Workflow Automation Suite

I identified systemic bottlenecks across our guidebook production pipeline and built an integrated automation suite using Google Apps Script, with AI as a development partner. No formal engineering background—just a willingness to learn, interview stakeholders, and iterate until the systems worked.

The Problem

Our guidebook production process had accumulated years of manual overhead. Aging print-era systems were full of redundancies and friction: copy this file to this folder, ensure this specific payment amount appears in a variety of forms, files, and contracts. Across 200+ guidebooks annually, these inefficiencies crushed team capacity.

The fee calculator—which takes in several inputs including word counts, author payment profiles, and estimated expenses—was overcomplicated and brittle. Getting fees in place to trigger payments was a laborious process, requiring editors to manually copy data into an Asana form and contracts separately. Each manual transmission point introduced errors, and editors spent hours on administrative overhead that pulled them away from actual editorial work.

The Solution

Although I had experience in the guidebook process as a destination editor, I needed to understand the current workflow more deeply before I could fix it. I took on the role of commissioning editor myself—working on Colombia, 9th Edition—and spent time getting to know our systems firsthand. I also interviewed other editors and teams across the organization to see how they operated and where the pain points overlapped.

That research led me to a core insight: the biggest time sink wasn’t any single task, but the repeated manual data transmission between disconnected systems. The solution was an integrated pipeline where data is entered once and flows across all necessary touchpoints.

I built the suite through Google Apps Script, using Claude and ChatGPT as development partners:

Project Setup Tool automates folder creation and initialization with the correct directory structure, eliminating the manual copying of templates. Saves 11 hours per year.

Fee Calculator simplifies the calculation process so editors can arrive at accurate writer fees more quickly, replacing the brittle legacy spreadsheet with a streamlined interface.

Asana Integration connects the fee calculator directly to our payment triggers in Asana, eliminating the manual form-filling step entirely.

Contract Generator takes the same data and produces a contract from a template that editors can send to writers with the click of a button. Together with the fee calculator and Asana integration, this pipeline saves 154 hours per year.

Database Sync Tool eliminated 24-hour wait times for tax classification lookups, saving 5+ hours per year.

SEO ChatGPT Advisor integrated Asana with ChatGPT for automated article analysis, saving 250 hours per year across the editorial team.

DocuSign Replacement provided an e-signature workflow that cut external software costs and reduced contract processing from days to minutes.

Development Approach

All of these tools have run reliably for 2+ years across 200+ projects. I taught myself Google Apps Script using AI as a development partner, building a repeatable process: map requirements through stakeholder interviews, prototype with AI assistance, iterate through testing with real editors, and document for team maintenance.

Impact

• 420+ hours returned annually—equivalent to 10+ weeks of full-time work
• Improved accuracy by reducing manual data transmission to a single-entry workflow where data flows automatically across forms, contracts, and payment systems
• Eliminated external software costs through the DocuSign replacement
• Production systems running 2+ years across 200+ projects with no maintenance downtime
• Created a repeatable AI-assisted development model that I’ve since applied to other automation challenges