I once spent three weeks building what I thought was a brilliant customer segmentation analysis. I presented it to the marketing team, they nodded politely, and then… nothing changed. A month later, I discovered they were still using the same old manual spreadsheet. The problem wasn’t my analysis—it was that my insights were trapped in my R environment.
Publishing your work isn’t just the final step—it’s what separates interesting analysis from actual impact. Here’s how to get your work into the hands of people who can use it.
Choosing the Right Format for Your Audience
Different stakeholders need different things. The same analysis might need to be presented three different ways:
For Executives: The One-Pager
yaml
—
title: “Q3 Performance Snapshot”
format:
pdf:
toc: false
include-in-header:
text: |
<style>
body { font-family: Arial; font-size: 14pt; }
.main-container { max-width: 800px; margin: 0 auto; }
</style>
—
For Technical Teams: Interactive Dashboard
yaml
—
title: “Customer Behavior Explorer”
format:
html:
theme: flatly
toc: true
code-fold: true
—
For Public Sharing: Simple Web Page
yaml
—
title: “Our Methodology”
format:
html:
theme: journal
css: styles/simple.css
—
Building an Internal Analytics Portal
Instead of emailing reports around, create a central hub where people can find what they need:
Setting Up a Quarto Website
Create a _quarto.yml file:
yaml
project:
type: website
website:
title: “Company Analytics Hub”
navbar:
left:
– href: index.qmd
text: “Home”
– href: sales.qmd
text: “Sales Dashboard”
– href: marketing.qmd
text: “Marketing Insights”
– href: operations.qmd
text: “Operations Metrics”
right:
– href: about.qmd
text: “About & Methods”
format:
html:
theme: cosmo
css: styles/corporate.css
Then build it with:
bash
quarto render
Your entire analytics portal generates as static HTML that you can host anywhere—no special servers required.
Automated Publishing That Actually Works
The key to successful publishing is making it automatic. If people have to ask you for updated reports, you’ve already lost.
GitHub Actions for Zero-Effort Updates
Create .github/workflows/publish-reports.yml:
yaml
name: Publish Daily Reports
on:
schedule:
– cron: ‘0 6 * * 1-5’ # 6 AM weekdays
push:
branches: [main]
jobs:
build-and-deploy:
runs-on: ubuntu-latest
steps:
– name: Checkout code
uses: actions/checkout@v3
– name: Setup R
uses: r-lib/actions/setup-r@v2
– name: Install dependencies
run: |
Rscript -e ‘install.packages(c(“tidyverse”, “quarto”))’
Rscript -e ‘quarto::quarto_install()’
– name: Render reports
run: |
quarto render sales.qmd
quarto render marketing.qmd
quarto render operations.qmd
– name: Deploy to internal server
uses: appleboy/[email protected]
with:
host: ${{ secrets.SERVER_HOST }}
username: ${{ secrets.SERVER_USER }}
key: ${{ secrets.SERVER_KEY }}
source: “*.html”
target: “/var/www/analytics/”
Now your reports update themselves every weekday morning before anyone even arrives at work.
Cloud Publishing Options That Scale
GitHub Pages for Public-Facing Work
Perfect for research papers, open data projects, or public methodology documentation:
bash
# Enable in your repository settings
quarto publish gh-pages
Netlify for Team Documentation
Great for internal knowledge bases:
bash
quarto publish netlify
RStudio Connect for Enterprise
For organizations that need security and access controls:
r
rsconnect::deployDoc(
doc = “sales_dashboard.qmd”,
appName = “sales-dashboard”,
account = “company”,
server = “https://connect.company.com”
)
Making Your Work Discoverable
A beautiful report nobody can find is useless. Here’s how to make sure people actually see your work:
Create a Landing Page
Your index.qmd should be a dashboard of dashboards:
markdown
# Analytics Portal
## Quick Access
– 📈 [Live Sales Dashboard](/sales.html) – Updated hourly
– 👥 [Customer Insights](/customers.html) – Segmentation and behavior
– 📊 [Weekly Performance Report](/weekly.html) – Monday morning summary
## By Department
### Marketing
– [Campaign Performance](/marketing/campaigns.html)
– [Lead Generation Metrics](/marketing/leads.html)
### Sales
– [Pipeline Analysis](/sales/pipeline.html)
– [Regional Performance](/sales/regions.html)
### Product
– [User Engagement](/product/engagement.html)
– [Feature Usage](/product/features.html)
Set Up Automated Notifications
When important reports update, let people know:
r
send_report_notification <- function(report_name, recipients) {
library(blastula)
email <- compose_email(
body = md(sprintf(
“The %s report has been updated with the latest data.\n\n”,
report_name,
“View it here: https://analytics.company.com/%s”,
report_name
))
)
smtp_send(
email,
to = recipients,
from = “[email protected]”,
subject = paste(“Updated:”, report_name)
)
}
# Call this after publishing
send_report_notification(“Weekly Sales Report”, c(“[email protected]”, “[email protected]”))
Handling Sensitive Information
Not everything should be public. Here’s how to publish securely:
Password Protection
yaml
—
title: “Confidential Financial Analysis”
format:
html:
include-in-header:
text: |
<script>
if (prompt(‘Enter password:’) !== ‘company123’) {
document.body.innerHTML = ‘<h1>Access Denied</h1>’;
}
</script>
—
Internal-Only Publishing
Use your company’s authentication system:
r
# Only publish to internal network
if (Sys.info()[“nodename”] == “internal-server”) {
quarto::quarto_render(“confidential_analysis.qmd”)
}
Creating Living Documentation
The best published analysis evolves with your organization:
Version Control for Reports
bash
# Tag important versions
git tag -a “v1.0-q3-results” -m “Q3 2025 final results”
git push origin –tags
Archive Important Snapshots
r
archive_report <- function(report_path, description) {
timestamp <- format(Sys.time(), “%Y%m%d_%H%M”)
archive_name <- paste0(“archives/”, tools::file_path_sans_ext(basename(report_path)),
“_”, timestamp, “.html”)
file.copy(report_path, archive_name)
# Log the archive
write_lines(
paste(Sys.time(), description, archive_name),
“archives/log.txt”,
append = TRUE
)
}
Measuring Impact and Engagement
If you don’t know who’s using your reports, you’re flying blind:
Simple Analytics Tracking
html
<!– Add to your HTML reports –>
<script>
// Track report views
fetch(‘https://analytics.company.com/track’, {
method: ‘POST’,
body: JSON.stringify({
report: ‘sales-dashboard’,
user: ‘internal-user’, // From company SSO
timestamp: new Date().toISOString()
})
});
</script>
Feedback Mechanisms
r
# Add a feedback section to your reports
cat(‘
<div class=”feedback”>
<h3>Was this helpful?</h3>
<button onclick=”sendFeedback(\’yes\’)”>👍 Yes</button>
<button onclick=”sendFeedback(\’no\’)”>👎 No</button>
<button onclick=”showCommentBox()”>💬 Suggest improvement</button>
</div>
‘)
Collaboration and Peer Review
Make it easy for others to contribute:
Template Repositories
Create starter templates so other teams can publish their own analysis:
yaml
# template/_quarto.yml
project:
type: website
website:
title: “Team Analytics Site”
navbar:
left:
– href: index.qmd
text: “Home”
– href: analysis.qmd
text: “Our Analysis”
format:
html:
theme: cosmo
Review Workflows
Use GitHub’s pull request system for collaborative editing:
bash
# Create a branch for your changes
git checkout -b update-sales-metrics
# Edit your report
quarto render sales.qmd
# Submit for review
git add sales.qmd sales.html
git commit -m “Update sales metrics methodology”
git push origin update-sales-metrics
# Then create a pull request for team review
Conclusion: From Analysis to Organizational Asset
The turning point for our analytics team came when we stopped thinking of ourselves as “people who do analysis” and started thinking of ourselves as “people who provide insights.” The difference was publishing.
When you publish effectively:
- Your work finds its audience instead of sitting on your hard drive
- Decisions get made with current data instead of guesses
- Your impact multiplies as people build on your work
- You create institutional knowledge that outlasts any individual
Start small. Take one analysis you’re proud of and publish it somewhere people can actually use it. Set up one automated report. Create one dashboard that updates itself.
The tools have never been better. The barriers have never been lower. What separates impactful data professionals from the rest isn’t their analytical skill—it’s their ability to get their work into the world where it can make a difference.
Your analysis is too valuable to keep to yourself. Publish it, share it, and watch what happens when good data meets good decisions.