Workflow Best Practices: Building Reliable Automations

Every workflow will encounter errors. Plan for it.

Error Handling Pattern:

TRY: Do the main thing
CATCH Error:
Step 1: Log the error (for debugging)
Step 2: Notify person
Step 3: Either retry or escalate

Do not trust input data blindly.

Validation Checklist:

• Is required field present
• Is format correct (email is email, phone is phone)
• Is value within expected range
• No obviously bad data (email at test.local, phone equals 123)

Example:

Every workflow should log start time, input data, key decisions made, errors encountered, end result, and total time.

Best Practice: Create a log entry in a spreadsheet or database.

Best practices:

Your workflow will encounter empty fields, very long strings, special characters, unusual formats, missing data, and duplicate data.

For each workflow, maintain:

1. Purpose: Why does this exist
2. Owner: Who maintains it
3. Frequency: When or how often does it run
4. Integration Map: What systems connect
5. Known Limitations: What it cannot do

Track these metrics:

• Success Rate: Is it working - Daily
• Avg Execution Time: Is it slow - Daily
• Error Rate: Are issues increasing - Daily
• Cost: Are we overspending - Weekly
• Manual Escalations: How many need human review - Weekly

After 1 week of running:

1. Check success rate
2. Identify top errors
3. Fix the biggest problems
4. Deploy improvements
5. Repeat

Before deploying to production:

• Does it handle sensitive data securely
• Are API keys stored safely (not in code)
• Does it comply with data privacy laws
• Is access controlled (who can modify or view)
• Are logs retained for audit purposes
• Is there a backup or recovery plan

Better than trying to handle 100 percent (creates brittle complex workflows) or handling 50 percent (leaves too much manual work).

This balance gives you 80 percent automation (massive time savings), 20 percent human review (maintains quality), and a reliable system (simple, maintainable).