Michelle Healy survey-data-to-slide workflow walkthrough

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---
title: "Michelle Healy survey-data-to-slide workflow"
status: processed
source_type: workflow walkthrough
session_date: 2026-01-16
duration: "35m 03s"
participants:
  - Michelle Healy
  - Desmond Leo
product_area: "Quant Surveys / reporting"
tags: [quant-surveys, reporting, workflow-evidence, internal-practitioner]
---

# Michelle Healy survey-data-to-slide workflow

## Source file

- [survey-data-to-slide-workflow-transcript.docx](./survey-data-to-slide-workflow-transcript.docx) — original Microsoft Teams transcript export.
- [Processed opportunity analysis](../../../opportunities/michelle-data-to-slide-walkthrough.md) — earlier coding and product mapping.

## Evidence relevant to launch

- Researchers need most questions charted before they can see patterns and shape the story (2:17).
- Michelle rebuilds charts in PowerPoint because exports can be “quite fiddly” and often do not justify the setup effort (13:13).
- Manual labels and legends create “a lot of room for errors” (25:11 and 27:41).
- Rechecking text, colours and axes takes substantial time across a deck (26:36).

## What this supports

Quant reporting has a documented manual-work and error-risk problem. It supports presentation-safe outputs and faster reporting as product jobs.

## What this does not prove

This was an internal practitioner workflow interview. It does not prove purchase intent, broad demand, or that the current AI-summary output solves the complete reporting job.