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Formula, worked example, and the traps.",false,"md",{},"\u002Fglossary\u002Freorder-point",3,[336,337,338,339,340],"safety-stock","stockout","contribution-margin","bayesian-inference","low-margin-sku",{"title":342,"description":329},"What is a Reorder Point? Formula and Example | DataGlass",{"loc":333},[345,348],{"title":323,"url":346,"note":347},"https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FReorder_point","The standard reorder-point formulation as lead-time demand plus safety stock.",{"title":349,"url":350,"note":351},"Economic order quantity","https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FEconomic_order_quantity","The separate order-quantity decision, trading ordering cost against holding cost — what the reorder point deliberately does not answer.","glossary\u002Freorder-point","ezerPr-Cnd-UE99kCq8Rm1gO4O4aOSTIafZ0leGPpAw",{"frontmatter":355,"meta":362,"nodes":391},{"title":323,"description":329,"seo":356,"short":327,"category":310,"related":357,"date":328,"sources":358,"cta":361,"readMinutes":334},{"title":342,"description":329},[336,337,338,339,340],[359,360],{"title":323,"url":346,"note":347},{"title":349,"url":350,"note":351},{"title":326,"body":327},{"toc":363},{"title":364,"searchDepth":365,"depth":365,"links":366},"",2,[367,370,373,376,379,382,385,388],{"id":368,"depth":365,"text":369},"formula","Formula",{"id":371,"depth":365,"text":372},"example","Example",{"id":374,"depth":365,"text":375},"what-lead-time-should-you-use","What lead time should you use?",{"id":377,"depth":365,"text":378},"how-do-campaign-days-change-the-reorder-point","How do campaign days change the reorder point?",{"id":380,"depth":365,"text":381},"what-does-the-reorder-point-not-decide","What does the reorder point not decide?",{"id":383,"depth":365,"text":384},"why-it-matters","Why it matters",{"id":386,"depth":365,"text":387},"in-dataglass","In DataGlass",{"id":389,"depth":365,"text":390},"where-this-shows-up","Where this shows up",[392,396,399,408,410,415,417,420,422,425,427,430,432,435,440,442,445,447],[393,394,395],"p",{},"A reorder point is the on-hand inventory level at which a replenishment order must be placed so that new stock arrives before the existing stock runs out. It equals expected demand over the replenishment lead time plus safety stock. The first term covers what will sell while the order is in transit; the second covers the possibility that demand runs hot or the shipment runs late. Unlike a calendar-based ordering habit, a reorder point responds to how fast a product is actually selling, which is what makes it robust to the demand swings that marketplace campaign calendars produce.",[397,398,369],"h2",{"id":368},[400,401,403],"pre",{"language":402},"text",[404,405,407],"code",{"class":406},"language-text","Reorder point = (average daily demand × lead time in days) + safety stock\n\nWith in-transit stock:\n  order when  (on hand + on order) ≤ reorder point\n\nOrder quantity is a separate decision — see economic order quantity.",[397,409,372],{"id":371},[400,411,412],{"language":402},[404,413,414],{"class":406},"Average daily demand 20 units, supplier lead time 14 days,\nsafety stock 108 units at a 95% service level.\n\nReorder point = (20 × 14) + 108 = 388 units\n\nWith 500 on hand and nothing on order, no action.\nAt 388 the order goes out. It arrives with roughly 108 units left,\nunless demand or the supplier misbehaves — which is what the 108 is for.",[397,416,375],{"id":374},[393,418,419],{},"The full one, measured from the moment you decide to order to the moment the stock is sellable. That includes the internal approval and purchase-order step, the supplier’s production or picking time, transit, customs clearance, inbound receiving, quality check, and getting the units listed and available — including any marketplace-warehouse inbound time if you use one. Sellers routinely use the supplier’s quoted shipping time alone and are then surprised by stockouts, because the quoted number is often less than half of the real elapsed time. Measure it from your own purchase history rather than from the supplier’s claim, and measure its variability at the same time, because that variability is the dominant input into safety stock.",[397,421,378],{"id":377},[393,423,424],{},"They break the average-daily-demand term, which is the assumption the whole formula rests on. If a mega-campaign falls inside the lead-time window, expected demand over that window is not fourteen ordinary days — it is twelve ordinary days plus two days at several times the rate. The fix is to compute lead-time demand from a forward forecast that knows the campaign calendar, rather than from a trailing average that does not. Shops that reorder on a trailing average reliably stock out in the week after a campaign, because the campaign both consumed the buffer and inflated the average that the next order was sized from.",[397,426,381],{"id":380},[393,428,429],{},"How much to order. The reorder point answers when; the order quantity is a separate optimisation trading the fixed cost of placing and receiving an order against the cost of holding what arrives, which is the economic order quantity problem. Conflating the two produces one of two failure modes: ordering the reorder-point quantity every time, which orders too frequently in small lots, or ordering a fixed large quantity regardless of how demand has shifted. On marketplaces there is a third input as well, since supplier price breaks and container economics often dominate the textbook trade-off.",[397,431,384],{"id":383},[393,433,434],{},"Most marketplace shops replenish on a rhythm — a weekly review, a monthly purchase order — rather than on a level, and the rhythm does not know when a product is selling faster than usual. A reorder point converts replenishment from a calendar habit into a demand-responsive trigger, which is the difference between discovering a stockout and preventing one. It is also the cheapest inventory improvement available, because it needs no new data beyond demand, lead time, and their variability.",[436,437,439],"blog-callout",{"title":438},"Common mistake","Comparing the reorder point against on-hand stock only. Stock already ordered and in transit counts toward covering lead-time demand, and ignoring it produces duplicate orders and overstock — the classic pattern of a shop that stocks out and then over-corrects two weeks later when both shipments land.",[397,441,387],{"id":386},[393,443,444],{},"DataGlass computes reorder points per SKU from forecast demand over the measured lead time plus a safety buffer sized from that SKU’s own demand variability, and accounts for stock already in transit. Known campaign windows are included in the lead-time demand rather than smoothed into a trailing average.",[397,446,390],{"id":389},[448,449,450,458,464],"ul",{},[451,452,453],"li",{},[454,455,457],"a",{"href":456},"\u002Fmy\u002Fblog\u002Finventory-stockout","Inventory & stockout",[451,459,460],{},[454,461,463],{"href":462},"\u002Fmy\u002Fblog\u002Finventory-stockout-math-ecommerce","Stockout math for e-commerce sellers",[451,465,466],{},[454,467,469],{"href":468},"\u002Fmy\u002Fblog\u002Fml-demand-forecasting-for-ecommerce","ML demand forecasting for e-commerce sellers",[471,472,473,474,475,476,477,478],{"id":368,"depth":365,"text":369},{"id":371,"depth":365,"text":372},{"id":374,"depth":365,"text":375},{"id":377,"depth":365,"text":378},{"id":380,"depth":365,"text":381},{"id":383,"depth":365,"text":384},{"id":386,"depth":365,"text":387},{"id":389,"depth":365,"text":390},{"id":480,"categories":481,"domain":488,"extension":5,"fallback":489,"home":492,"industry":501,"meta":506,"pricing":507,"stem":519,"__hash__":520},"og_en\u002Fen\u002Fog.yml",[482,483,484,485,486,487],{"slug":302,"label":303},{"slug":305,"label":27},{"slug":307,"label":308},{"slug":310,"label":311},{"slug":316,"label":317},{"slug":319,"label":48},"dataglasslabs.com",{"title":490,"description":491},"DataGlass","The decision engine for Shopee, Lazada and TikTok Shop sellers.",{"chart":493,"metrics":494},"Net profit, last 30 days",[495,498],{"label":496,"value":497},"Net profit","฿1.24M",{"label":499,"value":500},"Profit ROAS","3.4x",{"axis":502,"point":503},"Ad spend",{"label":504,"value":505},"Next baht still pays","+฿0.42",{},{"plans":508},[509,513,516],{"name":510,"price":511,"period":512},"Free","฿0","\u002Fmonth",{"name":514,"price":515,"period":512},"Standard","฿1,499",{"name":517,"price":518,"period":512},"Pro","฿2,499","en\u002Fog","63L8y4Lv8I2q3NvR26fMXU1sE9Wd7TZaz2l_tV6oZuo",[],[523,527,531,535,539],{"path":524,"title":525,"short":526,"draft":330},"\u002Fglossary\u002Fsafety-stock","Safety stock","The buffer held against demand and lead-time variance. Priced by what a stockout costs you, not by a rule of thumb.",{"path":528,"title":529,"short":530,"draft":330},"\u002Fglossary\u002Fstockout","Stockout","Inventory hitting zero on a SKU customers want to buy. Lost revenue, wasted ad spend, and a ranking penalty that outlasts the restock.",{"path":532,"title":533,"short":534,"draft":330},"\u002Fglossary\u002Fcontribution-margin","Contribution margin","Revenue minus every variable cost of selling one more unit — the profit each sale actually contributes after fees, ads, and fulfillment.",{"path":536,"title":537,"short":538,"draft":330},"\u002Fglossary\u002Fbayesian-inference","Bayesian inference","Estimating with a range instead of a single number, so a decision can account for how little it actually knows.",{"path":540,"title":541,"short":542,"draft":330},"\u002Fglossary\u002Flow-margin-sku","Low-margin SKU","A product whose contribution per unit is too thin to fund the attention it consumes — often a former bestseller nobody re-checked.",1792785009001]