Mohamed Imran

🚀 5-Part Enterprise Automation Series

Role: Sr.salesforce Admin/Consultant & Architect | Stack: Advanced Flow, Custom Metadata, Tableau, External Services

Overview

This series demonstrates 5 real-world solutions to complex enterprise problems, utilizing 100% declarative tools (No-Code). Each episode focuses on scalable architecture, separating business logic (Custom Metadata) from automation (Flow) to ensure maintainability.

📺 Episode 1: Smart Discount Guardrails (CPQ)

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The Business Problem

Sales teams were pushing high discounts to close deals without justification, eroding margins. Leadership needed a clear “approval story,” but the logic lived in people’s heads, leading to inconsistent enforcement.

The Solution

I built a lightweight guardrail on the Quote object using a Before-Save Flow (Fast Field Updates).

Configuration: The discount threshold (e.g., 30%) is stored in Custom Metadata (Quote_Discount_Policy__mdt), allowing Admins to update the % without editing the Flow.
Logic: The Flow blocks the save if Additional Disc % > Threshold AND Discount Reason is blank.

🎥 Watch the Video Demo

📸 Implementation Gallery

1. Data Model & Governance

Custom Metadata stores the policy (Rule Separation), while the Quote object holds the validation field. Discount Reason Field Custom Metadata Type Threshold Field

2. Flow Architecture

The “Fast Field Update” Flow fetches the policy and validates input before the database commit. Full Flow Canvas Start Element Get Active Policy Decision Logic Custom Error Configuration

3. User Experience

The result: A clean, inline error message that guides the user to fix the data. Error Message in Action Additional Config

📺 Episode 2: Smart Case Escalation (Scheduled Paths)

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The Business Problem

High-priority cases were missing SLAs because escalation relied on manual tracking. There was no consistent way to route overdue cases to the right queue at the right time.

The Solution

Routing Logic: A Scheduled Path Flow runs on the Case object. It checks if the Case is still open as the SLA approaches.
Configuration: A Custom Metadata Type maps Priority → SLA Minutes → Target Queue.
Action: Automatically reassigns the case to the correct Escalation_Queue and stamps an escalation reason without human intervention.

🎥 Watch the Video Demo

📸 Implementation Gallery

Logic & Configuration

The Flow manages both immediate updates and scheduled escalation checks. Flow Canvas Custom Metadata Policy Queue Configuration

📺 Episode 3: Customer Health Signal Hub (Event-Driven)

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The Business Problem

Customer health data (usage, billing, NPS) lived in external systems. Sales reps were “blind” to churn risks until it was too late.

The Solution

I architected an Event-Driven architecture using Platform Events:

Ingestion: External systems publish to Account_Health_Signal__e (High Volume Platform Event).
Processing: A Platform Event-Triggered Flow receives the signal, finds the related Account, and updates the Health_Status__c.
Action: If the status turns “Red,” the Flow auto-generates a High-Priority Task for the Account Owner.

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📸 Implementation Gallery

Architecture & Automation

Handling high-volume events and automating the response. Platform Event Definition Subscriber Flow Screen Flow Publisher

The User Experience

Sales reps see real-time history and get immediate tasks for risks. Send Signal Action Input Screen Health History Record Auto-Generated Task

📺 Episode 4: Fair Workload Engine (Tableau Integration)

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The Business Problem

Support cases and urgent tasks were piling up on the same few high-performers, leading to burnout. Managers lacked data to prove overload.

The Solution

Scoring Engine: A Scheduled Flow runs nightly to calculate a “Workload Score” for every user based on Open Cases, Complexity, and Overdue Tasks.
Snapshotting: The score is saved to a User_Workload_Snapshot__c record.
Visualization: Data is pushed to Tableau to generate a “Heat Map,” allowing managers to visualize burnout risk across the team.

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📸 Implementation Gallery

Analytics & Logic

Calculating the score and visualizing the risk. Tableau Heatmap Calculation Flow Risk Assignment Logic Routing Logic

📺 Episode 5: Real-Time Credit Risk Engine (No-Code Integration)

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The Business Problem

Sales reps were negotiating deals with clients who had poor credit, leading to rejected contracts. The credit check process was manual and slow (email-based).

The Solution

I built a No-Code Integration using External Services:

Integration: Ingested a Swagger/OpenAPI schema to connect Salesforce to an external Banking API.
Automation: When an Opportunity reaches “Negotiation,” an HTTP Callout (GET) fetches the real-time credit score.
Security: Uses Named Credentials to handle authentication securely without Apex.

🎥 Watch the Video Demo

📸 Implementation Gallery

Integration Architecture

Connecting Salesforce to the Banking API securely. External Services Setup Named Credentials Permission Sets Mocking Rules

Flow Automation

Handling the API call asynchronously to prevent timeouts. Async Path Flow Data Cleanup Flow

Final Result

Real-time credit data appears instantly on the Opportunity. Opportunity View Details Panel

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