on a server or a low-cost Azure Function, that writes each new response into a SQL table or even a plain CSV file on a network share. The cron job then reads from that store. The Excel file becomes a backup or a reporting layer, not the operational database. Another approach, if the user is comfortable with Python, is to use the `requests` library to poll the Microsoft Graph API for the list of Form responses directly, bypassing the Excel file entirely. The Graph API for Forms returns the response data in JSON, which is always current.
The core lesson here is not about finding the right API endpoint. It is about recognizing when a tool is being asked to do what it was not designed for. Excel is a fantastic tool for analysis, visualization, and ad-hoc work. It is a terrible database for an automated pipeline. This user is doing the right thing by questioning the inefficiency. The solution is to stop treating the spreadsheet as the source of truth and start treating it as what it is: a document that needs to be opened to be alive. Move the data out of the sheet and into a store that never sleeps.