The New SKU Planning Problem
Every inventory planning decision is made with some degree of uncertainty, but new product launches represent the extreme end of that spectrum. For an established SKU, you have velocity data, seasonal patterns, channel behavior, and promotional response history to draw on. For a new SKU, you have analogues, assumptions, and a best-guess demand estimate.
That uncertainty gets expensive fast. An opening order quantity that's too conservative leaves you with an early stockout, a frustrated wholesale buyer, and a viral moment that has no inventory behind it. An opening order that's too aggressive leaves you with capital tied up in inventory that's moving slowly during the critical launch window — and a product that may enter the clearance phase before it ever had a chance to establish its sales baseline.
There's no formula that eliminates this uncertainty. But there is a structured decision framework that makes the uncertainty explicit, sets appropriate guardrails, and builds the conditions for a faster response when actual demand diverges from forecast.
Step 1: Define the Demand Analogue
The starting point for any new SKU demand forecast is identifying the best analogue in your existing catalog. An analogue is a prior SKU that shares as many relevant characteristics as possible: price point, category, channel distribution, target customer, and seasonal positioning.
A perfect analogue rarely exists. The goal is the closest available reference point. A new summer dress launching at $148 DTC is best analogized to your prior summer dress launches at similar price points — not to your core denim line or your accessories category. A new wholesale-distributed candle collection is best analogized to prior candle launches that went into wholesale channels, not to candle launches that ran DTC-only.
The analogue gives you a starting velocity estimate: "Our last comparable launch ran at X units/week in weeks 1–4." The new SKU forecast starts there, adjusted for any meaningful differences you can quantify — different price point, different channel mix, different launch timing, different promotional support.
Document the analogue selection explicitly. It forces the team to be honest about the strength of the comparison and creates an accountability record for the forecast assumptions. When actual performance diverges from forecast (and it will), understanding whether the analogue was a good or poor choice is how you improve future launch forecasting.
Step 2: Set the Opening Order Quantity Range
Rather than committing to a single opening order quantity, the structured approach builds a quantity range tied to your demand scenarios:
- Floor quantity: The minimum order that makes production economics viable and covers your committed wholesale obligations with modest DTC inventory. Based on the low demand scenario — the analogue's worst comparable performance.
- Base quantity: Your best estimate of required inventory for the primary selling window, based on the analogue's average performance. Should include safety stock for demand variance.
- Ceiling (option) quantity: The quantity you'd want if demand tracks to the high scenario. This isn't necessarily what you order upfront — it's what you'd like to be able to access quickly if early velocity signals are strong.
The opening order is typically the base quantity, placed at lead time. The critical addition is the "option" conversation with your supplier: can they produce additional units on a shortened timeline if demand in weeks 1–3 significantly exceeds forecast? What is the minimum order quantity for a reorder? What is the realistic expedite timeline?
Having that conversation before you place the opening order — not after you see demand is exceeding forecast — is the difference between a successful scale-up and a stockout with a 6-week gap before replenishment arrives.
Step 3: Structure the Channel Split
For brands selling through both DTC and wholesale, the opening order quantity needs to be split across channels. The default approach — fulfill wholesale commitments first, keep the remainder for DTC — is often correct but not always.
The nuance: wholesale buyers typically want product in their stores before your DTC site launches, to give their retail channel the impression of exclusivity or early access. DTC demand often ramps faster once the product is visible online. Structuring the channel split to give wholesale a 2–3 week early delivery window while your DTC site carries pre-launch waitlist or "coming soon" marketing can generate stronger DTC demand data and better manage the channel relationship simultaneously.
Whatever the split structure, it should be decided before the opening order is placed — not improvised when inventory arrives at the DC. Once 800 units hit the DC and both your wholesale buyer and your DTC ops team are asking for the inventory simultaneously, the allocation decision happens under pressure rather than based on strategy.
Step 4: Define Early Velocity Triggers
The most critical planning decision for a new SKU launch isn't the opening order — it's what you do in weeks 2–5 based on actual sell-through. Define the velocity triggers before launch:
- Green signal: If 4-week sell-through exceeds X% of opening order, initiate reorder immediately at [quantity]. This trigger should fire automatically based on POS data — no waiting for a monthly planning meeting.
- Yellow signal: If 4-week sell-through is tracking between Y% and X%, extend observation for two more weeks. Evaluate whether DTC performance vs. wholesale performance diverges.
- Red signal: If 4-week sell-through is below Y%, begin markdown evaluation. Is the velocity issue price-driven? Placement-driven? Product-driven? Act within the season, not after.
The specific thresholds depend on your category's typical launch velocity patterns. A fashion-forward brand launching trend-driven items typically sets higher green thresholds because trend items need to move fast before the window closes. A basics brand launching a core replenishable style can afford a more measured early-season response.
Sizing the Buffer Stock
Buffer stock for a new SKU requires a different calculation than safety stock for an established one. Without historical demand standard deviation data, you can't apply the statistical safety stock formulas that work well for your existing catalog. Instead, the buffer sizing for a new SKU launch should be based on:
Replenishment gap coverage: If the product sells through faster than expected and you need to reorder, how long will it take to get more inventory? The buffer should cover at least 75% of that gap period at the base demand rate. If your supplier can turn around a reorder in 35 days and your DTC velocity at the base scenario is 30 units/week, you need at least 22–25 units of buffer to maintain stock continuity through a reorder cycle.
For wholesale channels, buffer sizing is more complex because you may have wholesale buyers requesting reorders at unpredictable intervals. A practical approach: hold a wholesale buffer of one additional minimum order quantity, available for the first buyer reorder request, with a defined release timeline (units held for wholesale reorder for 30 days post-launch; if no reorder request, release to DTC).
What Good Launch Planning Cannot Solve
We're not saying a structured launch planning process eliminates the fundamental risk of a new product. The analogue is always imperfect. The channel split is always a judgment call. Consumer response to a new SKU has genuine randomness that no planning process fully tames.
What structured planning achieves is faster and better recovery from the inevitable gaps. When a new SKU underperforms, a team that documented their analogue selection and demand assumptions can diagnose why much faster than a team that improvised the forecast. When a new SKU dramatically outperforms, a team that pre-negotiated supplier option quantities and defined green signal triggers can respond in days rather than weeks.
The goal of new product inventory planning isn't to be right about the initial order. It's to be positioned to be responsive — to act quickly on what the market is actually telling you, rather than slowly catching up to a demand reality that outpaced or undercut your original plan.
