# Brand-owner weekly summary — playbook Plain-English definitions of every term, section, and threshold BIC needs to produce or interpret a brand-owner weekly summary. One concept per paragraph so each chunk stands on its own at retrieval time. ## What a brand-owner weekly summary is A **brand-owner weekly summary** is the Monday-morning deck a single brand owner (e.g. the owner of VALLI) gets covering the previous Monday-through-Sunday of trading. It rolls up every store under that one `FORMAT` and shows performance vs last year, vs ABP target, and vs the prior 13 weeks. Each `FORMAT` (VALLI, KLM, VML, MANDIR, KM) gets its OWN summary — never one mixed deck. The Chief Analyst writes a separate card per format so the owner sees only their brand. The pipeline runs every weekday at **08:30 IST** (raw computation) and **09:00 IST** (Chief Analyst curation). Owners sign in by ~10:00 IST and the homepage shows their cards. ## Week boundary The weekly window is **Monday 00:00 IST through Sunday 23:59 IST** of the PREVIOUS week. On Monday morning the summary covers the week that just closed; it does NOT include any Monday-of-current-week numbers. For comparisons, **PY-week** is the same Monday-through-Sunday window in the previous calendar year, NOT the calendar week of last year. We compare trading days to trading days, not week numbers. If a Sunday in the previous year was a major festival (Diwali) and this year's matching Sunday is not, expect a large negative growth artefact — flag it as a calendar mismatch, do NOT call it degrowth. ## Per-format scope When the summary says *"VALLI WTD net sales"* it means `sum(SALE_NET_AMOUNT) WHERE FORMAT='VALLI' AND lower(trType)='sale'` over the previous Mon–Sun window. ALL stores under that FORMAT roll up together. When the summary breaks down BY store, it filters to the same FORMAT and groups by `shortname`. When it breaks down BY section, it groups by `SALE_SECTION` (or `ABP_Section` when joining with ABP). Vendor breakdowns within a format use `SALE_VENDORGROUP_NAME` — that's the "merchandise brand" hierarchy, distinct from the store-format brand (VALLI/KLM are FORMATs, not vendor groups). ## Section 1 — Sales summary **What it answers:** how big was the brand last week, compared to LY and to ABP plan. **KPIs reported:** - Net sales for the week (in **crores** at brand level, two decimals) - Net sales LY-week (same window, previous year) - YoY growth % = (CY − LY) / LY × 100 - Net sales month-to-date and ABP achievement % MTD - Bills (count distinct saleId) and units sold **Anomaly flags raised here:** YoY growth < −10% → **warning**; < −20% → **critical**. ABP achievement < 80% with > 25% of the month elapsed → **warning**. ## Section 2 — KPI deep-dive **What it answers:** are baskets getting heavier or lighter, and is ASP moving. **Metrics:** - **ABS** (Average Basket Size) = `sum(SALE_QTY) / count(distinct saleId)` - **ABV** (Average Basket Value) = `sum(SALE_NET_AMOUNT) / count(distinct saleId)` - **ASP** (Average Selling Price) = `sum(SALE_NET_AMOUNT) / sum(SALE_QTY)` - **SSPD** (Sales per sqft per day) = `sum(SALE_NET_AMOUNT) / sum(AREA) / days_in_window` All four reported per FORMAT, with WoW % change and YoY % change. **Anomaly flags raised here:** any KPI > 15% movement WoW → **warning**. Bill count drop > 10% with ABV growth — flag as **traffic erosion masked by basket inflation**. ## Section 3 — 13-week trend **What it answers:** is last week part of a trend, or a one-off. **Output:** weekly net sales for the last 13 weeks with PY overlay. Same Monday-of-week boundary as the weekly summary. **Anomaly flags raised here:** - 4 consecutive weeks of negative growth → **SUSTAINED_DECLINE_4_WEEKS** (warning) - WoW step change > 20% (positive or negative) → **STEP_CHANGE_>20%** (warning) - One-off spike that does not repeat next week — note it but do not flag. ## Section 4 — Store grading **What it answers:** which stores in this format are pulling the format up or down. **Grading scheme** based on YoY growth in the weekly window: - **A** — growth > +10% AND ABP achievement > 95% - **B** — growth between 0% and +10% AND ABP achievement > 80% - **C** — growth between −10% and 0% OR ABP achievement 60–80% - **D** — growth < −10% OR ABP achievement < 60% **Anomaly flag:** any store classified D for two consecutive weeks → **STRUCTURAL_DECLINE_SIGNAL** (critical). Card audience: persona:owner + designation:area manager covering that store. ## Section 5 — Section / sub-section performance **What it answers:** within the brand, which merchandise sections drove or dragged growth. **Output:** for each `SALE_SECTION` and the top 10 `SALE_SUBSECTION` lines within it: net sales CY, net sales LY, growth %, contribution % of total brand sales. **Anomaly flags raised here:** - Section growth < −50% week-on-week → **SEVERE_DEGROWTH_>50%** (critical) - Section appearing in current week with no LY presence → **NEW_SECTION** (info) - Section with ABP target set but zero sales → **NO_ABP_TARGET_SET** (warning) ## Section 6 — Stock health **What it answers:** is inventory positioned to support next week's sales. **KPIs reported per format:** - Total SOH units and value (in **lakhs**) - SOH > 180 days as % of total (the "old stock" share) - MBQ gap = `sumIf(Qty, Data_type='MBQ') − sumIf(Qty, Data_type='STOCK')` per (store × section), positive values are shortfalls - Number of SKUs at zero stock with MBQ > 0 (the "stockout" count) **Anomaly flags raised here:** - Old-stock share > 30% → **INVENTORY_BUILDUP_RISK** (warning) - 100% of brand stock in 180+ age bucket → **100_PCT_OLD_STOCK** (critical) - Stockout count growing while sales declining → **STOCK_GROWING_REVENUE_DECLINING** (critical, cross-cutting) ## Section 7 — Staffing gaps **What it answers:** are stores understaffed against MBQ. **KPI:** `required_employees − current_employees` per `Staff_MBQ_Vs_Current_Staff_Vs_Monthly_Staff` row, summed by store. **Anomaly flags raised here:** - Gap > 5 in any single store → **GAP_GREATER_THAN_5** (warning) - Multiple sections in same store understaffed → **MULTI_SECTION_UNDERSTAFFED** (critical) Card audience: persona:store_ops + designation:store manager for the affected store, NOT the brand owner (operational, not strategic). ## Section 8 — CRM / customer retention **What it answers:** is the brand losing or gaining repeat buyers, and is the average ticket eroding within a customer segment. **Metrics:** - Retained customers / total LY customers (the retention ratio) - New customers acquired this week - Largest declining segment (by ASP or by bill count) **Anomaly flags raised here:** - Largest segment declining 4 weeks running → **LARGEST_SEGMENT_DECLINING** (warning) - ASP within a previously-stable segment dropping > 10% → **ASP_EROSION_IN_SEGMENT** (warning) ## Section 9 — Cross-cutting anomalies **What it answers:** patterns no single section can see. **Composite flags:** - All 3 KPIs (sales, units, bills) declining together → **ALL_3_KPIs_DECLINING** (critical) - Stock growing while revenue declining → **STOCK_GROWING_REVENUE_DECLINING** (critical) - A store with no sales at all in WTD → **NO_SALES_IN_WTD** (critical, store-ops) - ABP target row missing for an active store → **ABP_TARGET_MISSING** (warning, data-quality) - ASP eroding inside the CRM segments while net sales look flat at brand level → **CRM_ASP_EROSION** (warning) — masked margin compression. ## Section 10 — Synopsis (executive summary) **What it answers:** the 30-second version for the brand owner. **Format:** 4–6 bullet points. The Chief Analyst writes this — it must NAME the number, NAME the comparison window, and NAME the action. Example: *"VALLI WTD ₹3.42 Cr, down 8.4% vs PY-WTD; VAL-HYD store flagged D for second week — area manager review by Wednesday."* The synopsis is also the body of the homepage card; everything else is drill-down. Length cap: 60 words. ## Lakhs vs crores in this report Within a single format's weekly summary, headlines (brand-level totals) are in **crores** to two decimals. Store-level figures are in **lakhs**. Section-level breakdowns are in **lakhs**. Vendor-level breakdowns are in **lakhs**. Never mix units within one bullet. Always state the unit explicitly when quoting a figure: `₹3.42 Cr`, `₹84.50 L`. ## Severity thresholds — quick reference Card severity follows a single table the Chief Analyst applies: - **critical** — directly affects revenue, target attainment, or stockout risk: YoY growth < −20%, ABP achievement < 60% with the month half-elapsed, 100% old stock, all-3-KPIs declining, structural decline signal. - **warning** — soft early signals: WoW step change > 20%, MBQ gap > 5 staff, ASP erosion in a segment, sustained 4-week decline, retention drop. - **info** — noteworthy positives or context: new section appearing, growth > +20% in a section, new customer acquisition spikes. Cards default to **info** when in doubt — over-warning erodes trust. ## Audience tagging conventions for the Chief Analyst Each card the Chief Analyst writes from a brand-owner weekly summary should carry one of: - `persona:owner` — visible to every brand owner. Use for cross-brand patterns. - `user:` — visible only to the named brand owner. Use when the card is specific to that one brand and that one person should act on it. The pipeline knows: VALLI → user X, KLM → user Y, etc. - `designation:area manager` — operational signals about a region (stockouts, store grading drops). Surface to area managers in addition to the owner. - `designation:store manager` — store-specific operational items only. Brand owner generally does NOT need to see these. A card can hold 1–3 audience tokens. Bias toward `user:` for the weekly synopsis card; use `persona:owner` for items the whole owner cohort benefits from seeing. ## Ask BIC about this playbook - "What goes into a brand owner weekly summary?" - "What week boundary does the weekly summary use?" - "When is a store graded D?" - "What threshold makes a sales drop critical?" - "How are lakhs vs crores used in the weekly report?"