https://github.com/harshproj/narwal-rqueries
https://github.com/harshproj/narwal-rqueries
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- Host: GitHub
- URL: https://github.com/harshproj/narwal-rqueries
- Owner: HarshProj
- Created: 2025-03-11T07:18:06.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-03-11T07:53:37.000Z (over 1 year ago)
- Last Synced: 2025-03-11T08:27:54.846Z (over 1 year ago)
- Size: 18.6 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Narwal-rqueries
## ** Average cost per PO (USD) - Monthly average cost for delivery per PO that have completed last mile delivery within the month**
# Delivery Cost Analysis
## Overview
This document provides insights into two different SQL queries:
1. **Imports Analysis** - Tracks purchase orders (POs) and total invoice values.
2. **Delivery Cost Tracking** - Provides accurate cost tracking for deliveries with currency conversion.
## Query 1: Imports Analysis
```sql
SELECT
DATE_TRUNC('month', import_timestamp) AS month,
COUNT(id) AS total_pos,
SUM(total_invoice_value) AS total_cost,
ROUND(AVG(total_invoice_value), 2) AS avg_cost_per_po
FROM public.imports
WHERE DATE_PART('month', import_timestamp) = DATE_PART('month', import_timestamp)
AND DATE_PART('year', import_timestamp) = DATE_PART('year', import_timestamp)
GROUP BY month
ORDER BY month;
```
### Purpose:
- Extracts monthly data on purchase orders (POs) and total invoice values.
- Computes total and average cost per PO.
---
## Query 2: Delivery Cost Tracking (Recommended)
```sql
WITH completed_deliveries AS (
SELECT
DATE_TRUNC('month', d.latest_event_timestamp) as month,
d.id as delivery_id
FROM deliveries d
JOIN shipments s ON d.id = s.delivery_id
WHERE s.transport_mode = 'local delivery'
AND d.latest_event_timestamp >= '2024-01-01'
AND d.latest_event_timestamp < '2025-04-01'
),
delivery_costs AS (
SELECT
cd.month,
dq.quotation_id,
-- Convert all costs to USD using approximate exchange rates
SUM(
CASE qsf.currency
WHEN 'USD' THEN qsf.cost * qsf.quantity
WHEN 'EUR' THEN qsf.cost * qsf.quantity * 1.08 -- EUR to USD
WHEN 'JPY' THEN qsf.cost * qsf.quantity * 0.0067 -- JPY to USD
WHEN 'KRW' THEN qsf.cost * qsf.quantity * 0.00075 -- KRW to USD
ELSE qsf.cost * qsf.quantity -- Default to original value if currency not handled
END
) as total_cost_usd
FROM completed_deliveries cd
JOIN delivery_quotations dq ON cd.delivery_id = dq.delivery_id
JOIN quotation_schedules qs ON dq.quotation_id = qs.quotation_id
JOIN quotation_schedule_fees qsf ON qs.id = qsf.schedule_id
GROUP BY cd.month, dq.quotation_id
)
SELECT
month,
COUNT(DISTINCT quotation_id) as number_of_deliveries,
SUM(total_cost_usd) as total_cost_usd,
ROUND(AVG(total_cost_usd), 2) as avg_cost_per_delivery_usd
FROM delivery_costs
GROUP BY month
ORDER BY month DESC;
```
### Purpose:
- Tracks the number of deliveries per month.
- Converts delivery costs into **USD** for accurate cost analysis.
- Calculates total and average cost per delivery.
---
## Query Output
```json
{
"success": true,
"data": [
{
"month": "2025-01-31T18:30:00.000Z",
"number_of_deliveries": "294",
"total_cost_usd": "52100304.19150000000000000",
"avg_cost_per_delivery_usd": "177211.92"
},
{
"month": "2024-12-31T18:30:00.000Z",
"number_of_deliveries": "185",
"total_cost_usd": "1763409.60625000000000000",
"avg_cost_per_delivery_usd": "9531.94"
},
{
"month": "2024-11-30T18:30:00.000Z",
"number_of_deliveries": "156",
"total_cost_usd": "179175.51185000000000000",
"avg_cost_per_delivery_usd": "1148.56"
},
{
"month": "2024-10-31T18:30:00.000Z",
"number_of_deliveries": "5",
"total_cost_usd": "3893.40000000000000000",
"avg_cost_per_delivery_usd": "778.68"
}
]
}
```
---
## **Average cost per KG (USD) - Monthly average cost for delivery per PO that have completed last mile delivery within the month**
# Delivery Cost and Weight Report
## SQL Query
```sql
WITH completed_deliveries AS (
SELECT
DATE_TRUNC('month', d.latest_event_timestamp) as month,
d.id as delivery_id
FROM deliveries d
JOIN shipments s ON d.id = s.delivery_id
WHERE s.transport_mode = 'local delivery'
AND d.latest_event_timestamp >= '2024-01-01'
AND d.latest_event_timestamp < '2025-04-01'
),
delivery_weights AS (
-- Get weights from quotation packages
SELECT
cd.month,
cd.delivery_id,
SUM(qp.weight) as total_weight
FROM completed_deliveries cd
JOIN delivery_quotations dq ON cd.delivery_id = dq.delivery_id
JOIN quotation_packages qp ON dq.quotation_id = qp.quotation_id
GROUP BY cd.month, cd.delivery_id
),
delivery_costs AS (
SELECT
cd.month,
cd.delivery_id,
-- Convert all costs to USD using approximate exchange rates
SUM(
CASE qsf.currency
WHEN 'USD' THEN qsf.cost * qsf.quantity
WHEN 'EUR' THEN qsf.cost * qsf.quantity * 1.08 -- EUR to USD
WHEN 'JPY' THEN qsf.cost * qsf.quantity * 0.0067 -- JPY to USD
WHEN 'KRW' THEN qsf.cost * qsf.quantity * 0.00075 -- KRW to USD
ELSE qsf.cost * qsf.quantity -- Default to original value if currency not handled
END
) as total_cost_usd
FROM completed_deliveries cd
JOIN delivery_quotations dq ON cd.delivery_id = dq.delivery_id
JOIN quotation_schedules qs ON dq.quotation_id = qs.quotation_id
JOIN quotation_schedule_fees qsf ON qs.id = qsf.schedule_id
GROUP BY cd.month, cd.delivery_id
)
SELECT
dw.month,
COUNT(DISTINCT dw.delivery_id) as number_of_deliveries,
ROUND(SUM(dw.total_weight), 2) as total_weight_kg,
ROUND(SUM(dc.total_cost_usd), 2) as total_cost_usd,
ROUND(SUM(dc.total_cost_usd) / NULLIF(SUM(dw.total_weight), 0), 2) as avg_cost_per_kg_usd
FROM delivery_weights dw
JOIN delivery_costs dc ON dw.delivery_id = dc.delivery_id AND dw.month = dc.month
WHERE dw.total_weight > 0 -- Exclude deliveries with no weight data
GROUP BY dw.month
ORDER BY dw.month DESC;
```
## Output
```json
{
"success": true,
"data": [
{
"month": "2025-01-31T18:30:00.000Z",
"number_of_deliveries": "3117",
"total_weight_kg": "43264055.42",
"total_cost_usd": "52100304.19",
"avg_cost_per_kg_usd": "1.20"
},
{
"month": "2024-12-31T18:30:00.000Z",
"number_of_deliveries": "1520",
"total_weight_kg": "5405754.09",
"total_cost_usd": "1763409.61",
"avg_cost_per_kg_usd": "0.33"
},
{
"month": "2024-11-30T18:30:00.000Z",
"number_of_deliveries": "441",
"total_weight_kg": "310377.20",
"total_cost_usd": "179175.51",
"avg_cost_per_kg_usd": "0.58"
},
{
"month": "2024-10-31T18:30:00.000Z",
"number_of_deliveries": "5",
"total_weight_kg": "1341.60",
"total_cost_usd": "3893.40",
"avg_cost_per_kg_usd": "2.90"
}...
]
}
```
## **Cargo volumes in CBM - Monthly volume of inbound and outbound cargo in total and also by hub**
# Shipment Volume Report
## Overview
This project provides SQL queries to calculate monthly shipment volumes based on import and export data. Depending on whether shipment records track both imports and exports together or independently, different queries are used to compute the shipment volume.
## Queries
### Query 1: Independent Imports and Exports
Use this query when import and export records are managed separately and shipments do not always track both activities.
```sql
SELECT
DATE_TRUNC('month', s.latest_event_timestamp) AS month,
s.origin_city AS hub,
SUM(COALESCE(ip.cbm, 0)) AS inbound_volume,
SUM(COALESCE(ep.cbm, 0)) AS outbound_volume,
SUM(COALESCE(ip.cbm, 0) + COALESCE(ep.cbm, 0)) AS total_volume
FROM shipments s
LEFT JOIN import_packages ip ON s.id = ip.import_id -- Inbound shipments
LEFT JOIN export_packages ep ON s.id = ep.export_id -- Outbound shipments
WHERE s.latest_event_timestamp IS NOT NULL
GROUP BY month, hub
ORDER BY month DESC, hub;
```
### Query 2: Integrated Shipment Tracking
Use this query when shipment records reliably track both imports and exports.
```sql
WITH monthly_exports AS (
SELECT
DATE_TRUNC('month', e.export_timestamp) AS month,
e.port_from as hub,
SUM(ep.cbm) as total_cbm
FROM exports e
JOIN export_packages ep ON e.id = ep.export_id
WHERE e.export_timestamp IS NOT NULL
GROUP BY DATE_TRUNC('month', e.export_timestamp), e.port_from
),
monthly_imports AS (
SELECT
DATE_TRUNC('month', i.import_timestamp) AS month,
i.warehouse as hub,
SUM(ip.cbm) as total_cbm
FROM imports i
JOIN import_packages ip ON i.id = ip.import_id
WHERE i.import_timestamp IS NOT NULL
GROUP BY DATE_TRUNC('month', i.import_timestamp), i.warehouse
)
SELECT
COALESCE(e.month, i.month) as month,
COALESCE(e.hub, i.hub) as hub,
COALESCE(e.total_cbm, 0) as export_cbm,
COALESCE(i.total_cbm, 0) as import_cbm,
COALESCE(e.total_cbm, 0) + COALESCE(i.total_cbm, 0) as total_cbm
FROM monthly_exports e
FULL OUTER JOIN monthly_imports i
ON e.month = i.month
AND e.hub = i.hub
WHERE COALESCE(e.month, i.month) IS NOT NULL
ORDER BY month DESC, hub;
```
## Output Example
The query returns shipment volumes in the following JSON format:
```json
{
"success": true,
"data": [
{
"month": "2025-11-30T18:30:00.000Z",
"hub": null,
"export_cbm": "19.05800",
"import_cbm": "0",
"total_cbm": "19.05800"
},
{
"month": "2025-01-31T18:30:00.000Z",
"hub": "1F",
"export_cbm": "0",
"import_cbm": "1149.90900",
"total_cbm": "1149.90900"
},
{
"month": "2025-01-31T18:30:00.000Z",
"hub": "ICN",
"export_cbm": "158.67700",
"import_cbm": "0",
"total_cbm": "158.67700"
}...
]
}
```
## **List of High-cost shipment - Monthly list of high-cost delivery (only including shipment cost) that have completed onboard last mile delivery within the month**
# Monthly Shipments Report
## Overview
This SQL query retrieves and aggregates shipment data for the last three months, including details like shipment ID, customer, origin, destination, transport mode, latest event timestamp, total cost, and currency. The results are grouped by month and ordered by the highest total cost within each month, limited to the top 100 records.
## SQL Query
```sql
WITH monthly_shipments AS (
SELECT
s.id as shipment_id,
s.customer,
s.origin,
s.destination,
s.transport_mode,
s.latest_event_timestamp,
DATE_TRUNC('month', s.latest_event_timestamp) as delivery_month,
dq.quotation_id,
SUM(qsf.cost * qsf.quantity) as total_cost,
qsf.currency
FROM shipments s
JOIN deliveries d ON s.delivery_id = d.id
JOIN delivery_quotations dq ON d.id = dq.delivery_id
JOIN quotation_schedules qs ON dq.quotation_id = qs.quotation_id
JOIN quotation_schedule_fees qsf ON qs.id = qsf.schedule_id
WHERE s.latest_event_timestamp >= (CURRENT_DATE - INTERVAL '3 months')
AND s.latest_event_timestamp < CURRENT_DATE
GROUP BY
s.id,
s.customer,
s.origin,
s.destination,
s.transport_mode,
s.latest_event_timestamp,
DATE_TRUNC('month', s.latest_event_timestamp),
dq.quotation_id,
qsf.currency
)
SELECT
TO_CHAR(delivery_month, 'YYYY-MM') as month,
shipment_id,
customer,
origin,
destination,
transport_mode,
TO_CHAR(latest_event_timestamp, 'YYYY-MM-DD') as delivery_date,
ROUND(total_cost, 2) as total_cost,
currency
FROM monthly_shipments
ORDER BY
delivery_month DESC,
total_cost DESC
LIMIT 100;
```
## Output
```json
{
"success": true,
"data": [
{
"month": "2025-02",
"shipment_id": "523809",
"customer": "60YC",
"origin": "JPUKB",
"destination": "JPKII",
"transport_mode": "local delivery",
"delivery_date": "2025-02-14",
"total_cost": "12060690.00",
"currency": "KRW"
},
{
"month": "2025-02",
"shipment_id": "523791",
"customer": "60YC",
"origin": "JPUKB",
"destination": "JPKII",
"transport_mode": "local delivery",
"delivery_date": "2025-02-14",
"total_cost": "12060690.00",
"currency": "KRW"
},
{
"month": "2025-02",
"shipment_id": "523802",
"customer": "60YC",
"origin": "JPUKB",
"destination": "JPKII",
"transport_mode": "local delivery",
"delivery_date": "2025-02-14",
"total_cost": "12060690.00",
"currency": "KRW"
},
{
"month": "2025-02",
"shipment_id": "523804",
"customer": "60YC",
"origin": "JPUKB",
"destination": "JPKII",
"transport_mode": "local delivery",
"delivery_date": "2025-02-14",
"total_cost": "12060690.00",
"currency": "KRW"
},
{
"month": "2025-02",
"shipment_id": "523796",
"customer": "60YC",
"origin": "JPUKB",
"destination": "JPKII",
"transport_mode": "local delivery",
"delivery_date": "2025-02-14",
"total_cost": "12060690.00",
"currency": "KRW"
}
]
}
```
## Explanation
1. **CTE (`WITH monthly_shipments AS (...)`)**:
- Fetches shipment details from the `shipments` table.
- Joins multiple related tables (`deliveries`, `delivery_quotations`, `quotation_schedules`, `quotation_schedule_fees`).
- Filters shipments from the last three months.
- Groups by shipment ID, customer, origin, destination, transport mode, and currency.
- Calculates the `total_cost` for each shipment.
2. **Main Query (`SELECT ... FROM monthly_shipments`)**:
- Formats `delivery_month` as `YYYY-MM`.
- Formats `latest_event_timestamp` as `YYYY-MM-DD`.
- Sorts the results by `delivery_month DESC` and `total_cost DESC`.
- Limits the output to the top 100 shipments.
## //Ratio on freight mode - Monthly ratio of freight modes based on cost, number of POs, and weight. Total ratio including all the shipments and ratio by hub is required.
# Optimized SQL Query for Monthly Shipment Metrics
## Overview
This query calculates monthly shipment metrics, including purchase order count, shipment count, total weight, and total cost in USD. It also computes the ratio of each metric relative to total and hub-specific values.
## Optimized SQL Query
```sql
WITH monthly_metrics AS (
SELECT
DATE_TRUNC('month', s.latest_event_timestamp) AS month,
s.transport_mode,
s.origin AS hub,
COUNT(DISTINCT po.number) AS po_count,
COUNT(DISTINCT s.id) AS shipment_count,
SUM(qp.weight) AS total_weight,
SUM(
CASE qsf.currency
WHEN 'USD' THEN qsf.cost * qsf.quantity
WHEN 'EUR' THEN qsf.cost * qsf.quantity * 1.08
WHEN 'JPY' THEN qsf.cost * qsf.quantity * 0.0067
WHEN 'KRW' THEN qsf.cost * qsf.quantity * 0.00075
END
) AS total_cost_usd
FROM shipments s
LEFT JOIN deliveries d ON s.delivery_id = d.id
LEFT JOIN delivery_quotations dq ON d.id = dq.delivery_id
LEFT JOIN quotations q ON dq.quotation_id = q.id
LEFT JOIN quotation_packages qp ON q.id = qp.quotation_id
LEFT JOIN quotation_schedule_fees qsf ON q.id = qsf.schedule_id
LEFT JOIN export_package_po_numbers epn ON epn.export_package_id = qp.id
LEFT JOIN purchase_orders po ON epn.po_number = po.number
WHERE s.latest_event_timestamp >= '2024-01-01'
AND s.latest_event_timestamp < '2025-04-01'
GROUP BY
DATE_TRUNC('month', s.latest_event_timestamp),
s.transport_mode,
s.origin
),
monthly_totals AS (
SELECT
month,
SUM(po_count) AS total_po_count,
SUM(shipment_count) AS total_shipment_count,
SUM(total_weight) AS total_weight,
SUM(total_cost_usd) AS total_cost_usd
FROM monthly_metrics
GROUP BY month
),
hub_totals AS (
SELECT
month,
hub,
SUM(po_count) AS hub_po_count,
SUM(shipment_count) AS hub_shipment_count,
SUM(total_weight) AS hub_weight,
SUM(total_cost_usd) AS hub_cost_usd
FROM monthly_metrics
GROUP BY month, hub
)
SELECT
mm.month,
mm.hub,
mm.transport_mode,
mm.po_count,
ROUND(mm.po_count * 100.0 / NULLIF(mt.total_po_count, 0), 2) AS po_ratio_total,
ROUND(mm.po_count * 100.0 / NULLIF(ht.hub_po_count, 0), 2) AS po_ratio_hub,
mm.shipment_count,
ROUND(mm.shipment_count * 100.0 / NULLIF(mt.total_shipment_count, 0), 2) AS shipment_ratio_total,
ROUND(mm.shipment_count * 100.0 / NULLIF(ht.hub_shipment_count, 0), 2) AS shipment_ratio_hub,
ROUND(mm.total_weight, 2) AS total_weight_kg,
ROUND(mm.total_weight * 100.0 / NULLIF(mt.total_weight, 0), 2) AS weight_ratio_total,
ROUND(mm.total_weight * 100.0 / NULLIF(ht.hub_weight, 0), 2) AS weight_ratio_hub,
ROUND(mm.total_cost_usd, 2) AS total_cost_usd,
ROUND(mm.total_cost_usd * 100.0 / NULLIF(mt.total_cost_usd, 0), 2) AS cost_ratio_total,
ROUND(mm.total_cost_usd * 100.0 / NULLIF(ht.hub_cost_usd, 0), 2) AS cost_ratio_hub
FROM monthly_metrics mm
JOIN monthly_totals mt ON mm.month = mt.month
JOIN hub_totals ht ON mm.month = ht.month AND mm.hub = ht.hub
WHERE mm.transport_mode IS NOT NULL
ORDER BY
mm.month DESC,
mm.hub,
mm.total_cost_usd DESC;
```
## Sample Output
```json
{
"success": true,
"data": [
{
"month": "2025-01-31T18:30:00.000Z",
"hub": "AMS",
"transport_mode": "local delivery",
"po_count": "0",
"po_ratio_total": "0.00",
"po_ratio_hub": "0.00",
"shipment_count": "1",
"shipment_ratio_total": "0.00",
"shipment_ratio_hub": "2.13",
"total_weight_kg": null,
"weight_ratio_total": null,
"weight_ratio_hub": null,
"total_cost_usd": null,
"cost_ratio_total": null,
"cost_ratio_hub": null
},
{
"month": "2025-01-31T18:30:00.000Z",
"hub": "AMS",
"transport_mode": "air freight",
"po_count": "111",
"po_ratio_total": "2.81",
"po_ratio_hub": "100.00",
"shipment_count": "46",
"shipment_ratio_total": "0.02",
"shipment_ratio_hub": "97.87",
"total_weight_kg": "4156.34",
"weight_ratio_total": "0.00",
"weight_ratio_hub": "100.00",
"total_cost_usd": "120800.83",
"cost_ratio_total": "0.01",
"cost_ratio_hub": "100.00"
}
]
}
```
## Explanation
- **`monthly_metrics` CTE**: Computes monthly aggregated shipment metrics.
- **`monthly_totals` CTE**: Summarizes total counts and values per month.
- **`hub_totals` CTE**: Aggregates totals for each hub per month.
- **Final Query**: Joins all CTEs and calculates percentages to compare shipments, weight, and cost across hubs and transport modes.
## Use Cases
- Track shipment trends over time.
- Compare performance across different hubs and transport modes.
- Monitor costs in a unified currency (USD).
- Optimize logistics and resource allocation.
## // Ratio of key hub vs non-key hub (based on cost, number of POs, and weight) - Monthly ratio of completed last-mile delivery at key hubs vs non-key hubs based on cost, number of POs, and weight.
```
WITH delivery_metrics AS (
SELECT
DATE_TRUNC('month', s.latest_event_timestamp) as month,
CASE
WHEN s.origin IN ('ICN', 'JPUKB', 'KRPUS') THEN 'Key Hub'
ELSE 'Non-Key Hub'
END as hub_type,
s.origin as hub,
-- Count distinct POs
COUNT(DISTINCT po.number) as po_count,
-- Count shipments
COUNT(DISTINCT s.id) as shipment_count,
-- Sum weights
SUM(qp.weight) as total_weight,
-- Calculate costs in USD
SUM(
CASE qsf.currency
WHEN 'USD' THEN qsf.cost * qsf.quantity
WHEN 'EUR' THEN qsf.cost * qsf.quantity * 1.08 -- Approximate EUR to USD
WHEN 'JPY' THEN qsf.cost * qsf.quantity * 0.0067 -- Approximate JPY to USD
WHEN 'KRW' THEN qsf.cost * qsf.quantity * 0.00075 -- Approximate KRW to USD
END
) as total_cost_usd,
-- Count completed last mile deliveries
COUNT(DISTINCT CASE
WHEN s.transport_mode = 'local delivery'
AND d.latest_event_timestamp IS NOT NULL
THEN s.id
END) as completed_last_mile_count,
-- Sum weight of completed last mile deliveries
SUM(CASE
WHEN s.transport_mode = 'local delivery'
AND d.latest_event_timestamp IS NOT NULL
THEN qp.weight
ELSE 0
END) as completed_last_mile_weight,
-- Sum cost of completed last mile deliveries
SUM(CASE
WHEN s.transport_mode = 'local delivery'
AND d.latest_event_timestamp IS NOT NULL
THEN
CASE qsf.currency
WHEN 'USD' THEN qsf.cost * qsf.quantity
WHEN 'EUR' THEN qsf.cost * qsf.quantity * 1.08
WHEN 'JPY' THEN qsf.cost * qsf.quantity * 0.0067
WHEN 'KRW' THEN qsf.cost * qsf.quantity * 0.00075
END
ELSE 0
END) as completed_last_mile_cost_usd
FROM shipments s
LEFT JOIN deliveries d ON s.delivery_id = d.id
LEFT JOIN delivery_quotations dq ON d.id = dq.delivery_id
LEFT JOIN quotations q ON dq.quotation_id = q.id
LEFT JOIN quotation_packages qp ON q.id = qp.quotation_id
LEFT JOIN quotation_schedules qs ON q.id = qs.quotation_id
LEFT JOIN quotation_schedule_fees qsf ON qs.id = qsf.schedule_id
LEFT JOIN export_package_po_numbers epn ON epn.export_package_id = qp.id
LEFT JOIN purchase_orders po ON epn.po_number = po.number
WHERE s.latest_event_timestamp >= '2024-01-01'
AND s.latest_event_timestamp < '2025-04-01'
GROUP BY
DATE_TRUNC('month', s.latest_event_timestamp),
hub_type,
s.origin
),
monthly_totals AS (
SELECT
month,
SUM(po_count) as total_po_count,
SUM(shipment_count) as total_shipment_count,
SUM(total_weight) as total_weight,
SUM(total_cost_usd) as total_cost_usd,
SUM(completed_last_mile_count) as total_completed_last_mile_count,
SUM(completed_last_mile_weight) as total_completed_last_mile_weight,
SUM(completed_last_mile_cost_usd) as total_completed_last_mile_cost_usd
FROM delivery_metrics
GROUP BY month
)
SELECT
dm.month,
dm.hub_type,
dm.hub,
-- Overall metrics
dm.po_count,
ROUND(dm.po_count * 100.0 / NULLIF(mt.total_po_count, 0), 2) as po_ratio,
dm.shipment_count,
ROUND(dm.shipment_count * 100.0 / NULLIF(mt.total_shipment_count, 0), 2) as shipment_ratio,
ROUND(dm.total_weight, 2) as total_weight_kg,
ROUND(dm.total_weight * 100.0 / NULLIF(mt.total_weight, 0), 2) as weight_ratio,
ROUND(dm.total_cost_usd, 2) as total_cost_usd,
ROUND(dm.total_cost_usd * 100.0 / NULLIF(mt.total_cost_usd, 0), 2) as cost_ratio,
-- Last mile delivery metrics
dm.completed_last_mile_count,
ROUND(dm.completed_last_mile_count * 100.0 / NULLIF(mt.total_completed_last_mile_count, 0), 2) as last_mile_count_ratio,
ROUND(dm.completed_last_mile_weight, 2) as completed_last_mile_weight_kg,
ROUND(dm.completed_last_mile_weight * 100.0 / NULLIF(mt.total_completed_last_mile_weight, 0), 2) as last_mile_weight_ratio,
ROUND(dm.completed_last_mile_cost_usd, 2) as completed_last_mile_cost_usd,
ROUND(dm.completed_last_mile_cost_usd * 100.0 / NULLIF(mt.total_completed_last_mile_cost_usd, 0), 2) as last_mile_cost_ratio,
-- Last mile completion rates within hub
ROUND(dm.completed_last_mile_count * 100.0 / NULLIF(dm.shipment_count, 0), 2) as hub_last_mile_completion_rate,
ROUND(dm.completed_last_mile_weight * 100.0 / NULLIF(dm.total_weight, 0), 2) as hub_weight_completion_rate,
ROUND(dm.completed_last_mile_cost_usd * 100.0 / NULLIF(dm.total_cost_usd, 0), 2) as hub_cost_completion_rate
FROM delivery_metrics dm
JOIN monthly_totals mt ON dm.month = mt.month
WHERE dm.month >= '2025-01-01' -- Focus on recent months
ORDER BY
dm.month DESC,
dm.hub_type,
dm.total_cost_usd DESC;
```
```
/*Output*/
{
"success": true,
"data": [
{
"month": "2025-01-31T18:30:00.000Z",
"hub_type": "Key Hub",
"hub": "ICN",
"po_count": "721",
"po_ratio": "19.05",
"shipment_count": "612",
"shipment_ratio": "0.20",
"total_weight_kg": "31616585.18",
"weight_ratio": "20.15",
"total_cost_usd": "189103560.36",
"cost_ratio": "21.48",
"completed_last_mile_count": "434",
"last_mile_count_ratio": "0.14",
"completed_last_mile_weight_kg": "31019974.92",
"last_mile_weight_ratio": "20.29",
"completed_last_mile_cost_usd": "184082963.61",
"last_mile_cost_ratio": "21.43",
"hub_last_mile_completion_rate": "70.92",
"hub_weight_completion_rate": "98.11",
"hub_cost_completion_rate": "97.35"
},
{
"month": "2025-01-31T18:30:00.000Z",
"hub_type": "Key Hub",
"hub": "KRPUS",
"po_count": "422",
"po_ratio": "11.15",
"shipment_count": "2656",
"shipment_ratio": "0.87",
"total_weight_kg": "3299252.04",
"weight_ratio": "2.10",
"total_cost_usd": "14408073.50",
"cost_ratio": "1.64",
"completed_last_mile_count": "1",
"last_mile_count_ratio": "0.00",
"completed_last_mile_weight_kg": "154371.50",
"last_mile_weight_ratio": "0.10",
"completed_last_mile_cost_usd": "160325.00",
"last_mile_cost_ratio": "0.02",
"hub_last_mile_completion_rate": "0.04",
"hub_weight_completion_rate": "4.68",
"hub_cost_completion_rate": "1.11"
},
{
"month": "2025-01-31T18:30:00.000Z",
"hub_type": "Key Hub",
"hub": "JPUKB",
"po_count": "713",
"po_ratio": "18.84",
"shipment_count": "294974",
"shipment_ratio": "96.55",
"total_weight_kg": "324476.81",
"weight_ratio": "0.21",
"total_cost_usd": "2507634.20",
"cost_ratio": "0.28",
"completed_last_mile_count": "294947",
"last_mile_count_ratio": "98.28",
"completed_last_mile_weight_kg": "312803.91",
"last_mile_weight_ratio": "0.20",
"completed_last_mile_cost_usd": "1967489.07",
"last_mile_cost_ratio": "0.23",
"hub_last_mile_completion_rate": "99.99",
"hub_weight_completion_rate": "96.40",
"hub_cost_completion_rate": "78.46"
},
{
"month": "2025-01-31T18:30:00.000Z",
"hub_type": "Non-Key Hub",
"hub": "JPCHI",
"po_count": "0",
"po_ratio": "0.00",
"shipment_count": "1",
"shipment_ratio": "0.00",
"total_weight_kg": null,
"weight_ratio": null,
"total_cost_usd": null,
"cost_ratio": null,
"completed_last_mile_count": "0",
"last_mile_count_ratio": "0.00",
"completed_last_mile_weight_kg": "0.00",
"last_mile_weight_ratio": "0.00",
"completed_last_mile_cost_usd": "0.00",
"last_mile_cost_ratio": "0.00",
"hub_last_mile_completion_rate": "0.00",
"hub_weight_completion_rate": null,
"hub_cost_completion_rate": null
},
{
"month": "2025-01-31T18:30:00.000Z",
"hub_type": "Non-Key Hub",
"hub": null,
"po_count": "1584",
"po_ratio": "41.85",
"shipment_count": "7103",
"shipment_ratio": "2.32",
"total_weight_kg": "121541540.53",
"weight_ratio": "77.47",
"total_cost_usd": "673075596.72",
"cost_ratio": "76.47",
"completed_last_mile_count": "4702",
"last_mile_count_ratio": "1.57",
"completed_last_mile_weight_kg": "121414784.57",
"last_mile_weight_ratio": "79.41",
"completed_last_mile_cost_usd": "672835520.96",
"last_mile_cost_ratio": "78.32",
"hub_last_mile_completion_rate": "66.20",
"hub_weight_completion_rate": "99.90",
"hub_cost_completion_rate": "99.96"
},
{
"month": "2025-01-31T18:30:00.000Z",
"hub_type": "Non-Key Hub",
"hub": "KIX",
"po_count": "190",
"po_ratio": "5.02",
"shipment_count": "83",
"shipment_ratio": "0.03",
"total_weight_kg": "77913.70",
"weight_ratio": "0.05",
"total_cost_usd": "872881.75",
"cost_ratio": "0.10",
"completed_last_mile_count": "0",
"last_mile_count_ratio": "0.00",
"completed_last_mile_weight_kg": "0.00",
"last_mile_weight_ratio": "0.00",
"completed_last_mile_cost_usd": "0.00",
"last_mile_cost_ratio": "0.00",
"hub_last_mile_completion_rate": "0.00",
"hub_weight_completion_rate": "0.00",
"hub_cost_completion_rate": "0.00"
},
{
"month": "2025-01-31T18:30:00.000Z",
"hub_type": "Non-Key Hub",
"hub": "AMS",
"po_count": "111",
"po_ratio": "2.93",
"shipment_count": "47",
"shipment_ratio": "0.02",
"total_weight_kg": "4156.34",
"weight_ratio": "0.00",
"total_cost_usd": "120800.83",
"cost_ratio": "0.01",
"completed_last_mile_count": "1",
"last_mile_count_ratio": "0.00",
"completed_last_mile_weight_kg": "0.00",
"last_mile_weight_ratio": "0.00",
"completed_last_mile_cost_usd": "0.00",
"last_mile_cost_ratio": "0.00",
"hub_last_mile_completion_rate": "2.13",
"hub_weight_completion_rate": "0.00",
"hub_cost_completion_rate": "0.00"
},
...]
}
```
## //Consolidation Rate - Number of POs shipped / Number of shipments for air freight, sea freight, and trucking.
```
WITH storage_durations AS (
SELECT
DATE_TRUNC('month', de.event_timestamp) as month,
s.origin as hub,
s.origin_city,
s.id as shipment_id,
-- Get first arrival event
MIN(de.event_timestamp) as arrival_date,
-- Get last departure event
MAX(de.event_timestamp) as departure_date,
-- Calculate storage duration in days
EXTRACT(EPOCH FROM (MAX(de.event_timestamp) - MIN(de.event_timestamp)))/86400.0 as storage_days
FROM shipments s
JOIN delivery_events de ON s.delivery_id = de.delivery_id
WHERE
-- Focus on most recent data
de.event_timestamp >= '2025-02-01'
AND de.event_timestamp < '2025-03-01'
-- Ensure valid storage duration
AND s.latest_event_timestamp > s.earliest_event_timestamp
AND s.origin IS NOT NULL
GROUP BY
DATE_TRUNC('month', de.event_timestamp),
s.origin,
s.origin_city,
s.id
HAVING
MIN(de.event_timestamp) != MAX(de.event_timestamp)
)
SELECT
month,
hub,
origin_city,
-- Volume metrics
COUNT(DISTINCT shipment_id) as total_shipments,
-- Storage duration metrics
ROUND(AVG(storage_days)::numeric, 2) as avg_storage_days,
ROUND(MIN(storage_days)::numeric, 2) as min_storage_days,
ROUND(MAX(storage_days)::numeric, 2) as max_storage_days,
ROUND(PERCENTILE_CONT(0.5) WITHIN GROUP (ORDER BY storage_days)::numeric, 2) as median_storage_days,
-- Storage duration distribution
COUNT(CASE WHEN storage_days <= 7 THEN 1 END) as within_week,
COUNT(CASE WHEN storage_days > 7 AND storage_days <= 14 THEN 1 END) as within_two_weeks,
COUNT(CASE WHEN storage_days > 14 AND storage_days <= 30 THEN 1 END) as within_month,
COUNT(CASE WHEN storage_days > 30 THEN 1 END) as over_month,
-- Storage efficiency metrics
ROUND(COUNT(CASE WHEN storage_days <= 7 THEN 1 END)::numeric * 100 /
NULLIF(COUNT(*), 0)::numeric, 2) as within_week_percentage,
ROUND(COUNT(CASE WHEN storage_days <= 14 THEN 1 END)::numeric * 100 /
NULLIF(COUNT(*), 0)::numeric, 2) as within_two_weeks_percentage,
-- Additional metrics for analysis
ROUND(STDDEV(storage_days)::numeric, 2) as storage_days_stddev
FROM storage_durations
GROUP BY
month,
hub,
origin_city
HAVING COUNT(DISTINCT shipment_id) > 0
ORDER BY
avg_storage_days DESC
LIMIT 100;
```
/*Output*/
```
{
"success": true,
"data": [
{
"month": "2025-01-31T18:30:00.000Z",
"hub": "SIN",
"origin_city": "Busan",
"total_shipments": "1",
"avg_storage_days": "20.74",
"min_storage_days": "20.74",
"max_storage_days": "20.74",
"median_storage_days": "20.74",
"within_week": "0",
"within_two_weeks": "0",
"within_month": "1",
"over_month": "0",
"within_week_percentage": "0.00",
"within_two_weeks_percentage": "0.00",
"storage_days_stddev": null
},
{
"month": "2025-01-31T18:30:00.000Z",
"hub": "ICN",
"origin_city": null,
"total_shipments": "418",
"avg_storage_days": "20.47",
"min_storage_days": "4.81",
"max_storage_days": "21.46",
"median_storage_days": "20.46",
"within_week": "1",
"within_two_weeks": "0",
"within_month": "417",
"over_month": "0",
"within_week_percentage": "0.24",
"within_two_weeks_percentage": "0.24",
"storage_days_stddev": "0.80"
},
{
"month": "2025-01-31T18:30:00.000Z",
"hub": "AMS",
"origin_city": null,
"total_shipments": "1",
"avg_storage_days": "17.62",
"min_storage_days": "17.62",
"max_storage_days": "17.62",
"median_storage_days": "17.62",
"within_week": "0",
"within_two_weeks": "0",
"within_month": "1",
"over_month": "0",
"within_week_percentage": "0.00",
"within_two_weeks_percentage": "0.00",
"storage_days_stddev": null
},
{
"month": "2025-01-31T18:30:00.000Z",
"hub": "RTM",
"origin_city": "Rotterdam",
"total_shipments": "1",
"avg_storage_days": "16.76",
"min_storage_days": "16.76",
"max_storage_days": "16.76",
"median_storage_days": "16.76",
"within_week": "0",
"within_two_weeks": "0",
"within_month": "1",
"over_month": "0",
"within_week_percentage": "0.00",
"within_two_weeks_percentage": "0.00",
"storage_days_stddev": null
},
...]
}
```
## //Last mile delivery
# Last Mile Deliveries SQL Query
## Overview
This SQL query calculates key metrics for last-mile deliveries, filtering shipments based on the transport mode and delivery time range.
## Query
```sql
WITH last_mile_deliveries AS (
SELECT
s.id as shipment_id,
s.customer,
s.origin,
s.origin_city,
s.destination,
s.transport_mode,
s.earliest_event_timestamp,
s.latest_event_timestamp,
EXTRACT(EPOCH FROM (s.latest_event_timestamp - s.earliest_event_timestamp))/3600/24 as delivery_days,
s.forwarder
FROM shipments s
WHERE
s.transport_mode = 'local delivery'
AND s.earliest_event_timestamp IS NOT NULL
AND s.latest_event_timestamp IS NOT NULL
AND s.earliest_event_timestamp >= '2025-01-01'
)
SELECT
customer,
forwarder,
COUNT(*) as total_deliveries,
ROUND(AVG(delivery_days), 1) as avg_delivery_days,
ROUND(MIN(delivery_days), 1) as min_delivery_days,
ROUND(MAX(delivery_days), 1) as max_delivery_days,
ROUND(COUNT(CASE WHEN delivery_days <= 1 THEN 1 END) * 100.0 / COUNT(*), 1) as same_day_delivery_pct,
ROUND(COUNT(CASE WHEN delivery_days <= 2 THEN 1 END) * 100.0 / COUNT(*), 1) as within_2days_pct,
origin,
destination
FROM last_mile_deliveries
GROUP BY customer, forwarder, origin, destination
ORDER BY total_deliveries DESC;
```
## Sample Output
```json
{
"success": true,
"data": [
{
"customer": "6549",
"forwarder": null,
"total_deliveries": "1298",
"avg_delivery_days": "0.6",
"min_delivery_days": "-1.5",
"max_delivery_days": "34.6",
"same_day_delivery_pct": "99.9",
"within_2days_pct": "99.9",
"origin": null,
"destination": "CNZOS"
},
{
"customer": "6549",
"forwarder": null,
"total_deliveries": "432",
"avg_delivery_days": "1.4",
"min_delivery_days": "1.3",
"max_delivery_days": "1.4",
"same_day_delivery_pct": "0.0",
"within_2days_pct": "100.0",
"origin": "ICN",
"destination": "KRPUS"
},
{
"customer": "60YC",
"forwarder": null,
"total_deliveries": "19",
"avg_delivery_days": "-10.2",
"min_delivery_days": "-10.4",
"max_delivery_days": "-5.6",
"same_day_delivery_pct": "100.0",
"within_2days_pct": "100.0",
"origin": "JPUKB",
"destination": "JPKII"
}
]
}
```
//Monthly average duration of storage in days at each hub
Applies to POs that have departed from the hub within the month.
Departure date is calculated as the difference between arrival date and departure from the hub.