ASF — Workshop Outputs

What we set out to deliver — and what we produced.
The nine outputs below were the agreed deliverables for today's Story & Strategy Workshop. Each section records what was established, drafted, or agreed in the room, and where it is documented across the site. Some items are fully formed; others are first drafts that need refinement as the SATS proof case develops. That is expected — the commercial model cannot be fully locked until SATS produces real numbers.

Agreed strategic direction and baseline narrative

Agreed

Direction agreed in the room

ASF's role is to measure aviation food waste and convert that measurement into commercial value for caterers and airlines. The business sits at the intersection of data, sustainability, and operational efficiency — but the commercial entry point is the caterer's cost line, not the airline's sustainability agenda.

Baseline narrative — agreed ASF audits flights, captures what was loaded versus what was wasted, and produces data, insights, and a dashboard. The product creates real value. The problem today is it captures none of it. The next 12 months are about proving the equation that lets it start to.

Strategic direction — 4 stages to March 2027

Stage 1 (Now): Build and validate the commercial model using SATS as a live test
Stage 2: Lock the model — the written equation, with real numbers
Stage 3: JST sells — resource secured, pipeline built, AI video as pitch asset
Stage 4 (March 2027): Rename and rebrand — proof case delivered, brand ready to scale

Full roadmap →

Draft proposition, positioning and USP hypotheses

Draft

Core proposition hypothesis

ASF gives airlines and caterers the confidence to make the management call on food waste — backed by independent audit data and an AI-assisted waste model. The proposition is not "we measure waste." It is "we give you enough certainty to act on it."

Positioning hypotheses (to be tested)

Hypothesis A — Confidence

ASF is the confidence layer. Not intelligence, not prediction — but the certainty that lets a GM sign off a 10% load reduction without fearing a passenger complaint.

Hypothesis B — The Independent Standard

ASF is the only independent audit standard for aviation catering waste. Where IATA and ACI have failed to produce one, ASF fills the gap. Accreditation is the long-term moat.

USP — what no one else has

Independent (not owned by a caterer or airline)
Audit-based (not self-reported data)
Flight-level granularity (not depot or route averages)
Commercial link established (waste → cost → saving → ASF fee)

Needs refinement The positioning word — intelligence vs confidence vs accuracy — was debated and left unresolved. This must be settled before the narrative can be finalised.

Audience-specific value propositions, including the caterer story

Documented

The caterer story — the primary commercial vehicle

10% fewer meal loadings × cost per sealed meal = margin saved on wasted meals

Gate question: Is saving > cost of ASF? Yes → caterer commits. If this equation holds at SATS, the commercial model is proven and the caterer story becomes replicable at scale.

The caterer is the primary buyer. They recover margin. They also act as the commercial gateway to airlines — the cost passes through, and the ASF dashboard fee sits on top.

The airline story

Airlines care about load reduction, cost savings, and sustainability credentials. Their gate question is different: 95% data accuracy — enough certainty to make the management call. The airline buys confidence, not data.

Key contacts: In-Flight Services, Catering Operations, Procurement, Sustainability. These are four separate conversations, and they may not be joined up internally.

Trade bodies (channel, not buyers)

ACA — Primary channel for Stage 3 sales. Gateway to caterers at scale. Business critical
IFSA — Active presence. Secondary to ACA. Fans but no direct action yet.
IATA / ACI — Awareness only. Not revenue targets.

Commercial model diagram →

Agreed intelligence language and limits around predictive claims

Agreed

What was agreed

The room debated whether ASF should position as an intelligence business. The honest conclusion: not yet.

Agreed position 49 flights is not enough data to make intelligence claims that a sophisticated buyer — a procurement director or sustainability lead at a major airline — will accept. Intelligence requires volume, breadth, and statistical robustness that ASF does not yet have.

Language rules — agreed in the room

Use: Insight, confidence, accuracy, standardisation, audit data
Use with care: Intelligence — only once data volume supports it (post-SATS, post-scale)
Do not use: Prediction, forecast, AI-generated recommendation — until the AI partner licence is confirmed and the model is validated
The honest claim today: "We give you the data and the framework to make the management call confidently." Not: "We predict what you should load."

The capability ladder — where ASF sits today

ASF is at Level 3: Insight with consulting. Data collected, reporting done, post-audit insight meetings running. The jump to Level 4 (Intelligence) requires more data and the AI partner technology.

Full capability ladder →

Current and missing data map

Documented

What exists

Data collected

49 audited flights. More than any other independent source. Not statistically robust for AI claims, but sufficient to open senior buyer conversations.

Product

Microsoft Power Apps-based audit tool. Functional. Not yet live in a real client environment. First live deployment: SATS, September 2026.

Framework

Audit methodology, accreditation structure, insight meeting format. Clients receive a data report and a second meeting with recommendations.

Commercial relationships

ACA membership active. SATS relationship confirmed at senior level. Grace and Nurses as reference points. Frequent flyer programme insight.

What is missing

AI partner licence — The unnamed partner under NDA holds the AI technology layer. Without it, the POC cannot run as planned. Unconfirmed
Statistical volume — 49 flights is insufficient for intelligence or prediction claims. SATS adds more in September.
Validated AI model — The waste prediction model has never been tested in the wild.
Cross-route breadth — Current data skewed toward specific routes and caterers. Not yet representative.
Financial model with real numbers — The caterer calculation is structured but not yet populated with verified cost data.

Full gaps register →

Claims register and priority proof requirements

Draft

Claims ASF can make today

We have audited 49 flights — more than any independent source
We have an independent methodology — not owned by a caterer or airline
We produce flight-level waste data that airlines and caterers cannot produce themselves
We provide insight and recommendations in a structured post-audit meeting
The caterer equation structurally makes sense — saving > cost of ASF is testable

Claims that require proof before use

"10% load reduction" — This is the hypothesis. SATS is the first real test. Do not state as fact until SATS data confirms it. Pending SATS
"AI-powered" — The AI layer is real but unlicensed. Cannot be used in client-facing materials until partner licence is confirmed. Blocked
"Intelligence" — Requires data volume and model validation. Post-SATS at earliest. Not yet
"Predictive" — Cannot claim predictive capability without the AI model being live and tested. Not yet

Priority proof requirements — in order

SATS POC confirmed by 7 September — binary gate
AI partner licence confirmed — releases the technology claim
SATS data collected — populates the caterer equation with real numbers
Saving > cost of ASF demonstrated — locks the commercial model
Data volume grows to statistical threshold — unlocks intelligence language

Customer-validation questions and recommended conversations

Draft

Caterer validation questions

What is your current cost per sealed meal loaded? (This is the input to the commercial equation)
What percentage of loaded meals are returned uneaten? Do you track this by flight, by route, by class?
If we could demonstrate a 10% reduction in waste loading — what would that be worth to you in margin terms?
Who in your organisation makes the call on loading specifications? Is that the same person who has budget authority?
What would you need to see to make that call with confidence?

Airline validation questions

How do you currently measure catering waste at flight level? What accuracy do you have?
What would 95% data accuracy at flight level change in how you set loading specifications?
What is the relationship between your catering team and your sustainability reporting? Are they joined up?
If the caterer absorbs the cost of ASF and passes it through — what does that change for you commercially?
Who needs to be in the room for a load reduction decision? Who can block it?

Recommended next conversations

Immediate — before 7 September

Matt confirms ASF inclusion in SATS POC. This is the binary gate. Everything else follows from yes or no.

September — post SATS confirmation

First caterer conversation using the structured equation. Bring data from the audit. Ask the margin question directly. Don't lead with AI.

Decision log, unresolved questions and action ownership

Logged

Decisions made in the room

Commercial entry point: Caterer first. Airline second. Airports are network only. Agreed
Language: Confidence and insight now. Intelligence only once data supports it. Agreed
Proof gate: SATS is the primary proof case. The entire roadmap pivots on its outcome. Agreed
Rebrand: Happens after proof case delivered. Target March 2027. Agreed
ACA as primary sales channel: Stage 3 pipeline runs through ACA. Agreed

Unresolved questions

What is the one positioning word? Intelligence / Confidence / Accuracy / Standardisation — not settled
AI partner licence — confirmed or not? No decision date exists
What is ASF's role if the SATS POC proceeds without ASF in it?
How are the three founders' roles divided once the POC runs?
What is the NFP entity in Singapore — and what needs to happen to close it?

Action ownership

Matt — Confirm ASF inclusion in SATS POC by 7 September. Confirm AI partner licence status.
Matt — Close or restructure Singapore NFP entity within 30 days.
Chris / JST — Finalise the written commercial equation by November. Populate with SATS data when available.
All — Agree the positioning word once SATS confirmation is received.

Full gaps and assumptions register →

Outline roadmap for communications, product, data and AI

Drafted

Communications

Now → November: No public claims. Internal alignment only. Develop the written equation.
November: Commercial proposition written — the equation in words. Share with prospective caterers. Use ACA webinar platform.
Post-SATS (Jan–Mar): If hypothesis holds — launch the case study. Begin proactive pipeline with caterers. Deploy AI video as pitch asset.
March 2027: Rebrand and relaunch with proven commercial model at centre.

Product

September: Power Apps tool goes live at SATS. First real-world deployment.
October–November: Refine based on SATS experience. Document the operations process.
January: Product proposition documented and ready to pitch to next caterer.

Data

September–November: SATS data adds to the 49 flights. Assess volume sufficiency.
Ongoing: Every new client adds data. Volume threshold for intelligence claims to be defined with AI partner.

AI

Prerequisite: Partner licence confirmed. No AI roadmap is possible without this.
Post-licence: Integrate AI waste model with audit data. Test predictions against actual SATS loadings.
Post-validation: AI model becomes the dashboard intelligence layer. Claims upgrade from insight to intelligence.

Conditional The AI track is entirely dependent on the partner licence. If licence is not granted, the product roadmap reverts to insight + consulting only, and the commercial model is resized accordingly.

Full strategic roadmap →

Conditional communication and film direction

Conditional

Where clarity exists — what can be made now

The story that holds regardless of the SATS outcome:

Aviation creates food waste at scale. Nobody is measuring it properly. ASF is. And for the first time, airlines and caterers can see their waste profile — and act on it.

Direction for the introductory film

Open: The scale of the problem. Food loaded onto flights around the world — most of it never eaten.
The gap: No one has the data. No one has the standard. Every caterer and airline is guessing.
The turn: ASF audits. Independently. At flight level. And produces the data that changes the conversation.
The proof: SATS — real caterer, real flights, real numbers. The first time the equation has been tested in the wild.
The ask: If the saving is greater than the cost of ASF — what's stopping you?

What cannot be made yet

Any film that claims prediction or AI capability — blocked until licence confirmed
Any caterer case study film — needs SATS data first
Any rebrand assets — held until March 2027 or when proof case lands

Cleared to produce Introductory brand film using the problem/gap/turn structure above. No predictive claims. No AI language. Confidence and insight only.