diff --git a/inventory-server/db/metrics-schema-new.sql b/inventory-server/db/metrics-schema-new.sql index 0321e6a..15dfe61 100644 --- a/inventory-server/db/metrics-schema-new.sql +++ b/inventory-server/db/metrics-schema-new.sql @@ -116,6 +116,7 @@ CREATE TABLE public.product_metrics ( -- Lifetime Metrics (Recalculated Hourly/Daily from daily_product_snapshots) lifetime_sales INT, lifetime_revenue NUMERIC(16, 4), + lifetime_revenue_quality VARCHAR(10), -- 'exact', 'partial', 'estimated' -- First Period Metrics (Calculated Once/Periodically from daily_product_snapshots) first_7_days_sales INT, first_7_days_revenue NUMERIC(14, 4), @@ -176,6 +177,29 @@ CREATE TABLE public.product_metrics ( -- Product Status (Calculated from metrics) status VARCHAR, -- Stores status values like: Critical, Reorder Soon, Healthy, Overstock, At Risk, New + -- Growth Metrics (P3) + sales_growth_30d_vs_prev NUMERIC(10, 2), -- % growth current 30d vs prev 30d + revenue_growth_30d_vs_prev NUMERIC(10, 2), -- % growth current 30d vs prev 30d + sales_growth_yoy NUMERIC(10, 2), -- Year-over-year sales growth % + revenue_growth_yoy NUMERIC(10, 2), -- Year-over-year revenue growth % + + -- Demand Variability Metrics (P3) + sales_variance_30d NUMERIC(10, 2), -- Variance of daily sales + sales_std_dev_30d NUMERIC(10, 2), -- Standard deviation of daily sales + sales_cv_30d NUMERIC(10, 2), -- Coefficient of variation + demand_pattern VARCHAR(20), -- 'stable', 'variable', 'sporadic', 'lumpy' + + -- Service Level & Fill Rate (P5) + fill_rate_30d NUMERIC(8, 2), -- % of demand fulfilled from stock + stockout_incidents_30d INT, -- Days with stockouts + service_level_30d NUMERIC(8, 2), -- % of days without stockouts + lost_sales_incidents_30d INT, -- Days with potential lost sales + + -- Seasonality (P5) + seasonality_index NUMERIC(10, 2), -- Current vs average (100 = average) + seasonal_pattern VARCHAR(20), -- 'none', 'weekly', 'monthly', 'quarterly', 'yearly' + peak_season VARCHAR(20), -- e.g., 'Q4', 'summer', 'holiday' + CONSTRAINT fk_product_metrics_pid FOREIGN KEY (pid) REFERENCES public.products(pid) ON DELETE CASCADE ON UPDATE CASCADE ); @@ -242,7 +266,8 @@ CREATE TABLE public.category_metrics ( -- Calculated KPIs (Based on 30d aggregates) - Apply to rolled-up metrics avg_margin_30d NUMERIC(7, 3), -- (profit / revenue) * 100 stock_turn_30d NUMERIC(10, 3), -- sales_units / avg_stock_units (Needs avg stock calc) - -- growth_rate_30d NUMERIC(7, 3), -- (current 30d rev - prev 30d rev) / prev 30d rev + sales_growth_30d_vs_prev NUMERIC(10, 2), -- % growth in sales units + revenue_growth_30d_vs_prev NUMERIC(10, 2), -- % growth in revenue CONSTRAINT fk_category_metrics_cat_id FOREIGN KEY (category_id) REFERENCES public.categories(cat_id) ON DELETE CASCADE ON UPDATE CASCADE ); @@ -280,7 +305,9 @@ CREATE TABLE public.vendor_metrics ( lifetime_sales INT NOT NULL DEFAULT 0, lifetime_revenue NUMERIC(18, 4) NOT NULL DEFAULT 0.00, -- Calculated KPIs (Based on 30d aggregates) - avg_margin_30d NUMERIC(14, 4) -- (profit / revenue) * 100 + avg_margin_30d NUMERIC(14, 4), -- (profit / revenue) * 100 + sales_growth_30d_vs_prev NUMERIC(10, 2), -- % growth in sales units + revenue_growth_30d_vs_prev NUMERIC(10, 2), -- % growth in revenue -- Add more KPIs if needed (e.g., avg product value, sell-through rate for vendor) ); CREATE INDEX idx_vendor_metrics_active_count ON public.vendor_metrics(active_product_count); @@ -309,7 +336,9 @@ CREATE TABLE public.brand_metrics ( lifetime_sales INT NOT NULL DEFAULT 0, lifetime_revenue NUMERIC(18, 4) NOT NULL DEFAULT 0.00, -- Calculated KPIs (Based on 30d aggregates) - avg_margin_30d NUMERIC(7, 3) -- (profit / revenue) * 100 + avg_margin_30d NUMERIC(7, 3), -- (profit / revenue) * 100 + sales_growth_30d_vs_prev NUMERIC(10, 2), -- % growth in sales units + revenue_growth_30d_vs_prev NUMERIC(10, 2), -- % growth in revenue -- Add more KPIs if needed (e.g., avg product value, sell-through rate for brand) ); CREATE INDEX idx_brand_metrics_active_count ON public.brand_metrics(active_product_count); \ No newline at end of file diff --git a/inventory-server/scripts/calculate-metrics-new.js b/inventory-server/scripts/calculate-metrics-new.js index 8903976..c0dd718 100644 --- a/inventory-server/scripts/calculate-metrics-new.js +++ b/inventory-server/scripts/calculate-metrics-new.js @@ -437,7 +437,6 @@ async function executeSqlStep(config, progress) { try { // Try executing exactly as individual scripts do - console.log('Executing SQL with simple query method...'); const result = await connection.query(sqlQuery); // Try to extract row count from result diff --git a/inventory-server/scripts/metrics-new/calculate_brand_metrics.sql b/inventory-server/scripts/metrics-new/calculate_brand_metrics.sql index 84ca91f..f0fd505 100644 --- a/inventory-server/scripts/metrics-new/calculate_brand_metrics.sql +++ b/inventory-server/scripts/metrics-new/calculate_brand_metrics.sql @@ -42,6 +42,20 @@ BEGIN JOIN public.products p ON pm.pid = p.pid GROUP BY brand_group ), + PreviousPeriodBrandMetrics AS ( + -- Get previous period metrics for growth calculation + SELECT + COALESCE(p.brand, 'Unbranded') AS brand_group, + SUM(CASE WHEN dps.snapshot_date >= CURRENT_DATE - INTERVAL '59 days' + AND dps.snapshot_date < CURRENT_DATE - INTERVAL '29 days' + THEN dps.units_sold ELSE 0 END) AS sales_prev_30d, + SUM(CASE WHEN dps.snapshot_date >= CURRENT_DATE - INTERVAL '59 days' + AND dps.snapshot_date < CURRENT_DATE - INTERVAL '29 days' + THEN dps.net_revenue ELSE 0 END) AS revenue_prev_30d + FROM public.daily_product_snapshots dps + JOIN public.products p ON dps.pid = p.pid + GROUP BY brand_group + ), AllBrands AS ( -- Ensure all brands from products table are included, mapping NULL/empty to 'Unbranded' SELECT DISTINCT COALESCE(brand, 'Unbranded') as brand_group @@ -53,7 +67,8 @@ BEGIN current_stock_units, current_stock_cost, current_stock_retail, sales_7d, revenue_7d, sales_30d, revenue_30d, profit_30d, cogs_30d, sales_365d, revenue_365d, lifetime_sales, lifetime_revenue, - avg_margin_30d + avg_margin_30d, + sales_growth_30d_vs_prev, revenue_growth_30d_vs_prev ) SELECT b.brand_group, @@ -78,9 +93,13 @@ BEGIN -- This is mathematically equivalent to profit/revenue but more explicit ((COALESCE(ba.revenue_30d, 0) - COALESCE(ba.cogs_30d, 0)) / COALESCE(ba.revenue_30d, 1)) * 100.0 ELSE NULL -- No margin for low/no revenue brands - END + END, + -- Growth metrics + std_numeric(safe_divide((ba.sales_30d - ppbm.sales_prev_30d) * 100.0, ppbm.sales_prev_30d), 2), + std_numeric(safe_divide((ba.revenue_30d - ppbm.revenue_prev_30d) * 100.0, ppbm.revenue_prev_30d), 2) FROM AllBrands b LEFT JOIN BrandAggregates ba ON b.brand_group = ba.brand_group + LEFT JOIN PreviousPeriodBrandMetrics ppbm ON b.brand_group = ppbm.brand_group ON CONFLICT (brand_name) DO UPDATE SET last_calculated = EXCLUDED.last_calculated, @@ -95,7 +114,9 @@ BEGIN profit_30d = EXCLUDED.profit_30d, cogs_30d = EXCLUDED.cogs_30d, sales_365d = EXCLUDED.sales_365d, revenue_365d = EXCLUDED.revenue_365d, lifetime_sales = EXCLUDED.lifetime_sales, lifetime_revenue = EXCLUDED.lifetime_revenue, - avg_margin_30d = EXCLUDED.avg_margin_30d + avg_margin_30d = EXCLUDED.avg_margin_30d, + sales_growth_30d_vs_prev = EXCLUDED.sales_growth_30d_vs_prev, + revenue_growth_30d_vs_prev = EXCLUDED.revenue_growth_30d_vs_prev WHERE -- Only update if at least one value has changed brand_metrics.product_count IS DISTINCT FROM EXCLUDED.product_count OR brand_metrics.active_product_count IS DISTINCT FROM EXCLUDED.active_product_count OR diff --git a/inventory-server/scripts/metrics-new/calculate_category_metrics.sql b/inventory-server/scripts/metrics-new/calculate_category_metrics.sql index ae7f549..a55d2ef 100644 --- a/inventory-server/scripts/metrics-new/calculate_category_metrics.sql +++ b/inventory-server/scripts/metrics-new/calculate_category_metrics.sql @@ -1,5 +1,5 @@ --- Description: Calculates and updates aggregated metrics per category. --- Dependencies: product_metrics, products, categories, product_categories, calculate_status table. +-- Description: Calculates and updates aggregated metrics per category with hierarchy rollups. +-- Dependencies: product_metrics, products, categories, product_categories, category_hierarchy, calculate_status table. -- Frequency: Daily (after product_metrics update). DO $$ @@ -9,55 +9,21 @@ DECLARE _min_revenue NUMERIC := 50.00; -- Minimum revenue threshold for margin calculation BEGIN RAISE NOTICE 'Running % calculation...', _module_name; + + -- Refresh the category hierarchy materialized view first + REFRESH MATERIALIZED VIEW CONCURRENTLY category_hierarchy; - WITH - -- Identify the hierarchy depth for each category - CategoryDepth AS ( - WITH RECURSIVE CategoryTree AS ( - -- Base case: Start with categories without parents (root categories) - SELECT cat_id, name, parent_id, 0 AS depth - FROM public.categories - WHERE parent_id IS NULL - - UNION ALL - - -- Recursive step: Add child categories with incremented depth - SELECT c.cat_id, c.name, c.parent_id, ct.depth + 1 - FROM public.categories c - JOIN CategoryTree ct ON c.parent_id = ct.cat_id - ) - SELECT cat_id, depth - FROM CategoryTree - ), - -- For each product, find the most specific (deepest) category it belongs to - ProductDeepestCategory AS ( - SELECT - pc.pid, - pc.cat_id - FROM public.product_categories pc - JOIN CategoryDepth cd ON pc.cat_id = cd.cat_id - -- This is the key part: for each product, select only the category with maximum depth - WHERE (pc.pid, cd.depth) IN ( - SELECT pc2.pid, MAX(cd2.depth) - FROM public.product_categories pc2 - JOIN CategoryDepth cd2 ON pc2.cat_id = cd2.cat_id - GROUP BY pc2.pid - ) - ), - -- Calculate metrics only at the most specific category level for each product - -- These are the direct metrics (only products directly in this category) - DirectCategoryMetrics AS ( + -- First calculate direct metrics (products directly in each category) + WITH DirectCategoryMetrics AS ( SELECT - pdc.cat_id, - -- Counts + pc.cat_id, COUNT(DISTINCT pm.pid) AS product_count, COUNT(DISTINCT CASE WHEN pm.is_visible THEN pm.pid END) AS active_product_count, COUNT(DISTINCT CASE WHEN pm.is_replenishable THEN pm.pid END) AS replenishable_product_count, - -- Current Stock SUM(pm.current_stock) AS current_stock_units, SUM(pm.current_stock_cost) AS current_stock_cost, SUM(pm.current_stock_retail) AS current_stock_retail, - -- Rolling Periods - Only include products with actual sales in each period + -- Sales metrics with proper filtering SUM(CASE WHEN pm.sales_7d > 0 THEN pm.sales_7d ELSE 0 END) AS sales_7d, SUM(CASE WHEN pm.revenue_7d > 0 THEN pm.revenue_7d ELSE 0 END) AS revenue_7d, SUM(CASE WHEN pm.sales_30d > 0 THEN pm.sales_30d ELSE 0 END) AS sales_30d, @@ -67,179 +33,141 @@ BEGIN SUM(CASE WHEN pm.sales_365d > 0 THEN pm.sales_365d ELSE 0 END) AS sales_365d, SUM(CASE WHEN pm.revenue_365d > 0 THEN pm.revenue_365d ELSE 0 END) AS revenue_365d, SUM(CASE WHEN pm.lifetime_sales > 0 THEN pm.lifetime_sales ELSE 0 END) AS lifetime_sales, - SUM(CASE WHEN pm.lifetime_revenue > 0 THEN pm.lifetime_revenue ELSE 0 END) AS lifetime_revenue, - -- Data for KPIs - Only average stock for products with stock - SUM(CASE WHEN pm.avg_stock_units_30d > 0 THEN pm.avg_stock_units_30d ELSE 0 END) AS total_avg_stock_units_30d - FROM public.product_metrics pm - JOIN ProductDeepestCategory pdc ON pm.pid = pdc.pid - GROUP BY pdc.cat_id + SUM(CASE WHEN pm.lifetime_revenue > 0 THEN pm.lifetime_revenue ELSE 0 END) AS lifetime_revenue + FROM public.product_categories pc + JOIN public.product_metrics pm ON pc.pid = pm.pid + GROUP BY pc.cat_id ), - -- Build a category lookup table for parent relationships - CategoryHierarchyPaths AS ( - WITH RECURSIVE ParentPaths AS ( - -- Base case: All categories with their immediate parents - SELECT - cat_id, - cat_id as leaf_id, -- Every category is its own leaf initially - ARRAY[cat_id] as path - FROM public.categories - - UNION ALL - - -- Recursive step: Walk up the parent chain - SELECT - c.parent_id as cat_id, - pp.leaf_id, -- Keep the original leaf_id - c.parent_id || pp.path as path - FROM ParentPaths pp - JOIN public.categories c ON pp.cat_id = c.cat_id - WHERE c.parent_id IS NOT NULL -- Stop at root categories - ) - -- Select distinct paths to avoid duplication - SELECT DISTINCT cat_id, leaf_id - FROM ParentPaths - ), - -- Aggregate metrics from leaf categories to their ancestors without duplication - -- These are the rolled-up metrics (including all child categories) - RollupMetrics AS ( + -- Calculate rolled-up metrics (including all descendant categories) + RolledUpMetrics AS ( SELECT - chp.cat_id, - -- For each parent category, count distinct products to avoid duplication - COUNT(DISTINCT dcm.cat_id) AS child_categories_count, - SUM(dcm.product_count) AS rollup_product_count, - SUM(dcm.active_product_count) AS rollup_active_product_count, - SUM(dcm.replenishable_product_count) AS rollup_replenishable_product_count, - SUM(dcm.current_stock_units) AS rollup_current_stock_units, - SUM(dcm.current_stock_cost) AS rollup_current_stock_cost, - SUM(dcm.current_stock_retail) AS rollup_current_stock_retail, - SUM(dcm.sales_7d) AS rollup_sales_7d, - SUM(dcm.revenue_7d) AS rollup_revenue_7d, - SUM(dcm.sales_30d) AS rollup_sales_30d, - SUM(dcm.revenue_30d) AS rollup_revenue_30d, - SUM(dcm.cogs_30d) AS rollup_cogs_30d, - SUM(dcm.profit_30d) AS rollup_profit_30d, - SUM(dcm.sales_365d) AS rollup_sales_365d, - SUM(dcm.revenue_365d) AS rollup_revenue_365d, - SUM(dcm.lifetime_sales) AS rollup_lifetime_sales, - SUM(dcm.lifetime_revenue) AS rollup_lifetime_revenue, - SUM(dcm.total_avg_stock_units_30d) AS rollup_total_avg_stock_units_30d - FROM CategoryHierarchyPaths chp - JOIN DirectCategoryMetrics dcm ON chp.leaf_id = dcm.cat_id - GROUP BY chp.cat_id + ch.cat_id, + -- Sum metrics from this category and all its descendants + SUM(dcm.product_count) AS product_count, + SUM(dcm.active_product_count) AS active_product_count, + SUM(dcm.replenishable_product_count) AS replenishable_product_count, + SUM(dcm.current_stock_units) AS current_stock_units, + SUM(dcm.current_stock_cost) AS current_stock_cost, + SUM(dcm.current_stock_retail) AS current_stock_retail, + SUM(dcm.sales_7d) AS sales_7d, + SUM(dcm.revenue_7d) AS revenue_7d, + SUM(dcm.sales_30d) AS sales_30d, + SUM(dcm.revenue_30d) AS revenue_30d, + SUM(dcm.cogs_30d) AS cogs_30d, + SUM(dcm.profit_30d) AS profit_30d, + SUM(dcm.sales_365d) AS sales_365d, + SUM(dcm.revenue_365d) AS revenue_365d, + SUM(dcm.lifetime_sales) AS lifetime_sales, + SUM(dcm.lifetime_revenue) AS lifetime_revenue + FROM category_hierarchy ch + LEFT JOIN DirectCategoryMetrics dcm ON + dcm.cat_id = ch.cat_id OR + dcm.cat_id = ANY(SELECT cat_id FROM category_hierarchy WHERE ch.cat_id = ANY(ancestor_ids)) + GROUP BY ch.cat_id ), - -- Combine direct and rollup metrics - CombinedMetrics AS ( + PreviousPeriodCategoryMetrics AS ( + -- Get previous period metrics for growth calculation SELECT + pc.cat_id, + SUM(CASE WHEN dps.snapshot_date >= CURRENT_DATE - INTERVAL '59 days' + AND dps.snapshot_date < CURRENT_DATE - INTERVAL '29 days' + THEN dps.units_sold ELSE 0 END) AS sales_prev_30d, + SUM(CASE WHEN dps.snapshot_date >= CURRENT_DATE - INTERVAL '59 days' + AND dps.snapshot_date < CURRENT_DATE - INTERVAL '29 days' + THEN dps.net_revenue ELSE 0 END) AS revenue_prev_30d + FROM public.daily_product_snapshots dps + JOIN public.product_categories pc ON dps.pid = pc.pid + GROUP BY pc.cat_id + ), + RolledUpPreviousPeriod AS ( + -- Calculate rolled-up previous period metrics + SELECT + ch.cat_id, + SUM(ppcm.sales_prev_30d) AS sales_prev_30d, + SUM(ppcm.revenue_prev_30d) AS revenue_prev_30d + FROM category_hierarchy ch + LEFT JOIN PreviousPeriodCategoryMetrics ppcm ON + ppcm.cat_id = ch.cat_id OR + ppcm.cat_id = ANY(SELECT cat_id FROM category_hierarchy WHERE ch.cat_id = ANY(ancestor_ids)) + GROUP BY ch.cat_id + ), + AllCategories AS ( + -- Ensure all categories are included + SELECT c.cat_id, c.name, c.type, - c.parent_id, - -- Direct metrics (just this category) - COALESCE(dcm.product_count, 0) AS direct_product_count, - COALESCE(dcm.active_product_count, 0) AS direct_active_product_count, - COALESCE(dcm.replenishable_product_count, 0) AS direct_replenishable_product_count, - COALESCE(dcm.current_stock_units, 0) AS direct_current_stock_units, - COALESCE(dcm.current_stock_cost, 0) AS direct_current_stock_cost, - COALESCE(dcm.current_stock_retail, 0) AS direct_current_stock_retail, - COALESCE(dcm.sales_7d, 0) AS direct_sales_7d, - COALESCE(dcm.revenue_7d, 0) AS direct_revenue_7d, - COALESCE(dcm.sales_30d, 0) AS direct_sales_30d, - COALESCE(dcm.revenue_30d, 0) AS direct_revenue_30d, - COALESCE(dcm.cogs_30d, 0) AS direct_cogs_30d, - COALESCE(dcm.profit_30d, 0) AS direct_profit_30d, - COALESCE(dcm.sales_365d, 0) AS direct_sales_365d, - COALESCE(dcm.revenue_365d, 0) AS direct_revenue_365d, - COALESCE(dcm.lifetime_sales, 0) AS direct_lifetime_sales, - COALESCE(dcm.lifetime_revenue, 0) AS direct_lifetime_revenue, - COALESCE(dcm.total_avg_stock_units_30d, 0) AS direct_avg_stock_units_30d, - - -- Rolled up metrics (this category + all children) - COALESCE(rm.rollup_product_count, 0) AS product_count, - COALESCE(rm.rollup_active_product_count, 0) AS active_product_count, - COALESCE(rm.rollup_replenishable_product_count, 0) AS replenishable_product_count, - COALESCE(rm.rollup_current_stock_units, 0) AS current_stock_units, - COALESCE(rm.rollup_current_stock_cost, 0) AS current_stock_cost, - COALESCE(rm.rollup_current_stock_retail, 0) AS current_stock_retail, - COALESCE(rm.rollup_sales_7d, 0) AS sales_7d, - COALESCE(rm.rollup_revenue_7d, 0) AS revenue_7d, - COALESCE(rm.rollup_sales_30d, 0) AS sales_30d, - COALESCE(rm.rollup_revenue_30d, 0) AS revenue_30d, - COALESCE(rm.rollup_cogs_30d, 0) AS cogs_30d, - COALESCE(rm.rollup_profit_30d, 0) AS profit_30d, - COALESCE(rm.rollup_sales_365d, 0) AS sales_365d, - COALESCE(rm.rollup_revenue_365d, 0) AS revenue_365d, - COALESCE(rm.rollup_lifetime_sales, 0) AS lifetime_sales, - COALESCE(rm.rollup_lifetime_revenue, 0) AS lifetime_revenue, - COALESCE(rm.rollup_total_avg_stock_units_30d, 0) AS total_avg_stock_units_30d + c.parent_id FROM public.categories c - LEFT JOIN DirectCategoryMetrics dcm ON c.cat_id = dcm.cat_id - LEFT JOIN RollupMetrics rm ON c.cat_id = rm.cat_id + WHERE c.status = 'active' ) INSERT INTO public.category_metrics ( category_id, category_name, category_type, parent_id, last_calculated, - -- Store all direct and rolled up metrics + -- Rolled-up metrics product_count, active_product_count, replenishable_product_count, current_stock_units, current_stock_cost, current_stock_retail, sales_7d, revenue_7d, sales_30d, revenue_30d, profit_30d, cogs_30d, sales_365d, revenue_365d, lifetime_sales, lifetime_revenue, - -- Also store direct metrics with direct_ prefix + -- Direct metrics direct_product_count, direct_active_product_count, direct_replenishable_product_count, direct_current_stock_units, direct_stock_cost, direct_stock_retail, - direct_sales_7d, direct_revenue_7d, direct_sales_30d, direct_revenue_30d, + direct_sales_7d, direct_revenue_7d, direct_sales_30d, direct_revenue_30d, direct_profit_30d, direct_cogs_30d, direct_sales_365d, direct_revenue_365d, direct_lifetime_sales, direct_lifetime_revenue, -- KPIs - avg_margin_30d, stock_turn_30d + avg_margin_30d, + sales_growth_30d_vs_prev, revenue_growth_30d_vs_prev ) SELECT - cm.cat_id, - cm.name, - cm.type, - cm.parent_id, + ac.cat_id, + ac.name, + ac.type, + ac.parent_id, _start_time, - -- Rolled-up metrics (total including children) - cm.product_count, - cm.active_product_count, - cm.replenishable_product_count, - cm.current_stock_units, - cm.current_stock_cost, - cm.current_stock_retail, - cm.sales_7d, cm.revenue_7d, - cm.sales_30d, cm.revenue_30d, cm.profit_30d, cm.cogs_30d, - cm.sales_365d, cm.revenue_365d, - cm.lifetime_sales, cm.lifetime_revenue, - -- Direct metrics (just this category) - cm.direct_product_count, - cm.direct_active_product_count, - cm.direct_replenishable_product_count, - cm.direct_current_stock_units, - cm.direct_current_stock_cost, - cm.direct_current_stock_retail, - cm.direct_sales_7d, cm.direct_revenue_7d, - cm.direct_sales_30d, cm.direct_revenue_30d, cm.direct_profit_30d, cm.direct_cogs_30d, - cm.direct_sales_365d, cm.direct_revenue_365d, - cm.direct_lifetime_sales, cm.direct_lifetime_revenue, + -- Rolled-up metrics (includes descendants) + COALESCE(rum.product_count, 0), + COALESCE(rum.active_product_count, 0), + COALESCE(rum.replenishable_product_count, 0), + COALESCE(rum.current_stock_units, 0), + COALESCE(rum.current_stock_cost, 0.00), + COALESCE(rum.current_stock_retail, 0.00), + COALESCE(rum.sales_7d, 0), COALESCE(rum.revenue_7d, 0.00), + COALESCE(rum.sales_30d, 0), COALESCE(rum.revenue_30d, 0.00), + COALESCE(rum.profit_30d, 0.00), COALESCE(rum.cogs_30d, 0.00), + COALESCE(rum.sales_365d, 0), COALESCE(rum.revenue_365d, 0.00), + COALESCE(rum.lifetime_sales, 0), COALESCE(rum.lifetime_revenue, 0.00), + -- Direct metrics (only this category) + COALESCE(dcm.product_count, 0), + COALESCE(dcm.active_product_count, 0), + COALESCE(dcm.replenishable_product_count, 0), + COALESCE(dcm.current_stock_units, 0), + COALESCE(dcm.current_stock_cost, 0.00), + COALESCE(dcm.current_stock_retail, 0.00), + COALESCE(dcm.sales_7d, 0), COALESCE(dcm.revenue_7d, 0.00), + COALESCE(dcm.sales_30d, 0), COALESCE(dcm.revenue_30d, 0.00), + COALESCE(dcm.profit_30d, 0.00), COALESCE(dcm.cogs_30d, 0.00), + COALESCE(dcm.sales_365d, 0), COALESCE(dcm.revenue_365d, 0.00), + COALESCE(dcm.lifetime_sales, 0), COALESCE(dcm.lifetime_revenue, 0.00), -- KPIs - Calculate margin only for categories with significant revenue CASE - WHEN cm.revenue_30d >= _min_revenue THEN - ((cm.revenue_30d - cm.cogs_30d) / cm.revenue_30d) * 100.0 - ELSE NULL -- No margin for low/no revenue categories + WHEN COALESCE(rum.revenue_30d, 0) >= _min_revenue THEN + ((COALESCE(rum.revenue_30d, 0) - COALESCE(rum.cogs_30d, 0)) / COALESCE(rum.revenue_30d, 1)) * 100.0 + ELSE NULL END, - -- Stock Turn calculation - CASE - WHEN cm.total_avg_stock_units_30d > 0 THEN - cm.sales_30d / cm.total_avg_stock_units_30d - ELSE NULL -- No stock turn if no average stock - END - FROM CombinedMetrics cm + -- Growth metrics for rolled-up values + std_numeric(safe_divide((rum.sales_30d - rupp.sales_prev_30d) * 100.0, rupp.sales_prev_30d), 2), + std_numeric(safe_divide((rum.revenue_30d - rupp.revenue_prev_30d) * 100.0, rupp.revenue_prev_30d), 2) + FROM AllCategories ac + LEFT JOIN DirectCategoryMetrics dcm ON ac.cat_id = dcm.cat_id + LEFT JOIN RolledUpMetrics rum ON ac.cat_id = rum.cat_id + LEFT JOIN RolledUpPreviousPeriod rupp ON ac.cat_id = rupp.cat_id ON CONFLICT (category_id) DO UPDATE SET + last_calculated = EXCLUDED.last_calculated, category_name = EXCLUDED.category_name, category_type = EXCLUDED.category_type, parent_id = EXCLUDED.parent_id, - last_calculated = EXCLUDED.last_calculated, - - -- ROLLED-UP METRICS (includes this category + all descendants) + -- Rolled-up metrics product_count = EXCLUDED.product_count, active_product_count = EXCLUDED.active_product_count, replenishable_product_count = EXCLUDED.replenishable_product_count, @@ -251,8 +179,7 @@ BEGIN profit_30d = EXCLUDED.profit_30d, cogs_30d = EXCLUDED.cogs_30d, sales_365d = EXCLUDED.sales_365d, revenue_365d = EXCLUDED.revenue_365d, lifetime_sales = EXCLUDED.lifetime_sales, lifetime_revenue = EXCLUDED.lifetime_revenue, - - -- DIRECT METRICS (only products directly in this category) + -- Direct metrics direct_product_count = EXCLUDED.direct_product_count, direct_active_product_count = EXCLUDED.direct_active_product_count, direct_replenishable_product_count = EXCLUDED.direct_replenishable_product_count, @@ -264,10 +191,9 @@ BEGIN direct_profit_30d = EXCLUDED.direct_profit_30d, direct_cogs_30d = EXCLUDED.direct_cogs_30d, direct_sales_365d = EXCLUDED.direct_sales_365d, direct_revenue_365d = EXCLUDED.direct_revenue_365d, direct_lifetime_sales = EXCLUDED.direct_lifetime_sales, direct_lifetime_revenue = EXCLUDED.direct_lifetime_revenue, - - -- Calculated KPIs avg_margin_30d = EXCLUDED.avg_margin_30d, - stock_turn_30d = EXCLUDED.stock_turn_30d + sales_growth_30d_vs_prev = EXCLUDED.sales_growth_30d_vs_prev, + revenue_growth_30d_vs_prev = EXCLUDED.revenue_growth_30d_vs_prev WHERE -- Only update if at least one value has changed category_metrics.product_count IS DISTINCT FROM EXCLUDED.product_count OR category_metrics.active_product_count IS DISTINCT FROM EXCLUDED.active_product_count OR @@ -291,19 +217,23 @@ WITH update_stats AS ( SELECT COUNT(*) as total_categories, COUNT(*) FILTER (WHERE last_calculated >= NOW() - INTERVAL '5 minutes') as rows_processed, - COUNT(*) FILTER (WHERE category_type = 11) as main_categories, -- 11 = category - COUNT(*) FILTER (WHERE category_type = 12) as subcategories, -- 12 = subcategory - SUM(product_count) as total_products, - SUM(active_product_count) as total_active_products, - SUM(current_stock_units) as total_stock_units + COUNT(*) FILTER (WHERE category_type = 10) as sections, + COUNT(*) FILTER (WHERE category_type = 11) as categories, + COUNT(*) FILTER (WHERE category_type = 12) as subcategories, + SUM(product_count) as total_products_rolled, + SUM(direct_product_count) as total_products_direct, + SUM(sales_30d) as total_sales_30d, + SUM(revenue_30d) as total_revenue_30d FROM public.category_metrics ) SELECT rows_processed, total_categories, - main_categories, + sections, + categories, subcategories, - total_products::int, - total_active_products::int, - total_stock_units::int + total_products_rolled::int, + total_products_direct::int, + total_sales_30d::int, + ROUND(total_revenue_30d, 2) as total_revenue_30d FROM update_stats; \ No newline at end of file diff --git a/inventory-server/scripts/metrics-new/calculate_vendor_metrics.sql b/inventory-server/scripts/metrics-new/calculate_vendor_metrics.sql index 7ad10df..04eb2cf 100644 --- a/inventory-server/scripts/metrics-new/calculate_vendor_metrics.sql +++ b/inventory-server/scripts/metrics-new/calculate_vendor_metrics.sql @@ -44,6 +44,21 @@ BEGIN WHERE p.vendor IS NOT NULL AND p.vendor <> '' GROUP BY p.vendor ), + PreviousPeriodVendorMetrics AS ( + -- Get previous period metrics for growth calculation + SELECT + p.vendor, + SUM(CASE WHEN dps.snapshot_date >= CURRENT_DATE - INTERVAL '59 days' + AND dps.snapshot_date < CURRENT_DATE - INTERVAL '29 days' + THEN dps.units_sold ELSE 0 END) AS sales_prev_30d, + SUM(CASE WHEN dps.snapshot_date >= CURRENT_DATE - INTERVAL '59 days' + AND dps.snapshot_date < CURRENT_DATE - INTERVAL '29 days' + THEN dps.net_revenue ELSE 0 END) AS revenue_prev_30d + FROM public.daily_product_snapshots dps + JOIN public.products p ON dps.pid = p.pid + WHERE p.vendor IS NOT NULL AND p.vendor <> '' + GROUP BY p.vendor + ), VendorPOAggregates AS ( -- Aggregate PO related stats including lead time calculated from POs to receivings SELECT @@ -78,7 +93,8 @@ BEGIN po_count_365d, avg_lead_time_days, sales_7d, revenue_7d, sales_30d, revenue_30d, profit_30d, cogs_30d, sales_365d, revenue_365d, lifetime_sales, lifetime_revenue, - avg_margin_30d + avg_margin_30d, + sales_growth_30d_vs_prev, revenue_growth_30d_vs_prev ) SELECT v.vendor, @@ -102,10 +118,14 @@ BEGIN COALESCE(vpa.sales_365d, 0), COALESCE(vpa.revenue_365d, 0.00), COALESCE(vpa.lifetime_sales, 0), COALESCE(vpa.lifetime_revenue, 0.00), -- KPIs - (vpa.profit_30d / NULLIF(vpa.revenue_30d, 0)) * 100.0 + (vpa.profit_30d / NULLIF(vpa.revenue_30d, 0)) * 100.0, + -- Growth metrics + std_numeric(safe_divide((vpa.sales_30d - ppvm.sales_prev_30d) * 100.0, ppvm.sales_prev_30d), 2), + std_numeric(safe_divide((vpa.revenue_30d - ppvm.revenue_prev_30d) * 100.0, ppvm.revenue_prev_30d), 2) FROM AllVendors v LEFT JOIN VendorProductAggregates vpa ON v.vendor = vpa.vendor LEFT JOIN VendorPOAggregates vpoa ON v.vendor = vpoa.vendor + LEFT JOIN PreviousPeriodVendorMetrics ppvm ON v.vendor = ppvm.vendor ON CONFLICT (vendor_name) DO UPDATE SET last_calculated = EXCLUDED.last_calculated, @@ -124,7 +144,9 @@ BEGIN profit_30d = EXCLUDED.profit_30d, cogs_30d = EXCLUDED.cogs_30d, sales_365d = EXCLUDED.sales_365d, revenue_365d = EXCLUDED.revenue_365d, lifetime_sales = EXCLUDED.lifetime_sales, lifetime_revenue = EXCLUDED.lifetime_revenue, - avg_margin_30d = EXCLUDED.avg_margin_30d + avg_margin_30d = EXCLUDED.avg_margin_30d, + sales_growth_30d_vs_prev = EXCLUDED.sales_growth_30d_vs_prev, + revenue_growth_30d_vs_prev = EXCLUDED.revenue_growth_30d_vs_prev WHERE -- Only update if at least one value has changed vendor_metrics.product_count IS DISTINCT FROM EXCLUDED.product_count OR vendor_metrics.active_product_count IS DISTINCT FROM EXCLUDED.active_product_count OR diff --git a/inventory-server/scripts/metrics-new/update_daily_snapshots.sql b/inventory-server/scripts/metrics-new/update_daily_snapshots.sql index 12ff9ea..ff05315 100644 --- a/inventory-server/scripts/metrics-new/update_daily_snapshots.sql +++ b/inventory-server/scripts/metrics-new/update_daily_snapshots.sql @@ -86,7 +86,14 @@ BEGIN COALESCE(SUM(CASE WHEN o.quantity > 0 AND COALESCE(o.status, 'pending') NOT IN ('canceled', 'returned') THEN o.quantity ELSE 0 END), 0) AS units_sold, COALESCE(SUM(CASE WHEN o.quantity > 0 AND COALESCE(o.status, 'pending') NOT IN ('canceled', 'returned') THEN o.price * o.quantity ELSE 0 END), 0.00) AS gross_revenue_unadjusted, -- Before discount COALESCE(SUM(CASE WHEN o.quantity > 0 AND COALESCE(o.status, 'pending') NOT IN ('canceled', 'returned') THEN o.discount ELSE 0 END), 0.00) AS discounts, - COALESCE(SUM(CASE WHEN o.quantity > 0 AND COALESCE(o.status, 'pending') NOT IN ('canceled', 'returned') THEN COALESCE(o.costeach, p.landing_cost_price, p.cost_price) * o.quantity ELSE 0 END), 0.00) AS cogs, + COALESCE(SUM(CASE WHEN o.quantity > 0 AND COALESCE(o.status, 'pending') NOT IN ('canceled', 'returned') THEN + COALESCE( + o.costeach, -- First use order-specific cost if available + get_weighted_avg_cost(p.pid, o.date::date), -- Then use weighted average cost + p.landing_cost_price, -- Fallback to landing cost + p.cost_price -- Final fallback to current cost + ) * o.quantity + ELSE 0 END), 0.00) AS cogs, COALESCE(SUM(CASE WHEN o.quantity > 0 AND COALESCE(o.status, 'pending') NOT IN ('canceled', 'returned') THEN p.regular_price * o.quantity ELSE 0 END), 0.00) AS gross_regular_revenue, -- Use current regular price for simplicity here -- Aggregate Returns (Quantity < 0 or Status = Returned) diff --git a/inventory-server/scripts/metrics-new/update_product_metrics.sql b/inventory-server/scripts/metrics-new/update_product_metrics.sql index 214bbfc..2554c55 100644 --- a/inventory-server/scripts/metrics-new/update_product_metrics.sql +++ b/inventory-server/scripts/metrics-new/update_product_metrics.sql @@ -171,6 +171,85 @@ BEGIN FROM public.products p LEFT JOIN public.settings_product sp ON p.pid = sp.pid LEFT JOIN public.settings_vendor sv ON p.vendor = sv.vendor + ), + LifetimeRevenue AS ( + -- Calculate actual revenue from orders table + SELECT + o.pid, + SUM(o.price * o.quantity - COALESCE(o.discount, 0)) AS lifetime_revenue_from_orders, + SUM(o.quantity) AS lifetime_units_from_orders + FROM public.orders o + WHERE o.status NOT IN ('canceled', 'returned') + AND o.quantity > 0 + GROUP BY o.pid + ), + PreviousPeriodMetrics AS ( + -- Calculate metrics for previous 30-day period for growth comparison + SELECT + pid, + SUM(CASE WHEN snapshot_date >= _current_date - INTERVAL '59 days' + AND snapshot_date < _current_date - INTERVAL '29 days' + THEN units_sold ELSE 0 END) AS sales_prev_30d, + SUM(CASE WHEN snapshot_date >= _current_date - INTERVAL '59 days' + AND snapshot_date < _current_date - INTERVAL '29 days' + THEN net_revenue ELSE 0 END) AS revenue_prev_30d, + -- Year-over-year comparison + SUM(CASE WHEN snapshot_date >= _current_date - INTERVAL '395 days' + AND snapshot_date < _current_date - INTERVAL '365 days' + THEN units_sold ELSE 0 END) AS sales_30d_last_year, + SUM(CASE WHEN snapshot_date >= _current_date - INTERVAL '395 days' + AND snapshot_date < _current_date - INTERVAL '365 days' + THEN net_revenue ELSE 0 END) AS revenue_30d_last_year + FROM public.daily_product_snapshots + GROUP BY pid + ), + DemandVariability AS ( + -- Calculate variance and standard deviation of daily sales + SELECT + pid, + COUNT(*) AS days_with_data, + AVG(units_sold) AS avg_daily_sales, + VARIANCE(units_sold) AS sales_variance, + STDDEV(units_sold) AS sales_std_dev, + -- Coefficient of variation + CASE + WHEN AVG(units_sold) > 0 THEN STDDEV(units_sold) / AVG(units_sold) + ELSE NULL + END AS sales_cv + FROM public.daily_product_snapshots + WHERE snapshot_date >= _current_date - INTERVAL '29 days' + AND snapshot_date <= _current_date + GROUP BY pid + ), + ServiceLevels AS ( + -- Calculate service level and fill rate metrics + SELECT + pid, + COUNT(*) FILTER (WHERE stockout_flag = true) AS stockout_incidents_30d, + COUNT(*) FILTER (WHERE stockout_flag = true AND units_sold > 0) AS lost_sales_incidents_30d, + -- Service level: percentage of days without stockouts + (1.0 - (COUNT(*) FILTER (WHERE stockout_flag = true)::NUMERIC / NULLIF(COUNT(*), 0))) * 100 AS service_level_30d, + -- Fill rate: units sold / (units sold + potential lost sales) + CASE + WHEN SUM(units_sold) > 0 THEN + (SUM(units_sold)::NUMERIC / + (SUM(units_sold) + SUM(CASE WHEN stockout_flag THEN units_sold * 0.2 ELSE 0 END))) * 100 + ELSE NULL + END AS fill_rate_30d + FROM public.daily_product_snapshots + WHERE snapshot_date >= _current_date - INTERVAL '29 days' + AND snapshot_date <= _current_date + GROUP BY pid + ), + SeasonalityAnalysis AS ( + -- Simple seasonality detection + SELECT + p.pid, + sp.seasonal_pattern, + sp.seasonality_index, + sp.peak_season + FROM products p + CROSS JOIN LATERAL detect_seasonal_pattern(p.pid) sp ) -- Final UPSERT into product_metrics INSERT INTO public.product_metrics ( @@ -187,7 +266,7 @@ BEGIN stockout_days_30d, sales_365d, revenue_365d, avg_stock_units_30d, avg_stock_cost_30d, avg_stock_retail_30d, avg_stock_gross_30d, received_qty_30d, received_cost_30d, - lifetime_sales, lifetime_revenue, + lifetime_sales, lifetime_revenue, lifetime_revenue_quality, first_7_days_sales, first_7_days_revenue, first_30_days_sales, first_30_days_revenue, first_60_days_sales, first_60_days_revenue, first_90_days_sales, first_90_days_revenue, asp_30d, acp_30d, avg_ros_30d, avg_sales_per_day_30d, avg_sales_per_month_30d, @@ -203,7 +282,13 @@ BEGIN stock_cover_in_days, po_cover_in_days, sells_out_in_days, replenish_date, overstocked_units, overstocked_cost, overstocked_retail, is_old_stock, yesterday_sales, - status -- Add status field for calculated status + status, -- Add status field for calculated status + -- New fields + sales_growth_30d_vs_prev, revenue_growth_30d_vs_prev, + sales_growth_yoy, revenue_growth_yoy, + sales_variance_30d, sales_std_dev_30d, sales_cv_30d, demand_pattern, + fill_rate_30d, stockout_incidents_30d, service_level_30d, lost_sales_incidents_30d, + seasonality_index, seasonal_pattern, peak_season ) SELECT ci.pid, _start_time, ci.sku, ci.title, ci.brand, ci.vendor, ci.image_url, ci.is_visible, ci.is_replenishable, @@ -227,27 +312,33 @@ BEGIN sa.received_qty_30d, sa.received_cost_30d, -- Use total_sold from products table as the source of truth for lifetime sales -- This includes all historical data from the production database - ci.historical_total_sold AS lifetime_sales, - COALESCE( - -- Option 1: Use 30-day average price if available - CASE WHEN sa.sales_30d > 0 THEN - ci.historical_total_sold * (sa.revenue_30d / NULLIF(sa.sales_30d, 0)) - ELSE NULL END, - -- Option 2: Try 365-day average price if available - CASE WHEN sa.sales_365d > 0 THEN - ci.historical_total_sold * (sa.revenue_365d / NULLIF(sa.sales_365d, 0)) - ELSE NULL END, - -- Option 3: Use current price as a reasonable estimate - ci.historical_total_sold * ci.current_price, - -- Option 4: Use regular price if current price might be zero - ci.historical_total_sold * ci.current_regular_price, - -- Final fallback: Use accumulated revenue (this is less accurate for old products) - sa.total_net_revenue - ) AS lifetime_revenue, + ci.historical_total_sold AS lifetime_sales, + -- Calculate lifetime revenue using actual historical prices where available + CASE + WHEN lr.lifetime_revenue_from_orders IS NOT NULL THEN + -- We have some order history - use it plus estimate for remaining + lr.lifetime_revenue_from_orders + + (GREATEST(0, ci.historical_total_sold - COALESCE(lr.lifetime_units_from_orders, 0)) * + COALESCE( + -- Use oldest known price from snapshots as proxy + (SELECT revenue_7d / NULLIF(sales_7d, 0) + FROM daily_product_snapshots + WHERE pid = ci.pid AND sales_7d > 0 + ORDER BY snapshot_date ASC + LIMIT 1), + ci.current_price + )) + ELSE + -- No order history - estimate using current price + ci.historical_total_sold * ci.current_price + END AS lifetime_revenue, + CASE + WHEN lr.lifetime_units_from_orders >= ci.historical_total_sold * 0.9 THEN 'exact' + WHEN lr.lifetime_units_from_orders >= ci.historical_total_sold * 0.5 THEN 'partial' + ELSE 'estimated' + END AS lifetime_revenue_quality, fpm.first_7_days_sales, fpm.first_7_days_revenue, fpm.first_30_days_sales, fpm.first_30_days_revenue, fpm.first_60_days_sales, fpm.first_60_days_revenue, fpm.first_90_days_sales, fpm.first_90_days_revenue, - - -- Calculated KPIs sa.revenue_30d / NULLIF(sa.sales_30d, 0) AS asp_30d, sa.cogs_30d / NULLIF(sa.sales_30d, 0) AS acp_30d, sa.profit_30d / NULLIF(sa.sales_30d, 0) AS avg_ros_30d, @@ -262,317 +353,59 @@ BEGIN (sa.stockout_days_30d / 30.0) * 100 AS stockout_rate_30d, sa.gross_regular_revenue_30d - sa.gross_revenue_30d AS markdown_30d, ((sa.gross_regular_revenue_30d - sa.gross_revenue_30d) / NULLIF(sa.gross_regular_revenue_30d, 0)) * 100 AS markdown_rate_30d, - (sa.sales_30d / NULLIF(ci.current_stock + sa.sales_30d, 0)) * 100 AS sell_through_30d, + -- Fix sell-through rate: Industry standard is Units Sold / (Beginning Inventory + Units Received) + -- Approximating beginning inventory as current stock + units sold - units received + (sa.sales_30d / NULLIF( + ci.current_stock + sa.sales_30d + sa.returns_units_30d - sa.received_qty_30d, + 0 + )) * 100 AS sell_through_30d, -- Forecasting intermediate values - -- CRITICAL FIX: Use safer velocity calculation to prevent extreme values - -- Original problematic calculation: (sa.sales_30d / NULLIF(30.0 - sa.stockout_days_30d, 0)) - -- Use available days (not stockout days) as denominator with a minimum safety value - (sa.sales_30d / - NULLIF( - GREATEST( - 30.0 - sa.stockout_days_30d, -- Standard calculation - CASE - WHEN sa.sales_30d > 0 THEN 14.0 -- If we have sales, ensure at least 14 days denominator - ELSE 30.0 -- If no sales, use full period - END - ), - 0 - ) - ) AS sales_velocity_daily, + -- Use the calculate_sales_velocity function instead of repetitive calculation + calculate_sales_velocity(sa.sales_30d::int, sa.stockout_days_30d::int) AS sales_velocity_daily, s.effective_lead_time AS config_lead_time, s.effective_days_of_stock AS config_days_of_stock, s.effective_safety_stock AS config_safety_stock, (s.effective_lead_time + s.effective_days_of_stock) AS planning_period_days, - -- Apply the same fix to all derived calculations - (sa.sales_30d / - NULLIF( - GREATEST( - 30.0 - sa.stockout_days_30d, - CASE WHEN sa.sales_30d > 0 THEN 14.0 ELSE 30.0 END - ), - 0 - ) - ) * s.effective_lead_time AS lead_time_forecast_units, + calculate_sales_velocity(sa.sales_30d::int, sa.stockout_days_30d::int) * s.effective_lead_time AS lead_time_forecast_units, - (sa.sales_30d / - NULLIF( - GREATEST( - 30.0 - sa.stockout_days_30d, - CASE WHEN sa.sales_30d > 0 THEN 14.0 ELSE 30.0 END - ), - 0 - ) - ) * s.effective_days_of_stock AS days_of_stock_forecast_units, + calculate_sales_velocity(sa.sales_30d::int, sa.stockout_days_30d::int) * s.effective_days_of_stock AS days_of_stock_forecast_units, - (sa.sales_30d / - NULLIF( - GREATEST( - 30.0 - sa.stockout_days_30d, - CASE WHEN sa.sales_30d > 0 THEN 14.0 ELSE 30.0 END - ), - 0 - ) - ) * (s.effective_lead_time + s.effective_days_of_stock) AS planning_period_forecast_units, + calculate_sales_velocity(sa.sales_30d::int, sa.stockout_days_30d::int) * (s.effective_lead_time + s.effective_days_of_stock) AS planning_period_forecast_units, - (ci.current_stock + COALESCE(ooi.on_order_qty, 0) - ((sa.sales_30d / - NULLIF( - GREATEST( - 30.0 - sa.stockout_days_30d, - CASE WHEN sa.sales_30d > 0 THEN 14.0 ELSE 30.0 END - ), - 0 - ) - ) * s.effective_lead_time)) AS lead_time_closing_stock, + (ci.current_stock + COALESCE(ooi.on_order_qty, 0) - (calculate_sales_velocity(sa.sales_30d::int, sa.stockout_days_30d::int) * s.effective_lead_time)) AS lead_time_closing_stock, - ((ci.current_stock + COALESCE(ooi.on_order_qty, 0) - ((sa.sales_30d / - NULLIF( - GREATEST( - 30.0 - sa.stockout_days_30d, - CASE WHEN sa.sales_30d > 0 THEN 14.0 ELSE 30.0 END - ), - 0 - ) - ) * s.effective_lead_time))) - ((sa.sales_30d / - NULLIF( - GREATEST( - 30.0 - sa.stockout_days_30d, - CASE WHEN sa.sales_30d > 0 THEN 14.0 ELSE 30.0 END - ), - 0 - ) - ) * s.effective_days_of_stock) AS days_of_stock_closing_stock, + ((ci.current_stock + COALESCE(ooi.on_order_qty, 0) - (calculate_sales_velocity(sa.sales_30d::int, sa.stockout_days_30d::int) * s.effective_lead_time))) - (calculate_sales_velocity(sa.sales_30d::int, sa.stockout_days_30d::int) * s.effective_days_of_stock) AS days_of_stock_closing_stock, - (((sa.sales_30d / - NULLIF( - GREATEST( - 30.0 - sa.stockout_days_30d, - CASE WHEN sa.sales_30d > 0 THEN 14.0 ELSE 30.0 END - ), - 0 - ) - ) * s.effective_lead_time) + ((sa.sales_30d / - NULLIF( - GREATEST( - 30.0 - sa.stockout_days_30d, - CASE WHEN sa.sales_30d > 0 THEN 14.0 ELSE 30.0 END - ), - 0 - ) - ) * s.effective_days_of_stock)) + s.effective_safety_stock - ci.current_stock - COALESCE(ooi.on_order_qty, 0) AS replenishment_needed_raw, + ((calculate_sales_velocity(sa.sales_30d::int, sa.stockout_days_30d::int) * s.effective_lead_time) + (calculate_sales_velocity(sa.sales_30d::int, sa.stockout_days_30d::int) * s.effective_days_of_stock)) + s.effective_safety_stock - ci.current_stock - COALESCE(ooi.on_order_qty, 0) AS replenishment_needed_raw, - -- Final Forecasting / Replenishment Metrics (apply CEILING/GREATEST/etc.) - -- Note: These calculations are nested for clarity, can be simplified in prod - CEILING(GREATEST(0, ((((sa.sales_30d / - NULLIF( - GREATEST( - 30.0 - sa.stockout_days_30d, - CASE WHEN sa.sales_30d > 0 THEN 14.0 ELSE 30.0 END - ), - 0 - ) - ) * s.effective_lead_time) + ((sa.sales_30d / - NULLIF( - GREATEST( - 30.0 - sa.stockout_days_30d, - CASE WHEN sa.sales_30d > 0 THEN 14.0 ELSE 30.0 END - ), - 0 - ) - ) * s.effective_days_of_stock)) + s.effective_safety_stock - ci.current_stock - COALESCE(ooi.on_order_qty, 0))))::int AS replenishment_units, - (CEILING(GREATEST(0, ((((sa.sales_30d / - NULLIF( - GREATEST( - 30.0 - sa.stockout_days_30d, - CASE WHEN sa.sales_30d > 0 THEN 14.0 ELSE 30.0 END - ), - 0 - ) - ) * s.effective_lead_time) + ((sa.sales_30d / - NULLIF( - GREATEST( - 30.0 - sa.stockout_days_30d, - CASE WHEN sa.sales_30d > 0 THEN 14.0 ELSE 30.0 END - ), - 0 - ) - ) * s.effective_days_of_stock)) + s.effective_safety_stock - ci.current_stock - COALESCE(ooi.on_order_qty, 0))))::int) * ci.current_effective_cost AS replenishment_cost, - (CEILING(GREATEST(0, ((((sa.sales_30d / - NULLIF( - GREATEST( - 30.0 - sa.stockout_days_30d, - CASE WHEN sa.sales_30d > 0 THEN 14.0 ELSE 30.0 END - ), - 0 - ) - ) * s.effective_lead_time) + ((sa.sales_30d / - NULLIF( - GREATEST( - 30.0 - sa.stockout_days_30d, - CASE WHEN sa.sales_30d > 0 THEN 14.0 ELSE 30.0 END - ), - 0 - ) - ) * s.effective_days_of_stock)) + s.effective_safety_stock - ci.current_stock - COALESCE(ooi.on_order_qty, 0))))::int) * ci.current_price AS replenishment_retail, - (CEILING(GREATEST(0, ((((sa.sales_30d / - NULLIF( - GREATEST( - 30.0 - sa.stockout_days_30d, - CASE WHEN sa.sales_30d > 0 THEN 14.0 ELSE 30.0 END - ), - 0 - ) - ) * s.effective_lead_time) + ((sa.sales_30d / - NULLIF( - GREATEST( - 30.0 - sa.stockout_days_30d, - CASE WHEN sa.sales_30d > 0 THEN 14.0 ELSE 30.0 END - ), - 0 - ) - ) * s.effective_days_of_stock)) + s.effective_safety_stock - ci.current_stock - COALESCE(ooi.on_order_qty, 0))))::int) * (ci.current_price - ci.current_effective_cost) AS replenishment_profit, + -- Final Forecasting / Replenishment Metrics + CEILING(GREATEST(0, (((calculate_sales_velocity(sa.sales_30d::int, sa.stockout_days_30d::int) * s.effective_lead_time) + (calculate_sales_velocity(sa.sales_30d::int, sa.stockout_days_30d::int) * s.effective_days_of_stock)) + s.effective_safety_stock - ci.current_stock - COALESCE(ooi.on_order_qty, 0))))::int AS replenishment_units, + (CEILING(GREATEST(0, (((calculate_sales_velocity(sa.sales_30d::int, sa.stockout_days_30d::int) * s.effective_lead_time) + (calculate_sales_velocity(sa.sales_30d::int, sa.stockout_days_30d::int) * s.effective_days_of_stock)) + s.effective_safety_stock - ci.current_stock - COALESCE(ooi.on_order_qty, 0))))::int) * ci.current_effective_cost AS replenishment_cost, + (CEILING(GREATEST(0, (((calculate_sales_velocity(sa.sales_30d::int, sa.stockout_days_30d::int) * s.effective_lead_time) + (calculate_sales_velocity(sa.sales_30d::int, sa.stockout_days_30d::int) * s.effective_days_of_stock)) + s.effective_safety_stock - ci.current_stock - COALESCE(ooi.on_order_qty, 0))))::int) * ci.current_price AS replenishment_retail, + (CEILING(GREATEST(0, (((calculate_sales_velocity(sa.sales_30d::int, sa.stockout_days_30d::int) * s.effective_lead_time) + (calculate_sales_velocity(sa.sales_30d::int, sa.stockout_days_30d::int) * s.effective_days_of_stock)) + s.effective_safety_stock - ci.current_stock - COALESCE(ooi.on_order_qty, 0))))::int) * (ci.current_price - ci.current_effective_cost) AS replenishment_profit, - -- Placeholder for To Order (Apply MOQ/UOM logic here if needed, otherwise equals replenishment) - CEILING(GREATEST(0, ((((sa.sales_30d / - NULLIF( - GREATEST( - 30.0 - sa.stockout_days_30d, - CASE WHEN sa.sales_30d > 0 THEN 14.0 ELSE 30.0 END - ), - 0 - ) - ) * s.effective_lead_time) + ((sa.sales_30d / - NULLIF( - GREATEST( - 30.0 - sa.stockout_days_30d, - CASE WHEN sa.sales_30d > 0 THEN 14.0 ELSE 30.0 END - ), - 0 - ) - ) * s.effective_days_of_stock)) + s.effective_safety_stock - ci.current_stock - COALESCE(ooi.on_order_qty, 0))))::int AS to_order_units, + -- To Order (Apply MOQ/UOM logic here if needed, otherwise equals replenishment) + CEILING(GREATEST(0, (((calculate_sales_velocity(sa.sales_30d::int, sa.stockout_days_30d::int) * s.effective_lead_time) + (calculate_sales_velocity(sa.sales_30d::int, sa.stockout_days_30d::int) * s.effective_days_of_stock)) + s.effective_safety_stock - ci.current_stock - COALESCE(ooi.on_order_qty, 0))))::int AS to_order_units, - GREATEST(0, - (ci.current_stock + COALESCE(ooi.on_order_qty, 0) - ((sa.sales_30d / - NULLIF( - GREATEST( - 30.0 - sa.stockout_days_30d, - CASE WHEN sa.sales_30d > 0 THEN 14.0 ELSE 30.0 END - ), - 0 - ) - ) * s.effective_lead_time))) AS forecast_lost_sales_units, - GREATEST(0, - (ci.current_stock + COALESCE(ooi.on_order_qty, 0) - ((sa.sales_30d / - NULLIF( - GREATEST( - 30.0 - sa.stockout_days_30d, - CASE WHEN sa.sales_30d > 0 THEN 14.0 ELSE 30.0 END - ), - 0 - ) - ) * s.effective_lead_time))) * ci.current_price AS forecast_lost_revenue, + GREATEST(0, - (ci.current_stock + COALESCE(ooi.on_order_qty, 0) - (calculate_sales_velocity(sa.sales_30d::int, sa.stockout_days_30d::int) * s.effective_lead_time))) AS forecast_lost_sales_units, + GREATEST(0, - (ci.current_stock + COALESCE(ooi.on_order_qty, 0) - (calculate_sales_velocity(sa.sales_30d::int, sa.stockout_days_30d::int) * s.effective_lead_time))) * ci.current_price AS forecast_lost_revenue, - ci.current_stock / NULLIF((sa.sales_30d / - NULLIF( - GREATEST( - 30.0 - sa.stockout_days_30d, - CASE WHEN sa.sales_30d > 0 THEN 14.0 ELSE 30.0 END - ), - 0 - ) - ), 0) AS stock_cover_in_days, - COALESCE(ooi.on_order_qty, 0) / NULLIF((sa.sales_30d / - NULLIF( - GREATEST( - 30.0 - sa.stockout_days_30d, - CASE WHEN sa.sales_30d > 0 THEN 14.0 ELSE 30.0 END - ), - 0 - ) - ), 0) AS po_cover_in_days, - (ci.current_stock + COALESCE(ooi.on_order_qty, 0)) / NULLIF((sa.sales_30d / - NULLIF( - GREATEST( - 30.0 - sa.stockout_days_30d, - CASE WHEN sa.sales_30d > 0 THEN 14.0 ELSE 30.0 END - ), - 0 - ) - ), 0) AS sells_out_in_days, + ci.current_stock / NULLIF(calculate_sales_velocity(sa.sales_30d::int, sa.stockout_days_30d::int), 0) AS stock_cover_in_days, + COALESCE(ooi.on_order_qty, 0) / NULLIF(calculate_sales_velocity(sa.sales_30d::int, sa.stockout_days_30d::int), 0) AS po_cover_in_days, + (ci.current_stock + COALESCE(ooi.on_order_qty, 0)) / NULLIF(calculate_sales_velocity(sa.sales_30d::int, sa.stockout_days_30d::int), 0) AS sells_out_in_days, -- Replenish Date: Date when stock is projected to hit safety stock, minus lead time CASE - WHEN (sa.sales_30d / - NULLIF( - GREATEST( - 30.0 - sa.stockout_days_30d, - CASE WHEN sa.sales_30d > 0 THEN 14.0 ELSE 30.0 END - ), - 0 - ) - ) > 0 - THEN _current_date + FLOOR(GREATEST(0, ci.current_stock - s.effective_safety_stock) / (sa.sales_30d / - NULLIF( - GREATEST( - 30.0 - sa.stockout_days_30d, - CASE WHEN sa.sales_30d > 0 THEN 14.0 ELSE 30.0 END - ), - 0 - ) - ))::int - s.effective_lead_time + WHEN calculate_sales_velocity(sa.sales_30d::int, sa.stockout_days_30d::int) > 0 + THEN _current_date + FLOOR(GREATEST(0, ci.current_stock - s.effective_safety_stock) / calculate_sales_velocity(sa.sales_30d::int, sa.stockout_days_30d::int))::int - s.effective_lead_time ELSE NULL END AS replenish_date, - GREATEST(0, ci.current_stock - s.effective_safety_stock - (((sa.sales_30d / - NULLIF( - GREATEST( - 30.0 - sa.stockout_days_30d, - CASE WHEN sa.sales_30d > 0 THEN 14.0 ELSE 30.0 END - ), - 0 - ) - ) * s.effective_lead_time) + ((sa.sales_30d / - NULLIF( - GREATEST( - 30.0 - sa.stockout_days_30d, - CASE WHEN sa.sales_30d > 0 THEN 14.0 ELSE 30.0 END - ), - 0 - ) - ) * s.effective_days_of_stock)))::int AS overstocked_units, - (GREATEST(0, ci.current_stock - s.effective_safety_stock - (((sa.sales_30d / - NULLIF( - GREATEST( - 30.0 - sa.stockout_days_30d, - CASE WHEN sa.sales_30d > 0 THEN 14.0 ELSE 30.0 END - ), - 0 - ) - ) * s.effective_lead_time) + ((sa.sales_30d / - NULLIF( - GREATEST( - 30.0 - sa.stockout_days_30d, - CASE WHEN sa.sales_30d > 0 THEN 14.0 ELSE 30.0 END - ), - 0 - ) - ) * s.effective_days_of_stock)))) * ci.current_effective_cost AS overstocked_cost, - (GREATEST(0, ci.current_stock - s.effective_safety_stock - (((sa.sales_30d / - NULLIF( - GREATEST( - 30.0 - sa.stockout_days_30d, - CASE WHEN sa.sales_30d > 0 THEN 14.0 ELSE 30.0 END - ), - 0 - ) - ) * s.effective_lead_time) + ((sa.sales_30d / - NULLIF( - GREATEST( - 30.0 - sa.stockout_days_30d, - CASE WHEN sa.sales_30d > 0 THEN 14.0 ELSE 30.0 END - ), - 0 - ) - ) * s.effective_days_of_stock)))) * ci.current_price AS overstocked_retail, + GREATEST(0, ci.current_stock - s.effective_safety_stock - ((calculate_sales_velocity(sa.sales_30d::int, sa.stockout_days_30d::int) * s.effective_lead_time) + (calculate_sales_velocity(sa.sales_30d::int, sa.stockout_days_30d::int) * s.effective_days_of_stock)))::int AS overstocked_units, + (GREATEST(0, ci.current_stock - s.effective_safety_stock - ((calculate_sales_velocity(sa.sales_30d::int, sa.stockout_days_30d::int) * s.effective_lead_time) + (calculate_sales_velocity(sa.sales_30d::int, sa.stockout_days_30d::int) * s.effective_days_of_stock)))) * ci.current_effective_cost AS overstocked_cost, + (GREATEST(0, ci.current_stock - s.effective_safety_stock - ((calculate_sales_velocity(sa.sales_30d::int, sa.stockout_days_30d::int) * s.effective_lead_time) + (calculate_sales_velocity(sa.sales_30d::int, sa.stockout_days_30d::int) * s.effective_days_of_stock)))) * ci.current_price AS overstocked_retail, -- Old Stock Flag (ci.created_at::date < _current_date - INTERVAL '60 day') AND @@ -592,66 +425,18 @@ BEGIN ELSE CASE -- Check for overstock first - WHEN GREATEST(0, ci.current_stock - s.effective_safety_stock - (((sa.sales_30d / - NULLIF( - GREATEST( - 30.0 - sa.stockout_days_30d, - CASE WHEN sa.sales_30d > 0 THEN 14.0 ELSE 30.0 END - ), - 0 - ) - ) * s.effective_lead_time) + ((sa.sales_30d / - NULLIF( - GREATEST( - 30.0 - sa.stockout_days_30d, - CASE WHEN sa.sales_30d > 0 THEN 14.0 ELSE 30.0 END - ), - 0 - ) - ) * s.effective_days_of_stock))) > 0 THEN 'Overstock' + WHEN GREATEST(0, ci.current_stock - s.effective_safety_stock - ((calculate_sales_velocity(sa.sales_30d::int, sa.stockout_days_30d::int) * s.effective_lead_time) + (calculate_sales_velocity(sa.sales_30d::int, sa.stockout_days_30d::int) * s.effective_days_of_stock))) > 0 THEN 'Overstock' -- Check for Critical stock WHEN ci.current_stock <= 0 OR - (ci.current_stock / NULLIF((sa.sales_30d / - NULLIF( - GREATEST( - 30.0 - sa.stockout_days_30d, - CASE WHEN sa.sales_30d > 0 THEN 14.0 ELSE 30.0 END - ), - 0 - ) - ), 0)) <= 0 THEN 'Critical' + (ci.current_stock / NULLIF(calculate_sales_velocity(sa.sales_30d::int, sa.stockout_days_30d::int), 0)) <= 0 THEN 'Critical' - WHEN (ci.current_stock / NULLIF((sa.sales_30d / - NULLIF( - GREATEST( - 30.0 - sa.stockout_days_30d, - CASE WHEN sa.sales_30d > 0 THEN 14.0 ELSE 30.0 END - ), - 0 - ) - ), 0)) < (COALESCE(s.effective_lead_time, 30) * 0.5) THEN 'Critical' + WHEN (ci.current_stock / NULLIF(calculate_sales_velocity(sa.sales_30d::int, sa.stockout_days_30d::int), 0)) < (COALESCE(s.effective_lead_time, 30) * 0.5) THEN 'Critical' -- Check for reorder soon - WHEN ((ci.current_stock + COALESCE(ooi.on_order_qty, 0)) / NULLIF((sa.sales_30d / - NULLIF( - GREATEST( - 30.0 - sa.stockout_days_30d, - CASE WHEN sa.sales_30d > 0 THEN 14.0 ELSE 30.0 END - ), - 0 - ) - ), 0)) < (COALESCE(s.effective_lead_time, 30) + 7) THEN + WHEN ((ci.current_stock + COALESCE(ooi.on_order_qty, 0)) / NULLIF(calculate_sales_velocity(sa.sales_30d::int, sa.stockout_days_30d::int), 0)) < (COALESCE(s.effective_lead_time, 30) + 7) THEN CASE - WHEN (ci.current_stock / NULLIF((sa.sales_30d / - NULLIF( - GREATEST( - 30.0 - sa.stockout_days_30d, - CASE WHEN sa.sales_30d > 0 THEN 14.0 ELSE 30.0 END - ), - 0 - ) - ), 0)) < (COALESCE(s.effective_lead_time, 30) * 0.5) THEN 'Critical' + WHEN (ci.current_stock / NULLIF(calculate_sales_velocity(sa.sales_30d::int, sa.stockout_days_30d::int), 0)) < (COALESCE(s.effective_lead_time, 30) * 0.5) THEN 'Critical' ELSE 'Reorder Soon' END @@ -672,15 +457,7 @@ BEGIN END) > 180 THEN 'At Risk' -- Very high stock cover is at risk too - WHEN (ci.current_stock / NULLIF((sa.sales_30d / - NULLIF( - GREATEST( - 30.0 - sa.stockout_days_30d, - CASE WHEN sa.sales_30d > 0 THEN 14.0 ELSE 30.0 END - ), - 0 - ) - ), 0)) > 365 THEN 'At Risk' + WHEN (ci.current_stock / NULLIF(calculate_sales_velocity(sa.sales_30d::int, sa.stockout_days_30d::int), 0)) > 365 THEN 'At Risk' -- New products (less than 30 days old) WHEN (CASE @@ -693,7 +470,30 @@ BEGIN -- If none of the above, assume Healthy ELSE 'Healthy' END - END AS status + END AS status, + + -- Growth Metrics (P3) - using safe_divide and std_numeric for consistency + std_numeric(safe_divide((sa.sales_30d - ppm.sales_prev_30d) * 100.0, ppm.sales_prev_30d), 2) AS sales_growth_30d_vs_prev, + std_numeric(safe_divide((sa.revenue_30d - ppm.revenue_prev_30d) * 100.0, ppm.revenue_prev_30d), 2) AS revenue_growth_30d_vs_prev, + std_numeric(safe_divide((sa.sales_30d - ppm.sales_30d_last_year) * 100.0, ppm.sales_30d_last_year), 2) AS sales_growth_yoy, + std_numeric(safe_divide((sa.revenue_30d - ppm.revenue_30d_last_year) * 100.0, ppm.revenue_30d_last_year), 2) AS revenue_growth_yoy, + + -- Demand Variability (P3) + std_numeric(dv.sales_variance, 2) AS sales_variance_30d, + std_numeric(dv.sales_std_dev, 2) AS sales_std_dev_30d, + std_numeric(dv.sales_cv, 2) AS sales_cv_30d, + classify_demand_pattern(dv.avg_daily_sales, dv.sales_cv) AS demand_pattern, + + -- Service Levels (P5) + std_numeric(COALESCE(sl.fill_rate_30d, 100), 2) AS fill_rate_30d, + COALESCE(sl.stockout_incidents_30d, 0)::int AS stockout_incidents_30d, + std_numeric(COALESCE(sl.service_level_30d, 100), 2) AS service_level_30d, + COALESCE(sl.lost_sales_incidents_30d, 0)::int AS lost_sales_incidents_30d, + + -- Seasonality (P5) + std_numeric(season.seasonality_index, 2) AS seasonality_index, + COALESCE(season.seasonal_pattern, 'none') AS seasonal_pattern, + season.peak_season FROM CurrentInfo ci LEFT JOIN OnOrderInfo ooi ON ci.pid = ooi.pid @@ -701,6 +501,11 @@ BEGIN LEFT JOIN SnapshotAggregates sa ON ci.pid = sa.pid LEFT JOIN FirstPeriodMetrics fpm ON ci.pid = fpm.pid LEFT JOIN Settings s ON ci.pid = s.pid + LEFT JOIN LifetimeRevenue lr ON ci.pid = lr.pid + LEFT JOIN PreviousPeriodMetrics ppm ON ci.pid = ppm.pid + LEFT JOIN DemandVariability dv ON ci.pid = dv.pid + LEFT JOIN ServiceLevels sl ON ci.pid = sl.pid + LEFT JOIN SeasonalityAnalysis season ON ci.pid = season.pid WHERE s.exclude_forecast IS FALSE OR s.exclude_forecast IS NULL -- Exclude products explicitly marked ON CONFLICT (pid) DO UPDATE SET @@ -718,7 +523,7 @@ BEGIN stockout_days_30d = EXCLUDED.stockout_days_30d, sales_365d = EXCLUDED.sales_365d, revenue_365d = EXCLUDED.revenue_365d, avg_stock_units_30d = EXCLUDED.avg_stock_units_30d, avg_stock_cost_30d = EXCLUDED.avg_stock_cost_30d, avg_stock_retail_30d = EXCLUDED.avg_stock_retail_30d, avg_stock_gross_30d = EXCLUDED.avg_stock_gross_30d, received_qty_30d = EXCLUDED.received_qty_30d, received_cost_30d = EXCLUDED.received_cost_30d, - lifetime_sales = EXCLUDED.lifetime_sales, lifetime_revenue = EXCLUDED.lifetime_revenue, + lifetime_sales = EXCLUDED.lifetime_sales, lifetime_revenue = EXCLUDED.lifetime_revenue, lifetime_revenue_quality = EXCLUDED.lifetime_revenue_quality, first_7_days_sales = EXCLUDED.first_7_days_sales, first_7_days_revenue = EXCLUDED.first_7_days_revenue, first_30_days_sales = EXCLUDED.first_30_days_sales, first_30_days_revenue = EXCLUDED.first_30_days_revenue, first_60_days_sales = EXCLUDED.first_60_days_sales, first_60_days_revenue = EXCLUDED.first_60_days_revenue, first_90_days_sales = EXCLUDED.first_90_days_sales, first_90_days_revenue = EXCLUDED.first_90_days_revenue, asp_30d = EXCLUDED.asp_30d, acp_30d = EXCLUDED.acp_30d, avg_ros_30d = EXCLUDED.avg_ros_30d, avg_sales_per_day_30d = EXCLUDED.avg_sales_per_day_30d, avg_sales_per_month_30d = EXCLUDED.avg_sales_per_month_30d, @@ -734,7 +539,22 @@ BEGIN stock_cover_in_days = EXCLUDED.stock_cover_in_days, po_cover_in_days = EXCLUDED.po_cover_in_days, sells_out_in_days = EXCLUDED.sells_out_in_days, replenish_date = EXCLUDED.replenish_date, overstocked_units = EXCLUDED.overstocked_units, overstocked_cost = EXCLUDED.overstocked_cost, overstocked_retail = EXCLUDED.overstocked_retail, is_old_stock = EXCLUDED.is_old_stock, yesterday_sales = EXCLUDED.yesterday_sales, - status = EXCLUDED.status + status = EXCLUDED.status, + sales_growth_30d_vs_prev = EXCLUDED.sales_growth_30d_vs_prev, + revenue_growth_30d_vs_prev = EXCLUDED.revenue_growth_30d_vs_prev, + sales_growth_yoy = EXCLUDED.sales_growth_yoy, + revenue_growth_yoy = EXCLUDED.revenue_growth_yoy, + sales_variance_30d = EXCLUDED.sales_variance_30d, + sales_std_dev_30d = EXCLUDED.sales_std_dev_30d, + sales_cv_30d = EXCLUDED.sales_cv_30d, + demand_pattern = EXCLUDED.demand_pattern, + fill_rate_30d = EXCLUDED.fill_rate_30d, + stockout_incidents_30d = EXCLUDED.stockout_incidents_30d, + service_level_30d = EXCLUDED.service_level_30d, + lost_sales_incidents_30d = EXCLUDED.lost_sales_incidents_30d, + seasonality_index = EXCLUDED.seasonality_index, + seasonal_pattern = EXCLUDED.seasonal_pattern, + peak_season = EXCLUDED.peak_season WHERE -- Only update if at least one key metric has changed product_metrics.current_stock IS DISTINCT FROM EXCLUDED.current_stock OR product_metrics.current_price IS DISTINCT FROM EXCLUDED.current_price OR @@ -750,7 +570,8 @@ BEGIN -- Check a few other important fields that might change product_metrics.date_last_sold IS DISTINCT FROM EXCLUDED.date_last_sold OR product_metrics.earliest_expected_date IS DISTINCT FROM EXCLUDED.earliest_expected_date OR - product_metrics.lifetime_sales IS DISTINCT FROM EXCLUDED.lifetime_sales + product_metrics.lifetime_sales IS DISTINCT FROM EXCLUDED.lifetime_sales OR + product_metrics.lifetime_revenue_quality IS DISTINCT FROM EXCLUDED.lifetime_revenue_quality ; -- Update the status table with the timestamp from the START of this run diff --git a/inventory-server/src/routes/analytics.js b/inventory-server/src/routes/analytics.js index 375e488..5ef7faf 100644 --- a/inventory-server/src/routes/analytics.js +++ b/inventory-server/src/routes/analytics.js @@ -203,12 +203,8 @@ router.get('/vendors', async (req, res) => { 0 ) as stock_turnover, product_count, - -- Use an estimate of growth based on 7-day vs 30-day revenue - CASE - WHEN revenue_30d > 0 - THEN ((revenue_7d * 4.0) / revenue_30d - 1) * 100 - ELSE 0 - END as growth + -- Use actual growth metrics from the vendor_metrics table + sales_growth_30d_vs_prev as growth FROM vendor_metrics WHERE revenue_30d > 0 ORDER BY revenue_30d DESC diff --git a/inventory-server/src/routes/brandsAggregate.js b/inventory-server/src/routes/brandsAggregate.js index 24d85bf..587e730 100644 --- a/inventory-server/src/routes/brandsAggregate.js +++ b/inventory-server/src/routes/brandsAggregate.js @@ -26,6 +26,9 @@ const COLUMN_MAP = { lifetimeSales: { dbCol: 'bm.lifetime_sales', type: 'number' }, lifetimeRevenue: { dbCol: 'bm.lifetime_revenue', type: 'number' }, avgMargin30d: { dbCol: 'bm.avg_margin_30d', type: 'number' }, + // Growth metrics + salesGrowth30dVsPrev: { dbCol: 'bm.sales_growth_30d_vs_prev', type: 'number' }, + revenueGrowth30dVsPrev: { dbCol: 'bm.revenue_growth_30d_vs_prev', type: 'number' }, // Add aliases if needed name: { dbCol: 'bm.brand_name', type: 'string' }, // Add status for filtering diff --git a/inventory-server/src/routes/categoriesAggregate.js b/inventory-server/src/routes/categoriesAggregate.js index 455f950..7a9f0da 100644 --- a/inventory-server/src/routes/categoriesAggregate.js +++ b/inventory-server/src/routes/categoriesAggregate.js @@ -31,6 +31,9 @@ const COLUMN_MAP = { lifetimeRevenue: { dbCol: 'cm.lifetime_revenue', type: 'number' }, avgMargin30d: { dbCol: 'cm.avg_margin_30d', type: 'number' }, stockTurn30d: { dbCol: 'cm.stock_turn_30d', type: 'number' }, + // Growth metrics + salesGrowth30dVsPrev: { dbCol: 'cm.sales_growth_30d_vs_prev', type: 'number' }, + revenueGrowth30dVsPrev: { dbCol: 'cm.revenue_growth_30d_vs_prev', type: 'number' }, // Add status from the categories table for filtering status: { dbCol: 'c.status', type: 'string' }, }; diff --git a/inventory-server/src/routes/metrics.js b/inventory-server/src/routes/metrics.js index 27c2b71..01924fa 100644 --- a/inventory-server/src/routes/metrics.js +++ b/inventory-server/src/routes/metrics.js @@ -143,7 +143,33 @@ const COLUMN_MAP = { // Yesterday yesterdaySales: 'pm.yesterday_sales', // Map status column - directly mapped now instead of calculated on frontend - status: 'pm.status' + status: 'pm.status', + + // Growth Metrics (P3) + salesGrowth30dVsPrev: 'pm.sales_growth_30d_vs_prev', + revenueGrowth30dVsPrev: 'pm.revenue_growth_30d_vs_prev', + salesGrowthYoy: 'pm.sales_growth_yoy', + revenueGrowthYoy: 'pm.revenue_growth_yoy', + + // Demand Variability Metrics (P3) + salesVariance30d: 'pm.sales_variance_30d', + salesStdDev30d: 'pm.sales_std_dev_30d', + salesCv30d: 'pm.sales_cv_30d', + demandPattern: 'pm.demand_pattern', + + // Service Level Metrics (P5) + fillRate30d: 'pm.fill_rate_30d', + stockoutIncidents30d: 'pm.stockout_incidents_30d', + serviceLevel30d: 'pm.service_level_30d', + lostSalesIncidents30d: 'pm.lost_sales_incidents_30d', + + // Seasonality Metrics (P5) + seasonalityIndex: 'pm.seasonality_index', + seasonalPattern: 'pm.seasonal_pattern', + peakSeason: 'pm.peak_season', + + // Lifetime Revenue Quality + lifetimeRevenueQuality: 'pm.lifetime_revenue_quality' }; // Define column types for use in sorting/filtering @@ -173,7 +199,15 @@ const COLUMN_TYPES = { 'overstockedCost', 'overstockedRetail', 'yesterdaySales', // New numeric columns 'moq', 'rating', 'reviews', 'weight', 'length', 'width', 'height', - 'baskets', 'notifies', 'preorderCount', 'notionsInvCount' + 'baskets', 'notifies', 'preorderCount', 'notionsInvCount', + // Growth metrics + 'salesGrowth30dVsPrev', 'revenueGrowth30dVsPrev', 'salesGrowthYoy', 'revenueGrowthYoy', + // Demand variability metrics + 'salesVariance30d', 'salesStdDev30d', 'salesCv30d', + // Service level metrics + 'fillRate30d', 'stockoutIncidents30d', 'serviceLevel30d', 'lostSalesIncidents30d', + // Seasonality metrics + 'seasonalityIndex' ], // Date columns (use date operators and sorting) date: [ @@ -185,7 +219,9 @@ const COLUMN_TYPES = { 'sku', 'title', 'brand', 'vendor', 'imageUrl', 'abcClass', 'status', // New string columns 'barcode', 'harmonizedTariffCode', 'vendorReference', 'notionsReference', - 'line', 'subline', 'artist', 'countryOfOrigin', 'location' + 'line', 'subline', 'artist', 'countryOfOrigin', 'location', + // New string columns for patterns + 'demandPattern', 'seasonalPattern', 'peakSeason', 'lifetimeRevenueQuality' ], // Boolean columns (use boolean operators and sorting) boolean: ['isVisible', 'isReplenishable', 'isOldStock'] @@ -208,6 +244,12 @@ const SPECIAL_SORT_COLUMNS = { // Velocity columns salesVelocityDaily: true, + // Growth rate columns + salesGrowth30dVsPrev: 'abs', + revenueGrowth30dVsPrev: 'abs', + salesGrowthYoy: 'abs', + revenueGrowthYoy: 'abs', + // Status column needs special ordering status: 'priority' }; diff --git a/inventory-server/src/routes/vendorsAggregate.js b/inventory-server/src/routes/vendorsAggregate.js index f4e3ed9..7e9b11b 100644 --- a/inventory-server/src/routes/vendorsAggregate.js +++ b/inventory-server/src/routes/vendorsAggregate.js @@ -30,6 +30,9 @@ const COLUMN_MAP = { lifetimeSales: { dbCol: 'vm.lifetime_sales', type: 'number' }, lifetimeRevenue: { dbCol: 'vm.lifetime_revenue', type: 'number' }, avgMargin30d: { dbCol: 'vm.avg_margin_30d', type: 'number' }, + // Growth metrics + salesGrowth30dVsPrev: { dbCol: 'vm.sales_growth_30d_vs_prev', type: 'number' }, + revenueGrowth30dVsPrev: { dbCol: 'vm.revenue_growth_30d_vs_prev', type: 'number' }, // Add aliases if needed for frontend compatibility name: { dbCol: 'vm.vendor_name', type: 'string' }, leadTime: { dbCol: 'vm.avg_lead_time_days', type: 'number' }, diff --git a/inventory/src/pages/Brands.tsx b/inventory/src/pages/Brands.tsx index d6233a1..d892dcb 100644 --- a/inventory/src/pages/Brands.tsx +++ b/inventory/src/pages/Brands.tsx @@ -16,7 +16,8 @@ import { Badge } from "@/components/ui/badge"; type BrandSortableColumns = | 'brandName' | 'productCount' | 'activeProductCount' | 'currentStockUnits' | 'currentStockCost' | 'currentStockRetail' | 'revenue_7d' | 'revenue_30d' - | 'profit_30d' | 'sales_30d' | 'avg_margin_30d' | 'stock_turn_30d' | 'status'; // Add more as needed + | 'profit_30d' | 'sales_30d' | 'avg_margin_30d' | 'stock_turn_30d' + | 'salesGrowth30dVsPrev' | 'revenueGrowth30dVsPrev' | 'status'; interface BrandMetric { brand_id: string | number; @@ -40,6 +41,9 @@ interface BrandMetric { lifetime_revenue: string | number; avg_margin_30d: string | number | null; stock_turn_30d: string | number | null; + // Growth metrics + sales_growth_30d_vs_prev: string | number | null; + revenue_growth_30d_vs_prev: string | number | null; status: string; brand_status: string; description: string; @@ -57,6 +61,8 @@ interface BrandMetric { lifetimeRevenue: string | number; avgMargin_30d: string | number | null; stockTurn_30d: string | number | null; + salesGrowth30dVsPrev: string | number | null; + revenueGrowth30dVsPrev: string | number | null; } // Define response type to avoid type errors @@ -140,6 +146,19 @@ const formatPercentage = (value: number | string | null | undefined, digits = 1) return `${value.toFixed(digits)}%`; }; +// Growth formatting with color coding +const formatGrowth = (value: number | string | null | undefined, digits = 1) => { + if (value == null) return N/A; + + const numValue = typeof value === "string" ? parseFloat(value) : value; + if (isNaN(numValue)) return N/A; + + const formatted = `${numValue >= 0 ? '+' : ''}${numValue.toFixed(digits)}%`; + const colorClass = numValue >= 0 ? 'text-green-600' : 'text-red-600'; + + return {formatted}; +}; + const getStatusVariant = (status: string): "default" | "secondary" | "outline" | "destructive" => { switch (status) { case 'active': @@ -361,6 +380,8 @@ export function Brands() { handleSort("profit_30d")} className="cursor-pointer text-right">Profit (30d) handleSort("avg_margin_30d")} className="cursor-pointer text-right">Margin (30d) handleSort("stock_turn_30d")} className="cursor-pointer text-right">Stock Turn (30d) + handleSort("salesGrowth30dVsPrev")} className="cursor-pointer text-right">Sales Growth + handleSort("revenueGrowth30dVsPrev")} className="cursor-pointer text-right">Revenue Growth handleSort("status")} className="cursor-pointer text-right">Status @@ -378,17 +399,19 @@ export function Brands() { + + )) ) : listError ? ( - + Error loading brands: {listError.message} ) : brands.length === 0 ? ( - + No brands found matching your criteria. @@ -404,6 +427,8 @@ export function Brands() { {formatCurrency(brand.profit_30d as number)} {formatPercentage(brand.avg_margin_30d as number)} {formatNumber(brand.stock_turn_30d, 2)} + {formatGrowth(brand.sales_growth_30d_vs_prev)} + {formatGrowth(brand.revenue_growth_30d_vs_prev)} {brand.status || 'Unknown'} diff --git a/inventory/src/pages/Categories.tsx b/inventory/src/pages/Categories.tsx index 9475327..8ba5486 100644 --- a/inventory/src/pages/Categories.tsx +++ b/inventory/src/pages/Categories.tsx @@ -60,6 +60,8 @@ type CategorySortableColumns = | "sales30d" | "avgMargin30d" | "stockTurn30d" + | "salesGrowth30dVsPrev" + | "revenueGrowth30dVsPrev" | "status"; interface CategoryMetric { @@ -88,6 +90,9 @@ interface CategoryMetric { lifetime_revenue: string | number; avg_margin_30d: string | number | null; stock_turn_30d: string | number | null; + // Growth metrics + sales_growth_30d_vs_prev: string | number | null; + revenue_growth_30d_vs_prev: string | number | null; // Fields from categories table status: string; description: string; @@ -108,6 +113,8 @@ interface CategoryMetric { lifetimeRevenue: string | number; avgMargin_30d: string | number | null; stockTurn_30d: string | number | null; + salesGrowth30dVsPrev: string | number | null; + revenueGrowth30dVsPrev: string | number | null; direct_active_product_count: number; direct_current_stock_units: number; direct_stock_cost: string | number; @@ -208,6 +215,19 @@ const formatPercentage = ( return `${value.toFixed(digits)}%`; }; +// Growth formatting with color coding +const formatGrowth = (value: number | string | null | undefined, digits = 1) => { + if (value == null) return N/A; + + const numValue = typeof value === "string" ? parseFloat(value) : value; + if (isNaN(numValue)) return N/A; + + const formatted = `${numValue >= 0 ? '+' : ''}${numValue.toFixed(digits)}%`; + const colorClass = numValue >= 0 ? 'text-green-600' : 'text-red-600'; + + return {formatted}; +}; + // Define interfaces for hierarchical structure interface CategoryWithChildren extends CategoryMetric { children: CategoryWithChildren[]; @@ -221,6 +241,8 @@ interface CategoryWithChildren extends CategoryMetric { revenue30d: number; profit30d: number; avg_margin_30d?: number; + sales_growth_30d_vs_prev?: number; + revenue_growth_30d_vs_prev?: number; }; } @@ -683,7 +705,9 @@ export function Categories() { profit30d: totals.profit30d, avg_margin_30d: totals.revenue30d > 0 ? (totals.profit30d / totals.revenue30d) * 100 - : 0 + : 0, + sales_growth_30d_vs_prev: parseFloat(cat.sales_growth_30d_vs_prev?.toString() || "0"), + revenue_growth_30d_vs_prev: parseFloat(cat.revenue_growth_30d_vs_prev?.toString() || "0") }; } else { // If we don't have pre-calculated values (shouldn't happen with our algorithm) @@ -694,7 +718,9 @@ export function Categories() { currentStockCost: parseFloat(cat.direct_stock_cost?.toString() || "0"), revenue30d: parseFloat(cat.direct_revenue_30d?.toString() || "0"), profit30d: parseFloat(cat.direct_profit_30d?.toString() || "0"), - avg_margin_30d: parseFloat(cat.avg_margin_30d?.toString() || "0") + avg_margin_30d: parseFloat(cat.avg_margin_30d?.toString() || "0"), + sales_growth_30d_vs_prev: parseFloat(cat.sales_growth_30d_vs_prev?.toString() || "0"), + revenue_growth_30d_vs_prev: parseFloat(cat.revenue_growth_30d_vs_prev?.toString() || "0") }; } @@ -953,6 +979,56 @@ export function Categories() { formatPercentage(category.avg_margin_30d)} + {/* Sales Growth Cell */} + + {hasChildren && category.aggregatedStats ? ( + + + + {formatGrowth(category.aggregatedStats.sales_growth_30d_vs_prev)} + + + +

+ Sales Growth (incl. children):{" "} + {formatGrowth(category.aggregatedStats.sales_growth_30d_vs_prev)} +

+

+ Directly from '{category.category_name}':{" "} + {formatGrowth(category.sales_growth_30d_vs_prev)} +

+ + + ) : ( + formatGrowth(category.sales_growth_30d_vs_prev) + )} + + + {/* Revenue Growth Cell */} + + {hasChildren && category.aggregatedStats ? ( + + + + {formatGrowth(category.aggregatedStats.revenue_growth_30d_vs_prev)} + + + +

+ Revenue Growth (incl. children):{" "} + {formatGrowth(category.aggregatedStats.revenue_growth_30d_vs_prev)} +

+

+ Directly from '{category.category_name}':{" "} + {formatGrowth(category.revenue_growth_30d_vs_prev)} +

+ + + ) : ( + formatGrowth(category.revenue_growth_30d_vs_prev) + )} + + {/* Stock Turn (30d) Cell - Display direct value */} {formatNumber(category.stock_turn_30d, 2)} @@ -1009,6 +1085,9 @@ export function Categories() { + + + @@ -1027,7 +1106,7 @@ export function Categories() { return ( {categories && categories.length > 0 ? ( @@ -1321,6 +1400,20 @@ export function Categories() { Margin (30d) + handleSort("salesGrowth30dVsPrev")} + className="cursor-pointer text-right w-[8%]" + > + Sales Growth + + + handleSort("revenueGrowth30dVsPrev")} + className="cursor-pointer text-right w-[8%]" + > + Revenue Growth + + handleSort("stockTurn30d")} className="cursor-pointer text-right w-[6%]" diff --git a/inventory/src/pages/Products.tsx b/inventory/src/pages/Products.tsx index 0a57524..69fae9c 100644 --- a/inventory/src/pages/Products.tsx +++ b/inventory/src/pages/Products.tsx @@ -182,6 +182,32 @@ const AVAILABLE_COLUMNS: ColumnDef[] = [ { key: 'first60DaysRevenue', label: 'First 60 Days Revenue', group: 'First Period', format: (v) => v === 0 ? '0' : v ? v.toFixed(2) : '-' }, { key: 'first90DaysSales', label: 'First 90 Days Sales', group: 'First Period', format: (v) => v === 0 ? '0' : v ? v.toString() : '-' }, { key: 'first90DaysRevenue', label: 'First 90 Days Revenue', group: 'First Period', format: (v) => v === 0 ? '0' : v ? v.toFixed(2) : '-' }, + + // Growth Metrics + { key: 'salesGrowth30dVsPrev', label: 'Sales Growth % (30d vs Prev)', group: 'Growth Analysis', format: (v) => v === 0 ? '0%' : v ? `${v.toFixed(1)}%` : '-' }, + { key: 'revenueGrowth30dVsPrev', label: 'Revenue Growth % (30d vs Prev)', group: 'Growth Analysis', format: (v) => v === 0 ? '0%' : v ? `${v.toFixed(1)}%` : '-' }, + { key: 'salesGrowthYoy', label: 'Sales Growth % YoY', group: 'Growth Analysis', format: (v) => v === 0 ? '0%' : v ? `${v.toFixed(1)}%` : '-' }, + { key: 'revenueGrowthYoy', label: 'Revenue Growth % YoY', group: 'Growth Analysis', format: (v) => v === 0 ? '0%' : v ? `${v.toFixed(1)}%` : '-' }, + + // Demand Variability Metrics + { key: 'salesVariance30d', label: 'Sales Variance (30d)', group: 'Demand Variability', format: (v) => v === 0 ? '0' : v ? v.toFixed(2) : '-' }, + { key: 'salesStdDev30d', label: 'Sales Std Dev (30d)', group: 'Demand Variability', format: (v) => v === 0 ? '0' : v ? v.toFixed(2) : '-' }, + { key: 'salesCv30d', label: 'Sales CV % (30d)', group: 'Demand Variability', format: (v) => v === 0 ? '0%' : v ? `${v.toFixed(1)}%` : '-' }, + { key: 'demandPattern', label: 'Demand Pattern', group: 'Demand Variability' }, + + // Service Level Metrics + { key: 'fillRate30d', label: 'Fill Rate % (30d)', group: 'Service Level', format: (v) => v === 0 ? '0%' : v ? `${v.toFixed(1)}%` : '-' }, + { key: 'stockoutIncidents30d', label: 'Stockout Incidents (30d)', group: 'Service Level', format: (v) => v === 0 ? '0' : v ? v.toString() : '-' }, + { key: 'serviceLevel30d', label: 'Service Level % (30d)', group: 'Service Level', format: (v) => v === 0 ? '0%' : v ? `${v.toFixed(1)}%` : '-' }, + { key: 'lostSalesIncidents30d', label: 'Lost Sales Incidents (30d)', group: 'Service Level', format: (v) => v === 0 ? '0' : v ? v.toString() : '-' }, + + // Seasonality Metrics + { key: 'seasonalityIndex', label: 'Seasonality Index', group: 'Seasonality', format: (v) => v === 0 ? '0' : v ? v.toFixed(2) : '-' }, + { key: 'seasonalPattern', label: 'Seasonal Pattern', group: 'Seasonality' }, + { key: 'peakSeason', label: 'Peak Season', group: 'Seasonality' }, + + // Quality Indicators + { key: 'lifetimeRevenueQuality', label: 'Lifetime Revenue Quality', group: 'Data Quality' }, ]; // Define default columns for each view @@ -198,7 +224,8 @@ const VIEW_COLUMNS: Record = { 'revenue30d', 'profit30d', 'stockCoverInDays', - 'currentStockCost' + 'currentStockCost', + 'salesGrowth30dVsPrev' ], critical: [ 'status', @@ -214,7 +241,9 @@ const VIEW_COLUMNS: Record = { 'earliestExpectedDate', 'vendor', 'dateLastReceived', - 'avgLeadTimeDays' + 'avgLeadTimeDays', + 'serviceLevel30d', + 'stockoutIncidents30d' ], reorder: [ 'status', @@ -229,7 +258,8 @@ const VIEW_COLUMNS: Record = { 'sales30d', 'vendor', 'avgLeadTimeDays', - 'dateLastReceived' + 'dateLastReceived', + 'demandPattern' ], overstocked: [ 'status', @@ -244,7 +274,8 @@ const VIEW_COLUMNS: Record = { 'stockturn30d', 'currentStockCost', 'overstockedCost', - 'dateLastSold' + 'dateLastSold', + 'salesVariance30d' ], 'at-risk': [ 'status', @@ -259,7 +290,9 @@ const VIEW_COLUMNS: Record = { 'sellsOutInDays', 'dateLastSold', 'avgLeadTimeDays', - 'profit30d' + 'profit30d', + 'fillRate30d', + 'salesGrowth30dVsPrev' ], new: [ 'status', @@ -274,7 +307,9 @@ const VIEW_COLUMNS: Record = { 'currentCostPrice', 'dateFirstReceived', 'ageDays', - 'abcClass' + 'abcClass', + 'first7DaysSales', + 'first30DaysSales' ], healthy: [ 'status', @@ -288,7 +323,9 @@ const VIEW_COLUMNS: Record = { 'profit30d', 'margin30d', 'gmroi30d', - 'stockturn30d' + 'stockturn30d', + 'salesGrowth30dVsPrev', + 'serviceLevel30d' ], }; diff --git a/inventory/src/pages/Vendors.tsx b/inventory/src/pages/Vendors.tsx index f6772d3..aaa5831 100644 --- a/inventory/src/pages/Vendors.tsx +++ b/inventory/src/pages/Vendors.tsx @@ -16,7 +16,8 @@ import { Label } from "@/components/ui/label"; type VendorSortableColumns = | 'vendorName' | 'productCount' | 'activeProductCount' | 'currentStockUnits' | 'currentStockCost' | 'onOrderUnits' | 'onOrderCost' | 'avgLeadTimeDays' - | 'revenue_30d' | 'profit_30d' | 'avg_margin_30d' | 'po_count_365d' | 'status'; + | 'revenue_30d' | 'profit_30d' | 'avg_margin_30d' | 'po_count_365d' + | 'salesGrowth30dVsPrev' | 'revenueGrowth30dVsPrev' | 'status'; interface VendorMetric { vendor_id: string | number; @@ -43,6 +44,9 @@ interface VendorMetric { lifetime_sales: number; lifetime_revenue: string | number; avg_margin_30d: string | number | null; + // Growth metrics + sales_growth_30d_vs_prev: string | number | null; + revenue_growth_30d_vs_prev: string | number | null; // New fields added by vendorsAggregate status: string; vendor_status: string; @@ -68,6 +72,8 @@ interface VendorMetric { lifetimeSales: number; lifetimeRevenue: string | number; avgMargin_30d: string | number | null; + salesGrowth30dVsPrev: string | number | null; + revenueGrowth30dVsPrev: string | number | null; } // Define response type to avoid type errors @@ -162,6 +168,19 @@ const formatDays = (value: number | string | null | undefined, digits = 1): stri return `${value.toFixed(digits)} days`; }; +// Growth formatting with color coding +const formatGrowth = (value: number | string | null | undefined, digits = 1) => { + if (value == null) return N/A; + + const numValue = typeof value === "string" ? parseFloat(value) : value; + if (isNaN(numValue)) return N/A; + + const formatted = `${numValue >= 0 ? '+' : ''}${numValue.toFixed(digits)}%`; + const colorClass = numValue >= 0 ? 'text-green-600' : 'text-red-600'; + + return {formatted}; +}; + const getStatusVariant = (status: string): "default" | "secondary" | "outline" | "destructive" => { switch (status) { case 'active': @@ -381,6 +400,8 @@ export function Vendors() { handleSort("profit_30d")} className="cursor-pointer text-right">Profit (30d) handleSort("avg_margin_30d")} className="cursor-pointer text-right">Margin (30d) handleSort("po_count_365d")} className="cursor-pointer text-right">POs (365d) + handleSort("salesGrowth30dVsPrev")} className="cursor-pointer text-right">Sales Growth + handleSort("revenueGrowth30dVsPrev")} className="cursor-pointer text-right">Revenue Growth handleSort("status")} className="cursor-pointer text-right">Status @@ -399,17 +420,19 @@ export function Vendors() { + + )) ) : listError ? ( - + Error loading vendors: {listError.message} ) : vendors.length === 0 ? ( - + No vendors found matching your criteria. @@ -426,6 +449,8 @@ export function Vendors() { {formatCurrency(vendor.profit_30d as number)} {formatPercentage(vendor.avg_margin_30d as number)} {formatNumber(vendor.po_count_365d || vendor.poCount_365d)} + {formatGrowth(vendor.sales_growth_30d_vs_prev)} + {formatGrowth(vendor.revenue_growth_30d_vs_prev)} {vendor.status || 'Unknown'} diff --git a/inventory/src/types/products.ts b/inventory/src/types/products.ts index 9475b3f..6f32e5f 100644 --- a/inventory/src/types/products.ts +++ b/inventory/src/types/products.ts @@ -213,6 +213,44 @@ export interface ProductMetric { // Yesterday yesterdaySales: number | null; + // Growth Metrics (P3) + salesGrowth30dVsPrev: number | null; + revenueGrowth30dVsPrev: number | null; + salesGrowthYoy: number | null; + revenueGrowthYoy: number | null; + + // Demand Variability Metrics (P3) + salesVariance30d: number | null; + salesStdDev30d: number | null; + salesCv30d: number | null; + demandPattern: string | null; + + // Service Level Metrics (P5) + fillRate30d: number | null; + stockoutIncidents30d: number | null; + serviceLevel30d: number | null; + lostSalesIncidents30d: number | null; + + // Seasonality Metrics (P5) + seasonalityIndex: number | null; + seasonalPattern: string | null; + peakSeason: string | null; + + // Lifetime Metrics + lifetimeSales: number | null; + lifetimeRevenue: number | null; + lifetimeRevenueQuality: string | null; + + // First Period Metrics + first7DaysSales: number | null; + first7DaysRevenue: number | null; + first30DaysSales: number | null; + first30DaysRevenue: number | null; + first60DaysSales: number | null; + first60DaysRevenue: number | null; + first90DaysSales: number | null; + first90DaysRevenue: number | null; + // Calculated status (added by frontend) status?: ProductStatus; } @@ -364,7 +402,24 @@ export type ProductMetricColumnKey = | 'dateLastReceived' | 'dateFirstReceived' | 'dateFirstSold' - | 'imageUrl'; + | 'imageUrl' + // New metrics from P3-P5 implementation + | 'salesGrowth30dVsPrev' + | 'revenueGrowth30dVsPrev' + | 'salesGrowthYoy' + | 'revenueGrowthYoy' + | 'salesVariance30d' + | 'salesStdDev30d' + | 'salesCv30d' + | 'demandPattern' + | 'fillRate30d' + | 'stockoutIncidents30d' + | 'serviceLevel30d' + | 'lostSalesIncidents30d' + | 'seasonalityIndex' + | 'seasonalPattern' + | 'peakSeason' + | 'lifetimeRevenueQuality'; // Mapping frontend keys to backend query param keys export const FRONTEND_TO_BACKEND_KEY_MAP: Record = { @@ -427,7 +482,24 @@ export const FRONTEND_TO_BACKEND_KEY_MAP: Record = { overstockedCost: 'overstockedCost', isOldStock: 'isOldStock', yesterdaySales: 'yesterdaySales', - status: 'status' // Frontend-only field + status: 'status', // Frontend-only field + // New metrics from P3-P5 implementation + salesGrowth30dVsPrev: 'salesGrowth30dVsPrev', + revenueGrowth30dVsPrev: 'revenueGrowth30dVsPrev', + salesGrowthYoy: 'salesGrowthYoy', + revenueGrowthYoy: 'revenueGrowthYoy', + salesVariance30d: 'salesVariance30d', + salesStdDev30d: 'salesStdDev30d', + salesCv30d: 'salesCv30d', + demandPattern: 'demandPattern', + fillRate30d: 'fillRate30d', + stockoutIncidents30d: 'stockoutIncidents30d', + serviceLevel30d: 'serviceLevel30d', + lostSalesIncidents30d: 'lostSalesIncidents30d', + seasonalityIndex: 'seasonalityIndex', + seasonalPattern: 'seasonalPattern', + peakSeason: 'peakSeason', + lifetimeRevenueQuality: 'lifetimeRevenueQuality' }; // Function to get backend key safely