Smart Windows for Balloon Capacity

Summary

Confidential Company is launching balloon services to support both simple and complex event-based orders. This is a direct response to Confidential Company B going out of business. These orders are highly time- and labor-intensive, requiring careful orchestration to ensure product quality. To deliver a reliable customer experience and maintain operational efficiency, we propose extending Smart Windows with balloon-specific capacity controls that are dynamically enforced via API.

Problem Statement: Capacity Management for Balloon Inflation

Balloon inflation introduces distinct operational complexities:

- Time-Sensitive Fulfillment: Balloons must be inflated shortly before pickup or delivery to preserve float time and quality.

- Labor-Intensive Prep: Orders may involve hundreds of units, requiring significant time and labor.

- Scheduling Complexity: Capacity must align with employee availability, and scheduling needs to support events booked up to 30 days in advance.

- Operational Variability: Demand spikes during peak seasons (e.g., holidays, graduations), necessitating dynamic capacity overrides.

Without a smart, enforceable scheduling system, stores risk overpromising and underdelivering, leading to customer dissatisfaction and operational strain.

Proposed Solution: Balloon-Specific Smart Windows

To address these challenges, we propose enhancing Smart Windows with capacity logic tailored for balloon services. This includes centrally-managed configuration, API-driven enforcement, and the ability to dynamically adjust windows based on operational inputs.

Requirements

1. Smart Window Configuration

- Define fulfillment windows specific to balloon services.
- Phase 1: BOPIS (Buy Online Pickup In-Store) support.
- Phase 2: SDD (Same-Day Delivery) support, using a shared capacity pool.

2. Item-Level Capacity Management

- Set capacity based on the item category and number of balloon units per time window
- Example: An arch requiring 100 balloons uses 100 capacity units.

3. API-Based Capacity Updates

- DS will provide an API allowing:
 - Capacity updates by time window.
 - Time Window Overrides during peak seasons.

4. Capacity Enforcement via Order Data

- DS will:
 - Read balloon SKUs from incoming orders.
 - Track cumulative balloon count for each time window.
 - Remove time windows from future API responses once capacity is reached.

5. Pick/Pack Time Constraints

- Configure a buffer between order placement and fulfillment to allow for preparation and inflation.
- Prevent customers from choosing time windows that don’t allow for sufficient prep time.

Additional Considerations

Item Classification

- Define rules for what counts as a balloon unit.
- Determine whether all balloon SKUs consume the same capacity or require weighted handling (e.g., helium vs air-filled, foil vs latex).

Monitoring & Alerting

- Define if over-capacity attempts should be logged.
- Consider alerting thresholds or dashboards for store and corporate oversight.

Configuration Ownership

- Initial assumption: Capacity and window configuration will be centrally managed, but discovery is needed on store-level configuration permissions

Revenue & Volume Projects

Confidential Company B Same Day Delivery volume: 25k per week - October 40k per week

  • Estimate: 1.2 million same day delivery orders
  • BOPIS: ~4million

5million @ $.50 = $2.5M

Currently $.73/order for same day orchestration for $170k ARR