https://reorconsulting.com/assets/FmcgQuickCommerce-CNNf5TLA.js

1import{j as e,P as r,N as n,F as a}from"./index-DmHrUkhe.js";import{C as s}from"./CTASection-C9cvLOMR.js";import{I as l,a as o,C as c,b as d,c as m,E as p,O as u,R as h}from"./IndustryPage-Dcc7_Bge.js";import"./check-lV1fgzPV.js";import"./arrow-right-CTGmh4R-.js";const g=["Sell-out","Inventory","In-Transit","Location","Promotion","Historical Demand"],f=[{title:"Demand Forecast",detail:"SKU × Platform × Dark Store × Time",tone:"engine"},{title:"Stock-out Risk",detail:"Locations about to go out of stock",tone:"action"},{title:"Replenishment Priority",detail:"Where the next dispatch matters most",tone:"action"},{title:"Inventory Requirement",detail:"Quantity needed by location and period",tone:"action"},{title:"Performance Intelligence",detail:"Platform, geography and SKU performance",tone:"insight"}],y={engine:"border-primary bg-primary text-primary-foreground",action:"border-accent/60 bg-surface-amber text-foreground",insight:"border-terracotta/60 bg-terracotta/10 text-foreground"},b=()=>e.jsxs("figure",{className:"rounded-xl border border-border bg-surface p-5 sm:p-8",children:[e.jsx("p",{className:"text-[10px] font-bold uppercase tracking-[0.18em] text-muted-foreground",children:"Platform data available to the brand"}),e.jsx("div",{className:"mt-3 grid grid-cols-2 gap-2 sm:grid-cols-3 lg:grid-cols-6",children:g.map(t=>e.jsx("div",{className:"rounded-md border border-brand-blue/50 bg-brand-blue/10 px-3 py-2.5 text-xs font-semibold text-foreground",children:t},t))}),e.jsx("div",{className:"mt-5 rounded-lg border border-dashed border-primary/50 px-4 py-2 text-center text-[10px] font-bold uppercase tracking-[0.18em] text-muted-foreground",children:"Ingested and normalised by REOR"}),e.jsx("div",{className:"mt-5 grid gap-3 sm:grid-cols-2 lg:grid-cols-5",children:f.map((t,i)=>e.jsxs("div",{className:`rounded-lg border p-4 ${y[t.tone]}`,children:[e.jsxs("span",{className:"text-[10px] font-bold uppercase tracking-[0.18em] opacity-70",children:["Stage ",i+1]}),e.jsx("p",{className:"mt-1 text-sm font-bold leading-snug",children:t.title}),e.jsx("p",{className:"mt-2 text-xs leading-relaxed opacity-80",children:t.detail})]},t.title))}),e.jsx("figcaption",{className:"mt-6 text-xs uppercase tracking-widest text-muted-foreground",children:"From reported sales to predicted inventory requirement"})]}),x=[{dimension:"Thousands of fulfilment locations",detail:"A brand's inventory and sales are spread across hundreds or thousands of dark stores, each with its own demand pattern."},{dimension:"SKU × Platform × Location × Time",detail:"The same SKU sells at very different rates by platform, by city and by week, so aggregate numbers hide the decision."},{dimension:"Geographic demand variation",detail:"Neighbouring locations can differ sharply by pack size, variant and price sensitivity."},{dimension:"Backward-looking reporting",detail:"Platform reports explain what already sold. They do not say where inventory will be required next."},{dimension:"Promotions distort signals",detail:"Platform-led promotions spike sell-out, and without adjustment that spike contaminates the next forecast."},{dimension:"Limited direct control",detail:"The brand influences supply into the platform, not the platform's internal allocation, so prioritisation matters more than control."}],v=[{challenge:"Teams review last week's platform sales and react",reor:"REOR forecasts SKU-location demand forward, so the conversation shifts from what sold to where inventory will be required next.",outcome:"Proactive supply instead of retrospective review"},{challenge:"Stock-outs at location level are invisible",reor:"Stock-out risk is identified per SKU-location from sell-out velocity, on-hand, in-transit and cover.",outcome:"At-risk locations flagged before availability drops"},{challenge:"Replenishment is spread evenly across the network",reor:"Replenishment priority ranks locations by forecast demand and stock-out risk, so limited stock goes where it earns most.",outcome:"Dispatches prioritised by expected impact"},{challenge:"Inventory requirement is guessed at a national level",reor:"Requirement is computed bottom-up from SKU-location forecasts, cover targets and lead times, then rolled up by platform and region.",outcome:"Requirement plans grounded in location demand"},{challenge:"Platform and geography performance is hard to compare",reor:"Business 360° compares sell-out, availability, cover and growth by platform, city and dark-store cluster.",outcome:"Clear view of which platforms and geographies to back"},{challenge:"Promotion demand is planned informally",reor:"Promotion periods are modelled as separate demand events by platform and location, with uplift stripped from the baseline afterwards.",outcome:"Promotions supplied without post-event excess"}],k=["SKU-location demand forecasting","Platform-wise demand analysis","Dark-store and location performance","Stock-out identification","Days of cover monitoring","Replenishment recommendations","Inventory availability tracking","Promotion demand modelling","Geographic demand comparison","Business 360° analytics"],w=["Where will inventory be required next week?","Which SKU-location combinations are at stock-out risk?","Which locations should be replenished first?","How much cover do we hold by platform?","How much extra stock does this promotion need?","Which cities and dark-store cluster

1s are growing?"],j=[{title:"Forward-looking supply planning",description:"The core shift: from looking at historical quick-commerce sales to predicting where inventory will be required next."},{title:"Fewer location-level stock-outs",description:"Risk scoring at SKU-location grain surfaces gaps while a dispatch can still fix them."},{title:"Better return on quick-commerce inventory",description:"Replenishment priority concentrates stock in locations with real forecast demand rather than spreading it thin."}],N=()=>e.jsxs("div",{className:"min-h-screen",children:[e.jsx(r,{title:"FMCG Quick Commerce Intelligence Software | REOR",description:"Plan and replenish FMCG inventory on quick-commerce platforms by SKU, dark store and location. REOR improves fill rates and reduces stockout days.",path:"/industries/fmcg-quick-commerce"}),e.jsx(n,{}),e.jsxs("main",{children:[e.jsx(l,{title:"FMCG Brands in",highlight:"Quick Commerce",model:"SKU × Platform × Dark Store/Location × Time",lead:"Help FMCG brands move from looking at historical quick-commerce sales to proactively predicting where inventory will be required next.",note:"This page is for FMCG and consumer brands selling through quick-commerce platforms. It is not a page for quick-commerce retailers themselves. REOR forecasts and prioritises the brand's supply decisions; it does not control or automatically change a third-party platform's inventory."}),e.jsx(o,{eyebrow:"Unique complexity",title:"Demand Scattered Across Thousands of Locations",lead:"A consumer brand's quick-commerce demand is distributed across a very large number of fulfilment points, each behaving differently.",tone:"ivory",children:e.jsx(c,{items:x})}),e.jsx(o,{eyebrow:"REOR operating model",title:"Ingest Available Signals, Produce Forward Decisions",children:e.jsx(b,{})}),e.jsx(o,{eyebrow:"Key challenges",title:"How REOR Solves Quick-Commerce Problems",tone:"blue",children:e.jsx(d,{items:v})}),e.jsx(o,{eyebrow:"How REOR helps",title:"Capabilities Applied to Quick Commerce",children:e.jsx(m,{items:k,columns:3})}),e.jsx(o,{eyebrow:"Example decisions",title:"Questions REOR Answers",tone:"ivory",children:e.jsx(p,{items:w})}),e.jsx(o,{eyebrow:"Business outcomes",title:"What Changes in the Numbers",children:e.jsx(u,{items:j})}),e.jsx(o,{eyebrow:"Relevant solutions",title:"The REOR Modules Behind This",tone:"blue",children:e.jsx(h,{items:[{name:"Demand Forecasting",reason:"SKU-platform-location forecasts including promotion and seasonality effects."},{name:"Inventory Intelligence",reason:"Stock-out risk, cover, replenishment priority and inventory requirement."},{name:"Business 360°",reason:"Platform, city and dark-store performance intelligence in one view."},{name:"Planning",reason:"Supply and inventory requirement planning rolled up from location demand."}]})}),e.jsx(s,{})]}),e.jsx(a,{})]});export{N as default};