Strong velocity, thin distribution
It sells wherever it lands. The problem is that it has not landed in enough places.
A distribution problem
Expand authorization, chase the voids, unblock the pipeline.
New Item Launch Performance
Is it on the shelf, or is it just not selling?
A governed workflow that turns shipment, POS, authorization, planogram and campaign feeds into ranked launch interventions — routed to account, marketing and supply-chain teams while the launch window is still open.
What the workflow runs on
Feeds you already have
ShipmentPOSAuthorizationPlanogramCampaign
Governed decision logic
One grainBenchmark curveFour-tier bandingConfidence
What reaches the team
Ranked voidsOwnerDollar size
The challenge
Four signals, four systems, one blind spot
Every launch is a sizable bet — slotting, trade, marketing and supply-chain capacity all committed before a single unit sells — and the retailer decides keep-or-cut inside the first three months. When one lags, the question is whether it is a distribution gap or a demand problem. On a report the two look identical. In practice they have completely different fixes, and the signals that would separate them sit in disconnected systems.
No common scoreboard
Each retailer is tracked in its own portal, on its own feed, in its own format, on its own schedule. Assembling one view is manual, so it happens late or not at all.
Three different things, counted as one
Authorized, on shelf and actually selling get conflated. The gaps between them are exactly where launches are lost, and they are never measured.
Benchmarked against nothing
Shelf-delay lag and per-store velocity have no reference curve to sit against, so a slow launch looks indistinguishable from a normal ramp until the window has closed.
Spend landing ahead of the shelf
Marketing weight arrives in markets where the item is not yet stocked, and sales cannibalized from your own existing items get counted as launch wins.
The result is familiar: the brand assembles the real picture only after the retailer’s keep-or-cut call has already been made.
The leadership question
One question, asked in every review
“Can we see, while there is still time to act, whether every new item is actually on the shelf and selling — and then put the right dollars behind the right fix?”
The split
A distribution gap or a demand problem?
They are not the same failure and they do not have the same fix. Separating them while the window is still open is the whole point of the workflow — and it is what indexing velocity against a comparable-item launch curve makes possible.
Full distribution, weak velocity
It is on the shelf almost everywhere and still not moving.
A demand problem
Rework the offer, the price, the pack or the placement.
How the two axes resolve
Distribution against velocity
This is the same four-tier banding the worklist applies, drawn as the two questions it actually asks. Every item, store and retailer combination lands in one of these corners, and each corner maps to exactly one action.
Velocity vs. benchmark →
Thin distribution · Above the curveExpand distribution
It sells wherever it lands. Widen the footprint.
Full distribution · Above the curveScale
Working and under-resourced. Put more behind it.
Thin distribution · Below the curveFix execution
Authorized and not selling through. Chase the void.
Full distribution · Below the curveReassess
Supported, stocked, still flat. A demand answer.
Distribution →
What is included
Six capabilities, six deliverables
Each one is a packaged capability — the data model, the scoring logic and the deliverable already designed around the decision it serves. They are built to run together, but each produces an artefact that stands on its own.
01
Distribution Void Worklist
Speed-to-Shelf & Void Detection
Reconciles the pipeline across shipment, DC receipt, store receipt and first scan, computing days-to-shelf per store and per DC. It flags distribution voids and phantom inventory wherever authorization, DC stock and store scans disagree — recovering the authorized-but-unsold stores that quietly drag measured sales down and make a healthy item look like a failure.
02
Velocity Index vs. Benchmark
Penetration & Velocity Indexing
Indexes velocity per selling store against a comparable-item launch curve at the equivalent launch week, alongside selling-store percentage and ACV-weighted distribution. This is the layer that splits the two failure modes: measured against the right curve, a distribution gap and a demand problem stop looking alike.
03
Net Incremental Growth Read
Incrementality Decomposition
Decomposes gross launch contribution into net incremental category growth and cannibalization of your own existing items, using substitution clusters built from historical co-purchase patterns and category baselines. The result is an incremental figure that survives buyer scrutiny in the line review rather than collapsing under it.
04
Segment Performance Breakdown
Segment, Adjacency & Geo Analysis
Breaks performance down across retailer, region, store format and urban / suburban / rural type, estimates planogram-adjacency effects from placement differences, and aligns marketing exposure to distribution by geography — surfacing both where campaign weight landed ahead of the shelf and where strong distribution went completely unsupported.
05
Launch Intervention Brief
Opportunity Scoring & Banding
Scores every item / retailer / store combination into a four-tier band, each mapped to one specific action, and routes a structured brief into the next line-review conversation — pairing every underperformer with an analog success so the ask is evidenced rather than asserted.
06
Distribution & Velocity Forecast
Launch Forecasting & Tracking
Produces an expected distribution build curve and a velocity benchmark with a confidence interval for every authorized launch — sizing allocation up front and serving as the on-track reference the live launch is measured against. Versioned and stored, so post-launch accuracy traces back to the model that produced it.
The artefacts
What actually arrives, and who it arrives for
Six named deliverables rather than access to a tool. Each is versioned, traceable to the model that produced it, and routed to the team that acts on it.
Deliverable 01 · Speed-to-Shelf & Void DetectionDistribution Void Worklist
Reconciles the pipeline across shipment, DC receipt, store receipt and first scan, computing days-to-shelf per store and per DC.
Deliverable 02 · Penetration & Velocity IndexingVelocity Index vs. Benchmark
Indexes velocity per selling store against a comparable-item launch curve at the equivalent launch week, alongside selling-store percentage and ACV-weighted distribution.
Deliverable 03 · Incrementality DecompositionNet Incremental Growth Read
Decomposes gross launch contribution into net incremental category growth and cannibalization of your own existing items, using substitution clusters built from historical co-purchase patterns and category baselines.
Deliverable 04 · Segment, Adjacency & Geo AnalysisSegment Performance Breakdown
Breaks performance down across retailer, region, store format and urban / suburban / rural type, estimates planogram-adjacency effects from placement differences, and aligns marketing exposure to distribution by geography — surfacing both where campaign weight landed ahead of the shelf and where strong distribution went completely unsupported.
Deliverable 05 · Opportunity Scoring & BandingLaunch Intervention Brief
Scores every item / retailer / store combination into a four-tier band, each mapped to one specific action, and routes a structured brief into the next line-review conversation — pairing every underperformer with an analog success so the ask is evidenced rather than asserted.
Deliverable 06 · Launch Forecasting & TrackingDistribution & Velocity Forecast
Produces an expected distribution build curve and a velocity benchmark with a confidence interval for every authorized launch — sizing allocation up front and serving as the on-track reference the live launch is measured against.
Previews are schematic. They carry no figures, because the numbers on them would be ours rather than yours.
The output
Every launch lands in one of four bands
Scoring is not a number for its own sake. Each band maps to one action and one owner, so the worklist arrives already sequenced by addressable dollars rather than by whoever shouted loudest.
TIER 1Scale
Above the curve and widely stocked. It is working and under-resourced — put more behind it.
TIER 2Expand distribution
Above the curve where it is stocked, but thin on the ground. Widen the footprint.
TIER 3Fix execution
Authorized and not selling through. Chase the void before the keep-or-cut call.
TIER 4Reassess
Distributed, supported, and still below the curve. This is a demand answer, not a supply one.
The workflow
From the plant to the shelf
Days-to-shelf is computed per store and per DC across every one of them. A distribution void is simply a checkpoint that never fired — and phantom inventory is two checkpoints that disagree with each other.
1
ShippedUnits leave the plant against an authorized item
2
DC receiptBooked into the retailer’s distribution centre
3
Store receiptAllocated and received at the store
4
First scanThe only hard proof it reached the shelf
5
VelocityIndexed against a comparable-item launch curve
6
ActionBanded, sized in dollars and routed to an owner
Authorization, DC stock and store scans are reconciled against one another rather than trusted individually. Where they disagree, that disagreement is the finding.
What changes
Four things that stop being true
The workflow does not add another report. It replaces four sentences that get said in every review with something specific enough to act on.
“We’ll know after the line review.”
The read arrives while the window is still open, not after the keep-or-cut call.
“It’s underperforming.”
It is a void in a named set of stores and DCs, sized in dollars, with an owner.
“The launch grew the category.”
Growth is stated net of cannibalization of your own items, and survives scrutiny.
“Marketing supported the launch.”
Exposure is aligned to distribution by geography, so weight ahead of the shelf is visible.
Who it is for
One workflow, four seats
The same governed output, presented for the decision each team actually makes. Nobody is asked to interpret somebody else’s view.
Brand & Category Managers
A single command centre — distribution build, velocity index and a tiered void worklist sequenced by addressable dollars — to act while the launch window is still open.
Customer Business Managers
Independent, store-level evidence and one specific ask for every line review, each underperformer paired with an analog success from the same portfolio.
Sales & Supply-Chain Leaders
Portfolio KPIs in business terms — launch success rate, time to distribution, incremental growth and forecast accuracy — tying outcomes back to execution and spend.
Account & Category Teams
Item-store scorecards carrying speed-to-shelf, velocity-to-benchmark, adjacency and geo alignment — the root-cause detail that localizes a slow launch to the exact DCs.
How it is governed
What makes it repeatable
Anyone can produce this read once. What makes it a capability is that the grain, the logic and the model version are fixed and stored, so the next cycle is measured the same way as the last one.
Grain
Item × retailer × store × week. Every deliverable resolves to it, so two teams reading different reports are reading the same number.
Benchmark
A comparable-item launch curve at the equivalent launch week — not a year-ago comparison, which a first-year item does not have.
Confidence
The forecast carries an interval, and every banded action carries a confidence rating. A thin read is labelled as one rather than presented as certainty.
Versioning
Forecasts are versioned and stored, so post-launch accuracy traces back to the model that produced it and the benchmark improves each cycle.
Start with one launch.
Bring a single item and a single retailer. We’ll run the speed-to-shelf and velocity read against it and show you the void worklist it produces — before you commit to anything wider.