The Challenge
"Our Salesforce Org works, but it's getting slower, harder to change, and riskier every release."
Accumulated inactive metadata, redundant automations, outdated API versions, hard-coded references, high record volumes, and over-engineered Apex create fragility over time. Every new feature takes longer. Performance degrades. Fear of change increases.
Steps to Take
Important: Technical debt is abstract. The goal is to quickly surface tangible evidence — inactive metadata, automation sprawl, API drift, or hard-coded references. Your first experience should expose uncomfortable facts.
Step 1: Connect & Sync Your Salesforce Org
Before analysing anything, make sure your org is connected and synced.
Feature: Salesforce Sync (Salesforce Connect)
Support Article: Connect and Sync a Salesforce Org
📹 Video walkthrough available
Tip: The metadata dictionary is only as accurate as the latest sync. Always confirm sync status before analysing metadata.
Step 2: Understand the Overall State of Tech Debt
Open the Analytics 360 Tech Debt Dashboard
Review how much severe vs high impact tech debt exists in your org
Drill down by clicking into charts to see exactly what the tech debt is
Check outdated API versions of automations — running on old API versions means missing out on Salesforce's built-in performance improvements, bug fixes, and new features
Step 3: Understand Tech Debt Spread Across Key Objects
Using the Object Analysis Dashboard, configure a custom dashboard to see inactive automations per object. Include record types, Apex triggers, and other metadata to identify which objects carry the most tech debt.
Using Analytics 360, open the % filled for fields in Objects chart to see how many fields are unused across your org.
Step 4: Understand Tech Debt in Your Automations
Automations are the bloodline of your org — and often where the most fragility lives.
Using the Automation Dashboard in Analytics 360, review the overall state of your Apex and Flows. Pay particular attention to:
Test/fault coverage — higher coverage = more reliable automations
Complexity — high complexity means automations are harder to change and slow to update, though they can always be broken into smaller components
Review high record counts across your objects. Anything above 50,000 records per object creates performance issues for automations.
Identify and remove hard-coded references in code — hard-coded values are not secure, error-prone, and easy to break.
What You'll Learn
After completing these steps, you'll shift from "our org feels messy" to having clear answers:
I understand how much tech debt we really have
I know where the tech debt is concentrated — which objects carry disproportionate automation density and risk
I know how significant an issue it is for our team and our planned projects
Decisions You Can Now Make
With this insight, the following actions become possible:
Prioritise tech debt removal before building new features
Quantify the impact of tech debt on key capabilities and planned projects
Make the business case — explain clearly why changes take longer than expected, backed by data
Without quantified insight, clean-up never wins against feature pressure. With evidence, it becomes defensible.