# Explore a deterministic queue-drain scenario

Illustrative planning brief; no automatic product import.

Synthetic planning case: An invented queue opens with twelve requests. Each day two arrive before a review window that can finish five distinct requests. Capacity and arrival counts are held fixed in this scenario.

## Decision

The queue falls by three requests per day and reaches zero after four scenario days. Label this a deterministic illustration, not a calibrated clearance forecast.

## Owned work

- Declare fixed scenario inputs
  - Owner role: Planning owner
  - Acceptance evidence: Two arrivals and five accepted exits per day are assumptions, not observed guarantees.
- Track the daily balance
  - Owner role: Queue coordinator
  - Acceptance evidence: Each day preserves opening plus arrivals minus exits.
- Check the assumptions before commitment
  - Owner role: Receiving lead
  - Acceptance evidence: Different arrival, eligibility or review rates trigger a new scenario rather than a four-day promise.

## Workflow

1. Declare fixed scenario inputs. Check: Two arrivals and five accepted exits per day are assumptions, not observed guarantees.
2. Track the daily balance. Check: Each day preserves opening plus arrivals minus exits.
3. Check the assumptions before commitment. Check: Different arrival, eligibility or review rates trigger a new scenario rather than a four-day promise.

## Judgment

No stochastic queue model or confidence interval is supplied. Timing of arrivals and service is part of the declared example.


## Filled manual planning note

The queue falls by three requests per day and reaches zero after four scenario days. Label this a deterministic illustration, not a calibrated clearance forecast. Net reduction=5−2=3 per day; 12/3=4 days. Gross service of five is not the net queue-drain rate while two new requests continue arriving. No stochastic queue model or confidence interval is supplied. Timing of arrivals and service is part of the declared example.


## Workflow questions

### What if daily arrivals reach five?

Under the same service assumption there is no net reduction; this four-day result no longer applies.

### Does historical average service justify the fixed daily input?

Not alone. Variability and future context remain unmodelled.

## Product connection

Use the owned checks and downloaded brief to discuss this planning decision alongside your TeamBoostAI tasks. Confirm available fields, roles and account features separately. The example is manual; it does not calculate live analytics, create work or run an experiment in the product.

Confirm account availability before adopting this manual outline.

## Original worked case

Synthetic records, manual planning only. No account import or live analytics.

### Inspect the invented case records

Scenario day | Opening | Arrivals | Accepted exits | Closing
--- | --- | --- | --- | ---
1 | 12 | 2 | 5 | 9
2 | 9 | 2 | 5 | 6
3 | 6 | 2 | 5 | 3
4 | 3 | 2 | 5 | 0

### Reasoning

Net reduction=5−2=3 per day; 12/3=4 days. Gross service of five is not the net queue-drain rate while two new requests continue arriving.

### Bounded result

The queue falls by three requests per day and reaches zero after four scenario days. Label this a deterministic illustration, not a calibrated clearance forecast.

### Distinct decision

The decision distinguishes net backlog reduction from gross processing capacity.

### Limits

No stochastic queue model or confidence interval is supplied. Timing of arrivals and service is part of the declared example.

### Definitions and method context

- The Kanban Guide — https://kanbanguides.org/the-kanban-guide/ — Workflow and flow-measure context. Queue policies and staffing scenarios are explicitly local examples, not delivery guarantees.