Sena counts what the category absorbed in each market, so an internal ratio gains a denominator drawn from outside the company.
Supply chain analytics turns operational records into a picture a team can act on. Three patterns keep that picture pointed inward.
Orders, shipments, warehouse movements, and service level exports all describe the same company. An analysis built from them can measure consistency with great precision and stay silent on whether the result was good.
Dashboards report what happened at a level of detail the underlying data supports. Why a figure moved calls for evidence the operational record has yet to hold.
External comparison arrives as an industry figure, aggregated, lagged, and averaged across companies of different shapes.
Sena is the decision AI with access to real-world data. It counts what consumers across a market purchased and records what each outlet held on the day, so an internal figure gains an external denominator.
Sena counts purchases across every player in the category, so own movement reads against what the market absorbed over the same weeks.
Captures record what each outlet held, and buyers state where they moved, so a fall arrives with an explanation attached.
Recorded purchase carries its own date, so the external comparison sits in the same period as the decision.
An analysis is worth what its inputs are worth. Operational records describe the company precisely, and the questions teams bring usually concern the market that company sits inside.
Supply chain analytics applies measurement to the flow of goods: what moved, how fast, at what cost, and at what service level. The discipline is mature on the internal half and thin on the external half, because internal records are complete and free, while market records are partial and expensive.
Descriptive is well served by existing systems. Diagnostic calls for evidence outside the operational record, which is where most implementations thin out. Predictive projects the series forward, inheriting whatever the series measures. Prescriptive recommends an action and carries every assumption underneath it.
Six figures cover most supply chain scorecards, and every one of them is a ratio computed from internal records.
| Metric | What it measures | What it leaves open |
|---|---|---|
| Fill rate | Orders met from available stock. | Whether unmet demand existed at the outlet. |
| On time in full | Delivery against commitment. | Whether the buyer found the product afterward. |
| Forecast accuracy | The projection against actual shipments. | Whether shipments described demand. |
| Inventory turns | How fast stock cycles. | Whether the market moved faster. |
| Cash to cash | Working capital tied up. | Whether the cover sits in the right markets. |
| Perfect order rate | Orders complete and undamaged. | Whether the outlet held the line that week. |
Four collected inputs supply the market side, market by market.
| Input | What it answers |
|---|---|
| Receipts | What buyers purchased across the category and when, which supplies the denominator. |
| Store captures | What each outlet held on the day, which explains a movement figure. |
| Geo-verified photos | The outlet as it stood when captured, with the place and the day recorded. |
| Stated preference | Where buyers moved and why, which turns a diagnostic question into an answer. |
Four conditions decide whether an external comparison is worth quoting.
A category average across countries answers a different question from the market on the table.
A comparison dated a year back describes conditions the decision has already left.
A market figure absorbs formats and outlet types moving apart underneath it.
A benchmark that arrives as a single number, with the method described and the input withheld, settles arguments by authority.
Real people share what they buy and prefer, under explicit consent. Sena captures it directly at the source, so every figure traces back to where it came from whenever a number comes under question.
Consented purchase supplies the denominator, and every capture carries the market and the day it was taken.
Own movement reads against what the category absorbed in the same market and the same weeks.
Captures and stated reasons arrive with the figure, so the why sits beside the what.
Any market figure opens to the recorded purchases and outlet photographs that produced it.
An analysis carries weight only as far as its inputs. Sena builds every figure from real-world signals captured when the question needs it, from consumers purchasing across the category through to the dated capture a scorecard review opens.
Counts what buyers purchased across the category and when, including purchases made from every other player, so a ratio gains a market denominator.
Reads what each outlet held off images captured in real outlets, which turns a movement figure into an explained one.
Signal arrives from the consumer network under explicit consent. Where buyers went, and why, comes from those buyers.
Service level exports, shipment history, and warehouse records join over 250+ integrations, so the internal scorecard reads beside the market.
Every figure holds its market and its capture date, so a benchmark reopens on the transactions underneath it.
Historic scorecards, comparisons, and movement exports load in, so each measured period sits alongside the rest.
Four teams quote the same scorecard, and each one needs a different cut of it before they can act.
The scorecard. Needs a market denominator dated to the same period.
The projection review. Needs the miss traced to real purchases.
The market story. Needs its own movement set against the category.
The comparison. Needs a benchmark that opens to its input.
The same market denominator, read against whatever each industry counts as movement.
Own movement against category movement, per format, price tier, and outlet type.
Category movement by specification and price band, set against own volume.
Pack size movement at the counter, against what the category absorbed.
Movement between operators and tariffs, period against period.
One mechanism, applied per market and per category. Each step is documented, which is what makes a benchmark quotable.
Real contributors share what they buy and pay under explicit consent and record what each outlet held in the markets named.
Sena builds a dated series of category movement per market and format, with availability alongside it.
Own volume reads against that series over the same weeks, with the records attached.
Most supply chain analytics runs on records the company already holds, which describe the company precisely and the market thinly. Sena supplies the half that sits beyond it.
| Capability area | Typical setup | Sena |
|---|---|---|
| The dataset | Orders, shipments, and warehouse records. | Category purchase from every player selling into that market. |
| The denominator | Own prior period. | What the market absorbed over the same weeks. |
| Diagnosis | Inferred from the operational record. | Availability captured on the day, with reasons stated by buyers. |
| Benchmark currency | An industry comparison, aggregated and lagged. | Recorded purchase dated to the cycle in question. |
| Benchmark level | A category average across countries. | The named market, format, and outlet type. |
| Unmet demand | Absent from the record. | Counted, with the weeks a line ran absent attached. |
| Auditing a figure | A method appendix. | Click the figure, and the records open beneath it. |
Three situations where an external denominator changes what a scorecard says.
Set a service figure against what the category absorbed, so a steady ratio and a shrinking share separate.
Open the period to availability captures and stated reasons, so the diagnosis rests on evidence.
Compare against category movement dated to the same weeks in the market under review.
A measured market settles what the scorecard means. The four decisions below are what a supply chain team runs around it.
Every supply chain decision Sena answers, in one place
Where the records come from
Records what each outlet held, which supplies the evidence an analysis reads.
Explore supply chain visibility 02Turning numbers into answers
Turns a scorecard figure into an answer with its record.
Explore supply chain intelligence 03Acting on the comparison
Turns a demand series into what to hold for the period ahead.
Explore demand planning 04Where the analysis leads
Turns the measured market into route, cover, and service level.
Explore supply chain optimizationThe walkthrough builds a dated series of category movement for one market, sets own volume against it, and opens the transactions behind any figure while the team watches.
Name the category and the market on the scorecard, and we will supply the denominator.