Explanation

Why B is Correct:
Risk Mitigation (Partitioning): By breaking 20 million subscribers into logical blocks (e.g., by region, customer segment, or account number ranges), you can manage the data load in "waves." This prevents hitting Salesforce platform limits and allows the team to validate data integrity in smaller, manageable increments.

On-Demand "Just-in-Time" Migration: This is the most critical part of the strategy. If a customer who has not yet been migrated via the background bulk process calls in or logs into the portal, the system triggers an on-demand migration (usually via an Integration Procedure or middleware). This ensures the agent can process the order immediately without waiting for the scheduled block migration.

Operational Continuity: This "hybrid" approach ensures that sales and support operations are never interrupted. The legacy system remains the source of truth for non-migrated data until the final cutover for that specific block.

Incorrect Answers:
A is incorrect because while it mentions bulk migration, it doesn't emphasize the partitioning required for 20 million records. Without partitioning, a simple "bulk" strategy on such a massive scale is likely to fail or run into severe performance issues.

C is incorrect because the phrasing "on demand migration data when migrations occurs" is logically inconsistent. On-demand migration is needed specifically for data that has not yet been migrated.

D is incorrect because a Tier 1 Telco cannot afford to "disable the production system." Furthermore, migrating 20 million complex subscriber records (including Assets, Subscriptions, and Billing accounts) cannot be accomplished in a few "off-peak hours."

References:
Salesforce Architects: – Discusses the "trickle" and "phased" migration approaches.
Salesforce Help: – Recommends testing with subsets and partitioning large datasets.
Vlocity Success Framework: The Migration Playbook – "For Tier 1 operators, use an 'On-Demand' trigger to pull subscriber data into the SFI data model during the first interaction if the bulk load hasn't reached them yet."

Explanation:

Why A is Correct:
For a data migration of millions of records, it is a Salesforce best practice to notify support in advance. Opening a case allows Salesforce to monitor performance, allocate resources, and temporarily adjust governor limits if needed, ensuring the load does not disrupt org stability.

Why C is Correct:
Migrating millions of historical orders will significantly increase data volume in key objects (Order, OrderItem, FulfilmentRequest, etc.). This can degrade query performance, reporting speed, and increase risk of hitting Large Data Volume (LDV) limits unless archiving or data segregation strategies are implemented.

Why D is Correct:
Orders reference products. To maintain data integrity and avoid broken relationships, you must also migrate all products (Commercial and Technical) that were sold in those orders, even if they are discontinued. This expands the scope and complexity of the migration.

Why B is Incorrect:
Order Management can process large volumes if properly architected. While performance must be monitored, stating it will outright fail is incorrect—it’s a scalability challenge, not a guaranteed failure.

Why E is Incorrect:
The requirement is to migrate orders, not assets. Migrating assets instead would not meet the business need for historical order reporting and auditing. While assets provide value, they do not replace the requirement for order records.

Reference:
Salesforce Large Data Volume (LDV) guidelines and Data Migration Best Practices advise pre-notifying support, evaluating performance impacts of volume increases, and ensuring referential integrity by migrating all related master data (like Products).

Explanation:

Automated Retry Policies: Industries OM includes a native Fallout Management framework. When a callout to an external system (like an inventory management system) fails due to a timeout or a recoverable error, you can define Retry Policies.
Reduced Manual Intervention: Instead of the task staying "stuck" for days, the system automatically requeues the fulfillment request to retry at specified intervals (e.g., retry 3 times every 15 minutes). This resolves transient network issues or temporary system outages without requiring human support.
Fallout States: If the retry limit is reached, only then does the system move the task into a "Fallout" state for manual inspection, significantly reducing the volume of manual work.

Why other options are incorrect

A & B (Load Balancing): While Industries OM uses orchestration queues to manage processing, load balancing is used to optimize performance and throughput, not to resolve functional failures or stuck callouts.
D (Fallout Analysis): While Industries OM provides reporting and analysis for fallout, it does not use the report itself to automatically queue retries. The retry logic must be predefined in the Orchestration Item's Error Handling settings.

Reference:
Salesforce Industries Order Management: Handling Order Fallout

Explanation:

Why B is Correct:
As order volume scales, the "chattiness" of the orchestration engine increases.

Async Apex Callouts: Most fulfillment integrations are asynchronous. High order volume directly consumes the Asynchronous Apex limit (default is 250,000 per 24 hours or a factor based on user licenses). If these limits are hit, orchestration items will fail to execute or move into a "Failed" state.

Platform Events: Order Management uses Platform Events to move orders through different states (Decomposition to Orchestration). An increase in orders means an increase in event publishing and delivery. If the hourly/daily platform event limits are exceeded, order processing will stall.

Why C is Correct:
Platform Events Mode is a high-scale processing setting for Order Management Standard.

Efficiency: When enabled, the OM engine switches from a purely synchronous/transactional model to an event-driven architecture. This offloads the processing of order decomposition and orchestration to the Event Bus.

Stability: This mode significantly reduces the risk of hitting Apex CPU Time and SOQL query limits during high-volume order submissions. It allows Salesforce to process a much higher throughput of orders by decoupling the initial order submission from the complex background fulfillment tasks.

Incorrect Answers:
A is incorrect: Enterprise Sales Management (ESM) is specifically designed for B2B (Business-to-Business) use cases involving thousands of line items in a single multi-site quote. The prompt specifies a B2C (Business-to-Consumer) business, which typically involves many individual small orders rather than one massive order that needs splitting.

D is incorrect: While MuleSoft is an excellent integration layer, simply "employing" it doesn't solve the core issue of Salesforce resource consumption if the OM engine itself isn't optimized. Furthermore, for B2C scale, the focus should be on native Salesforce scalability features (like Platform Events Mode) rather than shifting the burden to a third-party middleware as a first step.

Explanation:

Cardinality Min as 0: This configuration allows users to opt out of the product, meaning the minimum quantity required for the bundle is 0. Cardinality Max as 1: This enforces the rule that users cannot take more than one of Product A per bundle, setting the maximum allowed quantity.
Default as 1: This ensures that Product A is included every time Bundle B is sold by setting the initial default quantity to 1. Users can then manually change it to 0 if they wish to opt out, satisfying the "can opt out" requirement.

Why other options are incorrect
B. Configure the cardinality Min as 1, Max 1 and default as 1: This would make Product A mandatory, as the minimum quantity is 1. Users would not be able to opt out, which contradicts the requirement.
C. Add an Auto Add rule to include product A with bundle B: An "Auto Add" rule would typically add the product automatically, but it might not provide the necessary control over the maximum quantity and might not allow for a clear opt-out. The cardinality settings are the standard and most explicit way to manage this behavior within a bundle structure.
D. Add a Recommendation rule for Product A when bundle B is added: A recommendation rule suggests a product to the user but does not automatically add it to the bundle. The user would have to manually add the product, which contradicts the requirement that it should be included "every time" the bundle is sold.