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+# PRD: IBL Sales Dashboard for Marketing Manager and Owner
+
+**Date:** 2026-06-22  
+**Scope:** Design only. No code changes yet.  
+**Project:** `one-api-lab`  
+**Primary source database:** `one_lab`  
+**Primary ETL target database:** `one_lab_etl`  
+
+---
+
+## Problem
+
+Saat ini data order, pembayaran, company, MOU, omzet type, dan grouping test masih tersebar di banyak tabel operasional. Ini menyulitkan dua audiens utama:
+
+1. Manager marketing yang butuh melihat pertumbuhan omzet, kontribusi company, komposisi layanan, dan peluang follow-up.
+2. Pemilik perusahaan yang butuh ringkasan revenue, cash-in, piutang, kolektibilitas, dan tren bisnis secara cepat.
+
+Query langsung ke tabel transaksi operasional juga berisiko:
+
+- definisi angka bisa beda-beda antar report,
+- agregasi menjadi berat untuk dashboard,
+- filter lintas `company`, `company type group`, `omzet type`, `lunas/tagihan`, dan `nat_subgroup` sulit distandarkan,
+- level order dan level item test tercampur.
+
+---
+
+## Goals
+
+1. Menyediakan satu sumber data dashboard yang konsisten untuk owner dan manager marketing.
+2. Mendukung filter:
+   - tanggal,
+   - company,
+   - company type group,
+   - omzet type,
+   - status lunas,
+   - status tagihan/outstanding,
+   - nat subgroup.
+3. Memisahkan metrik level order dan level test detail agar angka tidak double count.
+4. Menyediakan API PHP yang ringan untuk summary, chart, ranking, dan detail table.
+5. Menjaga definisi bisnis agar konsisten dengan pola join report existing di repo.
+
+---
+
+## Non Goals
+
+1. Belum mencakup prediksi sales atau forecasting.
+2. Belum mencakup target marketing per staff.
+3. Belum mencakup mutasi invoice, retur, atau akuntansi GL penuh.
+4. Belum mencakup writeback atau input manual dari dashboard.
+
+---
+
+## Target Users
+
+### A. Marketing Manager
+
+Butuh membaca:
+
+- omzet per periode,
+- top company,
+- kontribusi per `omzet type`,
+- kontribusi per `nat_subgroup`,
+- company mana yang turun,
+- company mana yang outstanding-nya tinggi.
+
+### B. Owner
+
+Butuh membaca:
+
+- gross sales,
+- cash-in,
+- outstanding,
+- rasio collection,
+- distribusi revenue,
+- aging tagihan,
+- konsentrasi revenue per customer.
+
+---
+
+## Source Tables
+
+Tabel utama yang sudah diverifikasi:
+
+- `t_orderheader`
+- `t_orderdetailorder`
+- `t_orderdetail`
+- `t_test`
+- `nat_subgroup`
+- `m_company`
+- `m_companytypegroup`
+- `m_companytype`
+- `m_mou`
+- `m_omzettype`
+- `f_payment`
+- `f_payment_orderheader`
+
+### Relasi Utama
+
+#### Relasi order dan company
+
+- `t_orderheader.T_OrderHeaderM_CompanyID -> m_company.M_CompanyID`
+- `m_company.M_CompanyM_CompanyGroupTypeID -> m_companytypegroup.M_CompanyTypeGroupID`
+- `m_company.M_CompanyM_CompanyTypeID -> m_companytype.M_CompanyTypeID`
+
+#### Relasi order dan MOU / omzet
+
+- `t_orderheader.T_OrderHeaderM_MouID -> m_mou.M_MouID`
+- `m_mou.M_MouM_OmzetTypeID -> m_omzettype.M_OmzetTypeID`
+
+#### Relasi order dan payment
+
+- `f_payment.F_PaymentT_OrderHeaderID -> t_orderheader.T_OrderHeaderID`
+- `f_payment_orderheader.F_Payment_OrderHeaderID -> t_orderheader.T_OrderHeaderID`
+
+#### Relasi detail dan subgroup
+
+- `t_orderdetail.T_OrderDetailT_TestID -> t_test.T_TestID`
+- `t_test.T_TestNat_SubgroupID -> nat_subgroup.Nat_SubGroupID`
+
+---
+
+## Key Business Rules
+
+1. `sales order amount` memakai basis `t_orderheader.T_OrderHeaderTotal`.
+2. `cash-in amount` memakai basis akumulasi `f_payment.F_PaymentTotal` aktif.
+3. `lunas` memakai flag utama `f_payment_orderheader.F_Payment_OrderHeaderIsLunas`.
+4. `outstanding amount` memakai prioritas:
+   - `f_payment_orderheader.F_Payment_OrderHeaderChargeAmount` bila tersedia,
+   - fallback `order_total - payment_total`.
+5. `nat_subgroup` adalah atribut level test detail, bukan level order header.
+6. Satu order bisa punya banyak `nat_subgroup`, sehingga filter subgroup harus memakai mart detail atau bridge.
+7. Hanya data aktif yang dipakai:
+   - `T_OrderHeaderIsActive = 'Y'`
+   - `T_OrderDetailIsActive = 'Y'`
+   - `M_CompanyIsActive = 'Y'`
+   - `M_MouIsActive = 'Y'`
+   - `M_OmzetTypeIsActive = 'Y'`
+   - `Nat_SubGroupIsActive = 'Y'`
+   - `F_PaymentIsActive = 'Y'`
+8. Semua tabel ETL baru ditempatkan di database `one_lab_etl`, bukan di `one_lab`, agar query dashboard tidak membebani database transaksional.
+9. Struktur tabel ETL baru tidak memakai foreign key constraint. Relasi dijaga di level query dan index saja.
+10. Naming tabel dan kolom baru mengikuti gaya schema inti `one_lab`:
+   - nama tabel: lowercase dengan underscore,
+   - nama kolom: prefix nama entitas tabel sendiri,
+   - hindari gaya generik seperti `created_at`, `updated_at`, atau nama kolom tanpa prefix domain.
+
+---
+
+## Product Scope
+
+Dashboard dibagi menjadi 4 blok:
+
+1. Executive summary
+2. Sales composition
+3. Collection and receivable health
+4. Customer and subgroup drilldown
+
+---
+
+## KPI Definitions
+
+### Core KPI
+
+- `total_sales`: total nilai order
+- `total_paid`: total pembayaran masuk
+- `total_outstanding`: sisa tagihan
+- `collection_rate`: `total_paid / total_sales`
+- `lunas_order_count`: jumlah order lunas
+- `open_order_count`: jumlah order belum lunas
+- `active_company_count`: jumlah company yang punya transaksi
+
+### Breakdown KPI
+
+- `sales_by_company`
+- `sales_by_company_type_group`
+- `sales_by_omzet_type`
+- `sales_by_nat_subgroup`
+- `outstanding_by_company`
+- `outstanding_by_aging_bucket`
+
+### Trend KPI
+
+- `daily_sales_trend`
+- `monthly_sales_trend`
+- `daily_cashin_trend`
+- `monthly_cashin_trend`
+
+---
+
+## Dashboard Views
+
+### A. Executive Summary
+
+Cards:
+
+- total sales
+- total paid
+- total outstanding
+- collection rate
+- lunas order
+- active company
+
+Charts:
+
+- line chart `sales vs cash-in`
+- donut `lunas vs belum lunas`
+- bar chart `outstanding aging bucket`
+
+### B. Sales Composition
+
+Charts:
+
+- bar `sales by omzet type`
+- bar `sales by company type group`
+- horizontal bar `top 10 company by sales`
+- pareto `sales by nat_subgroup`
+
+### C. Collection Health
+
+Charts:
+
+- bar `top outstanding company`
+- stacked bar `lunas vs belum lunas by omzet type`
+- aging chart `0-30 / 31-60 / 61-90 / 90+ days`
+
+### D. Drilldown Tables
+
+Tables:
+
+- order summary table
+- company ranking table
+- subgroup contribution table
+- outstanding exception table
+
+---
+
+## Filter Requirements
+
+Global filters:
+
+1. date range
+2. company
+3. company type group
+4. omzet type
+5. payment status:
+   - all
+   - lunas
+   - belum lunas
+6. tagihan status:
+   - all
+   - ada outstanding
+   - outstanding nol
+7. nat subgroup
+
+### Filter Semantics
+
+#### Jika filter `nat_subgroup` dipakai
+
+- KPI summary tetap harus akurat di level order.
+- Implementasi awal yang aman:
+  - summary berbasis mart detail dengan `COUNT(DISTINCT order_id)` untuk order count,
+  - nominal sales untuk subgroup memakai `detail_total`,
+  - summary order total saat filter subgroup aktif harus diberi label jelas: `sales contribution by subgroup`, bukan `full order revenue`, agar tidak misleading.
+
+#### Rekomendasi produk
+
+Pisahkan dua mode saat filter subgroup aktif:
+
+1. `Order view`
+   - subgroup dipakai sebagai `has subgroup in order`
+   - nilai sales tetap full order total
+2. `Contribution view`
+   - subgroup dipakai pada level detail
+   - nilai sales memakai `detail_total`
+
+Untuk phase 1, lebih aman default ke `Contribution view`.
+
+---
+
+## Data Model Design
+
+### Naming Convention for New ETL Tables
+
+Prinsip penamaan:
+
+- database target: `one_lab_etl`
+- nama tabel mengikuti pola lowercase underscore
+- nama kolom mengikuti pola prefix entitas tabel seperti `T_OrderHeader...`, `M_Company...`, `F_Payment...`
+- tidak memakai foreign key
+- relasi dioptimalkan dengan `PRIMARY KEY`, `UNIQUE KEY`, dan `INDEX`
+
+### 1. `sales_dashboard_order`
+
+Grain: `1 row = 1 orderheader`
+
+Tujuan:
+
+- dashboard utama owner,
+- KPI order-level,
+- summary payment / receivable.
+
+#### Proposed Columns
+
+```sql
+SalesDashboardOrderID BIGINT PK AUTO_INCREMENT
+SalesDashboardOrderT_OrderHeaderID BIGINT NOT NULL
+SalesDashboardOrderDate DATETIME NOT NULL
+SalesDashboardOrderDateOnly DATE NOT NULL
+SalesDashboardOrderT_OrderHeaderLabNumber VARCHAR(25) NULL
+SalesDashboardOrderT_OrderHeaderStatus VARCHAR(150) NULL
+SalesDashboardOrderM_CompanyID INT NULL
+SalesDashboardOrderM_CompanyName VARCHAR(100) NULL
+SalesDashboardOrderM_CompanyTypeID INT NULL
+SalesDashboardOrderM_CompanyTypeName VARCHAR(50) NULL
+SalesDashboardOrderM_CompanyTypeGroupID INT NULL
+SalesDashboardOrderM_CompanyTypeGroupName VARCHAR(100) NULL
+SalesDashboardOrderM_MouID INT NULL
+SalesDashboardOrderM_MouName VARCHAR(100) NULL
+SalesDashboardOrderM_OmzetTypeID INT NULL
+SalesDashboardOrderM_OmzetTypeName VARCHAR(25) NULL
+SalesDashboardOrderTotal DECIMAL(18,2) NOT NULL DEFAULT 0.00
+SalesDashboardOrderPaymentTotal DECIMAL(18,2) NOT NULL DEFAULT 0.00
+SalesDashboardOrderOutstandingTotal DECIMAL(18,2) NOT NULL DEFAULT 0.00
+SalesDashboardOrderIsLunas CHAR(1) NOT NULL DEFAULT 'N'
+SalesDashboardOrderHasOutstanding CHAR(1) NOT NULL DEFAULT 'N'
+SalesDashboardOrderLastPaymentDate DATE NULL
+SalesDashboardOrderAgingDays INT NOT NULL DEFAULT 0
+SalesDashboardOrderAgingBucket VARCHAR(20) NOT NULL DEFAULT '0-30'
+SalesDashboardOrderDetailCount INT NOT NULL DEFAULT 0
+SalesDashboardOrderSourceLastUpdated DATETIME NOT NULL
+SalesDashboardOrderCreated DATETIME NOT NULL
+SalesDashboardOrderLastUpdated DATETIME NOT NULL
+PRIMARY KEY (SalesDashboardOrderID)
+UNIQUE KEY SalesDashboardOrderT_OrderHeaderID (SalesDashboardOrderT_OrderHeaderID)
+KEY SalesDashboardOrderDateOnly (SalesDashboardOrderDateOnly)
+KEY SalesDashboardOrderM_CompanyID (SalesDashboardOrderM_CompanyID)
+KEY SalesDashboardOrderM_CompanyTypeGroupID (SalesDashboardOrderM_CompanyTypeGroupID)
+KEY SalesDashboardOrderM_OmzetTypeID (SalesDashboardOrderM_OmzetTypeID)
+KEY SalesDashboardOrderIsLunas (SalesDashboardOrderIsLunas)
+KEY SalesDashboardOrderHasOutstanding (SalesDashboardOrderHasOutstanding)
+KEY SalesDashboardOrderAgingBucket (SalesDashboardOrderAgingBucket)
+```
+
+### 2. `sales_dashboard_order_subgroup`
+
+Grain: `1 row = 1 orderdetail`
+
+Tujuan:
+
+- breakdown `nat_subgroup`,
+- analisis kontribusi layanan,
+- drilldown marketing.
+
+#### Proposed Columns
+
+```sql
+SalesDashboardOrderSubGroupID BIGINT PK AUTO_INCREMENT
+SalesDashboardOrderSubGroupT_OrderDetailID BIGINT NOT NULL
+SalesDashboardOrderSubGroupT_OrderHeaderID BIGINT NOT NULL
+SalesDashboardOrderSubGroupDate DATETIME NOT NULL
+SalesDashboardOrderSubGroupDateOnly DATE NOT NULL
+SalesDashboardOrderSubGroupM_CompanyID INT NULL
+SalesDashboardOrderSubGroupM_CompanyName VARCHAR(100) NULL
+SalesDashboardOrderSubGroupM_CompanyTypeGroupID INT NULL
+SalesDashboardOrderSubGroupM_CompanyTypeGroupName VARCHAR(100) NULL
+SalesDashboardOrderSubGroupM_MouID INT NULL
+SalesDashboardOrderSubGroupM_MouName VARCHAR(100) NULL
+SalesDashboardOrderSubGroupM_OmzetTypeID INT NULL
+SalesDashboardOrderSubGroupM_OmzetTypeName VARCHAR(25) NULL
+SalesDashboardOrderSubGroupT_TestID INT NOT NULL
+SalesDashboardOrderSubGroupT_TestCode VARCHAR(25) NULL
+SalesDashboardOrderSubGroupT_TestName VARCHAR(100) NOT NULL
+SalesDashboardOrderSubGroupNat_SubGroupID INT NULL
+SalesDashboardOrderSubGroupNat_SubGroupCode VARCHAR(10) NULL
+SalesDashboardOrderSubGroupNat_SubGroupName VARCHAR(50) NULL
+SalesDashboardOrderSubGroupPriceTotal DECIMAL(18,2) NOT NULL DEFAULT 0.00
+SalesDashboardOrderSubGroupNetTotal DECIMAL(18,2) NOT NULL DEFAULT 0.00
+SalesDashboardOrderSubGroupIsLunas CHAR(1) NOT NULL DEFAULT 'N'
+SalesDashboardOrderSubGroupSourceLastUpdated DATETIME NOT NULL
+SalesDashboardOrderSubGroupCreated DATETIME NOT NULL
+SalesDashboardOrderSubGroupLastUpdated DATETIME NOT NULL
+PRIMARY KEY (SalesDashboardOrderSubGroupID)
+UNIQUE KEY SalesDashboardOrderSubGroupT_OrderDetailID (SalesDashboardOrderSubGroupT_OrderDetailID)
+KEY SalesDashboardOrderSubGroupT_OrderHeaderID (SalesDashboardOrderSubGroupT_OrderHeaderID)
+KEY SalesDashboardOrderSubGroupDateOnly (SalesDashboardOrderSubGroupDateOnly)
+KEY SalesDashboardOrderSubGroupM_CompanyID (SalesDashboardOrderSubGroupM_CompanyID)
+KEY SalesDashboardOrderSubGroupM_CompanyTypeGroupID (SalesDashboardOrderSubGroupM_CompanyTypeGroupID)
+KEY SalesDashboardOrderSubGroupM_OmzetTypeID (SalesDashboardOrderSubGroupM_OmzetTypeID)
+KEY SalesDashboardOrderSubGroupNat_SubGroupID (SalesDashboardOrderSubGroupNat_SubGroupID)
+KEY SalesDashboardOrderSubGroupIsLunas (SalesDashboardOrderSubGroupIsLunas)
+```
+
+### 3. `sales_dashboard_etl_log`
+
+Tujuan:
+
+- audit ETL,
+- troubleshooting refresh,
+- monitoring last successful sync.
+
+#### Proposed Columns
+
+```sql
+SalesDashboardEtlLogID BIGINT PK AUTO_INCREMENT
+SalesDashboardEtlLogJobName VARCHAR(100) NOT NULL
+SalesDashboardEtlLogStarted DATETIME NOT NULL
+SalesDashboardEtlLogFinished DATETIME NULL
+SalesDashboardEtlLogStatus VARCHAR(20) NOT NULL
+SalesDashboardEtlLogLastWatermark DATETIME NULL
+SalesDashboardEtlLogRowsInserted INT NOT NULL DEFAULT 0
+SalesDashboardEtlLogRowsUpdated INT NOT NULL DEFAULT 0
+SalesDashboardEtlLogRowsDeleted INT NOT NULL DEFAULT 0
+SalesDashboardEtlLogErrorMessage TEXT NULL
+SalesDashboardEtlLogCreated DATETIME NOT NULL
+PRIMARY KEY (SalesDashboardEtlLogID)
+KEY SalesDashboardEtlLogJobName (SalesDashboardEtlLogJobName)
+KEY SalesDashboardEtlLogStatus (SalesDashboardEtlLogStatus)
+KEY SalesDashboardEtlLogStarted (SalesDashboardEtlLogStarted)
+```
+
+---
+
+## ETL Strategy
+
+### Recommended Approach
+
+Gunakan ETL incremental ke tabel fisik di database `one_lab_etl`, bukan query live langsung dari tabel operasional `one_lab` untuk semua chart.
+
+### Why
+
+1. Query dashboard akan jauh lebih cepat.
+2. Definisi bisnis menjadi terkunci dan konsisten.
+3. Filter multi-dimensi lebih gampang.
+4. Aman untuk kebutuhan chart owner yang sering membuka data agregat.
+
+### Load Frequency
+
+Phase 1:
+
+- scheduled refresh tiap `30 menit`
+- plus endpoint manual refresh untuk dev/admin
+
+Phase 2 opsional:
+
+- refresh per `5 menit` atau near real-time
+
+### Watermark Incremental
+
+Gunakan `MAX(last_updated)` dari sumber:
+
+- `t_orderheader.T_OrderHeaderLastUpdated`
+- `t_orderdetail.T_OrderDetailLastUpdated`
+- `f_payment.F_PaymentLastUpdated`
+
+Untuk order-level ETL, satu order harus di-rebuild jika salah satu dari tiga sumber berubah.
+
+### ETL Steps
+
+#### Job 1: Build `one_lab_etl.sales_dashboard_order`
+
+1. Ambil order aktif yang berubah sejak watermark.
+2. Join:
+   - `m_company`
+   - `m_companytype`
+   - `m_companytypegroup`
+   - `m_mou`
+   - `m_omzettype`
+3. Aggregate payment aktif per order dari `f_payment`.
+4. Ambil status lunas dari `f_payment_orderheader`.
+5. Hitung:
+   - `payment_amount`
+   - `outstanding_amount`
+   - `has_outstanding`
+   - `aging_days`
+   - `aging_bucket`
+6. Upsert ke `one_lab_etl.sales_dashboard_order`.
+
+#### Job 2: Build `one_lab_etl.sales_dashboard_order_subgroup`
+
+1. Ambil detail aktif yang berubah sejak watermark, atau detail milik order yang berubah.
+2. Join:
+   - `t_test`
+   - `nat_subgroup`
+   - `m_company`
+   - `m_companytypegroup`
+   - `m_mou`
+   - `m_omzettype`
+3. Tempel status lunas dari hasil order fact.
+4. Upsert ke `one_lab_etl.sales_dashboard_order_subgroup`.
+
+#### Job 3: ETL log
+
+1. Tulis status awal job.
+2. Simpan jumlah row insert/update.
+3. Simpan watermark akhir.
+4. Simpan error jika gagal.
+
+---
+
+## API Design
+
+### Controller Proposal
+
+File baru:
+
+`application/controllers/dashboard/Sales.php`
+
+### Endpoint Proposal
+
+#### 1. Summary KPI
+
+**Route:** `GET /dashboard/sales/summary`
+
+Purpose:
+
+- cards executive summary
+
+Query params:
+
+- `date_start`
+- `date_end`
+- `company_id`
+- `company_type_group_id`
+- `omzet_type_id`
+- `is_lunas`
+- `has_outstanding`
+- `nat_subgroup_id`
+- `view_mode` = `order|contribution`
+
+Response:
+
+```json
+{
+  "status": "OK",
+  "data": {
+    "total_sales": 0,
+    "total_paid": 0,
+    "total_outstanding": 0,
+    "collection_rate": 0,
+    "lunas_order_count": 0,
+    "open_order_count": 0,
+    "active_company_count": 0
+  }
+}
+```
+
+#### 2. Sales Trend
+
+**Route:** `GET /dashboard/sales/trend`
+
+Purpose:
+
+- line chart sales vs cash-in
+
+Query params:
+
+- semua filter global
+- `granularity` = `day|month`
+
+Response:
+
+```json
+{
+  "status": "OK",
+  "data": [
+    {
+      "period": "2026-06-01",
+      "sales_amount": 0,
+      "paid_amount": 0,
+      "outstanding_amount": 0
+    }
+  ]
+}
+```
+
+#### 3. Breakdown
+
+**Route:** `GET /dashboard/sales/breakdown`
+
+Purpose:
+
+- reusable endpoint untuk donut/bar by dimension
+
+Query params:
+
+- semua filter global
+- `dimension` = `company|company_type_group|omzet_type|nat_subgroup|aging_bucket|lunas_status`
+- `metric` = `sales|paid|outstanding|order_count`
+- `limit`
+
+Response:
+
+```json
+{
+  "status": "OK",
+  "data": [
+    {
+      "dimension_id": "1",
+      "dimension_name": "Kimia Klinik",
+      "metric_value": 0,
+      "order_count": 0
+    }
+  ]
+}
+```
+
+#### 4. Company Ranking
+
+**Route:** `GET /dashboard/sales/company-ranking`
+
+Purpose:
+
+- top/bottom company
+
+Query params:
+
+- semua filter global
+- `sort_by` = `sales|paid|outstanding|collection_rate`
+- `sort_dir` = `asc|desc`
+- `limit`
+
+Response:
+
+```json
+{
+  "status": "OK",
+  "data": [
+    {
+      "company_id": 0,
+      "company_name": "",
+      "company_type_group_name": "",
+      "omzet_type_name": "",
+      "sales_amount": 0,
+      "paid_amount": 0,
+      "outstanding_amount": 0,
+      "collection_rate": 0,
+      "order_count": 0
+    }
+  ]
+}
+```
+
+#### 5. Order Detail Table
+
+**Route:** `GET /dashboard/sales/orders`
+
+Purpose:
+
+- detail table order-level
+
+Query params:
+
+- semua filter global
+- `page`
+- `page_size`
+- `sort_by`
+- `sort_dir`
+
+Response:
+
+```json
+{
+  "status": "OK",
+  "data": {
+    "rows": [
+      {
+        "order_id": 0,
+        "order_date": "",
+        "lab_number": "",
+        "company_name": "",
+        "company_type_group_name": "",
+        "mou_name": "",
+        "omzet_type_name": "",
+        "gross_sales_amount": 0,
+        "payment_amount": 0,
+        "outstanding_amount": 0,
+        "is_lunas": "N",
+        "aging_bucket": "0-30"
+      }
+    ],
+    "pagination": {
+      "page": 1,
+      "page_size": 20,
+      "total_rows": 0
+    }
+  }
+}
+```
+
+#### 6. Subgroup Contribution Table
+
+**Route:** `GET /dashboard/sales/subgroup-contribution`
+
+Purpose:
+
+- detail analisis subgroup untuk marketing
+
+Query params:
+
+- semua filter global
+- `page`
+- `page_size`
+
+Response:
+
+```json
+{
+  "status": "OK",
+  "data": {
+    "rows": [
+      {
+        "nat_subgroup_id": 0,
+        "nat_subgroup_name": "",
+        "sales_amount": 0,
+        "detail_count": 0,
+        "company_count": 0
+      }
+    ]
+  }
+}
+```
+
+#### 7. ETL Refresh
+
+**Route:** `POST /dashboard/sales/refresh`
+
+Purpose:
+
+- manual trigger ETL oleh admin/dev
+
+Response:
+
+```json
+{
+  "status": "OK",
+  "data": {
+    "job_name": "sales_dashboard_refresh",
+    "message": "Refresh started"
+  }
+}
+```
+
+---
+
+## PHP Function Proposal
+
+Di controller `dashboard/Sales.php`, fungsi yang disarankan:
+
+- `summary()`
+- `trend()`
+- `breakdown()`
+- `company_ranking()`
+- `orders()`
+- `subgroup_contribution()`
+- `refresh()`
+
+Di library/service baru, misalnya `application/libraries/SalesDashboardService.php`:
+
+- `buildFilter(array $params): array`
+- `getSummary(array $filters): array`
+- `getTrend(array $filters, string $granularity): array`
+- `getBreakdown(array $filters, string $dimension, string $metric): array`
+- `getCompanyRanking(array $filters, array $paging): array`
+- `getOrders(array $filters, array $paging): array`
+- `getSubgroupContribution(array $filters, array $paging): array`
+- `runRefresh(?string $forcedFrom = null): array`
+- `refreshOrderFact(?string $watermark = null): array`
+- `refreshSubgroupFact(?string $watermark = null): array`
+
+---
+
+## SQL Semantics by Use Case
+
+### Summary without subgroup filter
+
+Source utama:
+
+- `one_lab_etl.sales_dashboard_order`
+
+### Summary with subgroup filter
+
+Source utama:
+
+- `one_lab_etl.sales_dashboard_order_subgroup`
+
+Logic:
+
+- bila `view_mode = contribution`, agregasi nominal dari detail fact
+- bila `view_mode = order`, filter order yang punya subgroup terkait lalu join ke order fact
+
+### Trend sales vs payment
+
+Gunakan:
+
+- sales berdasarkan `order_date_key`
+- payment berdasarkan `payment_date_last` untuk phase 1 sederhana
+
+Catatan:
+
+Jika owner butuh cash-in by actual payment day yang akurat penuh, phase berikutnya perlu mart payment harian terpisah.
+
+---
+
+## Recommended Future Extension
+
+### Optional Table: `sales_dashboard_payment`
+
+Grain: `1 row = 1 payment`
+
+Dipakai bila nanti butuh:
+
+- cash-in trend murni berdasarkan tanggal bayar,
+- payment method analysis,
+- rekonsiliasi koleksi lebih detail.
+
+Untuk phase 1, tabel ini opsional.
+
+---
+
+## UAT Checklist
+
+1. Summary total sales sesuai order aktif pada periode yang sama.
+2. Total paid sesuai akumulasi `f_payment` aktif.
+3. Lunas count sesuai flag `f_payment_orderheader`.
+4. Outstanding count dan nominal sesuai expected manual sample.
+5. Filter `company` bekerja konsisten di summary, chart, dan table.
+6. Filter `company type group` bekerja konsisten.
+7. Filter `omzet type` bekerja konsisten.
+8. Filter `nat_subgroup` menampilkan kontribusi subgroup yang benar.
+9. Top company dan subgroup ranking konsisten dengan sample query manual.
+10. Refresh ETL tidak membuat duplicate row pada mart.
+
+---
+
+## Risks
+
+1. Definisi `lunas` dan `outstanding` bisa berbeda antara report lama dan kebutuhan dashboard baru.
+2. Jika filter subgroup dipaksa memakai full order value tanpa mode khusus, angka bisa misleading.
+3. Data payment historis bisa perlu mart terpisah bila owner ingin cashflow by actual payment day.
+4. Jika update transaksi lama sering terjadi, ETL incremental harus cukup hati-hati memilih order yang direbuild.
+
+---
+
+## Open Questions for Approval
+
+1. Saat filter `nat_subgroup` aktif, apakah default yang diinginkan:
+   - `contribution view` berbasis detail amount, atau
+   - `order view` berbasis full order amount?
+2. Untuk KPI owner, apakah `sales` mau dianggap:
+   - `gross order total`, atau
+   - `net detail total` dari item setelah diskon?
+3. Apakah cash-in trend perlu by `actual payment date` dari awal phase 1?
+4. Apakah perlu dimensi tambahan `marketing/staff` karena `m_company` punya `M_CompanyM_StaffID`?
+
+---
+
+## Recommended Phase Plan
+
+### Phase 1
+
+- buat tabel mart:
+- `sales_dashboard_order`
+- `sales_dashboard_order_subgroup`
+- `sales_dashboard_etl_log`
+- buat endpoint:
+  - `summary`
+  - `trend`
+  - `breakdown`
+  - `company_ranking`
+  - `orders`
+  - `subgroup_contribution`
+  - `refresh`
+
+### Phase 2
+
+- tambah `sales_dashboard_payment`
+- tambah chart cash-in by payment date murni
+- tambah analisis staff marketing
+- tambah alert outstanding company besar
+
+---
+
+## Recommendation
+
+Saya rekomendasikan lanjut implementasi dengan pendekatan:
+
+1. mart fisik untuk order-level dan subgroup-level,
+2. API PHP berbasis mart, bukan query operasional mentah,
+3. default subgroup mode = `contribution view`,
+4. phase 1 fokus owner + marketing summary yang cepat dan stabil,
+5. payment mart detail dijadikan phase 2 bila dibutuhkan owner untuk cashflow yang lebih presisi.