Technova Software📡 Air cargo · Data · Pricing
More signals, less noise: what air cargo data can actually decide
RTS closed its October campaign with a line worth testing: more data only matters when it leads to better decisions. In cargo, the evidence is blunt. More than half of the capacity offered in August 2026 flew unsold, while revenue grew 7.2% on volumes that barely moved. That gap is not an information problem. It is a decision problem, and it has numbers.
01 · The claim
🎯 “More signals, less noise, better decisions”
The post is short and unusually specific for a vendor: RTS combines AI, forecasting and revenue intelligence so cargo teams can identify the signals that matter and act faster. It ends with a promise — that's intelligence built for action — and a hashtag, #CargoQuotient, which is the company's label for the idea rather than a product name.
“More data only matters when it leads to better decisions. RTS combines AI, forecasting and revenue intelligence to help cargo teams identify the signals that matter, and act on them faster.”
Read literally, the claim contains three testable propositions: that cargo teams are data-rich and decision-poor; that forecasting plus pricing plus revenue intelligence can be combined in one workflow; and that acting faster produces a better outcome. The first two are checkable against the market. The third is not, at least not from public sources — and this article is explicit about where the evidence stops.
02 · The gap
📉 Revenue up, volume flat, half the capacity empty
Three IATA figures describe the same problem from different angles. In August 2026, cargo demand grew 4.4% in tonne-kilometres while capacity fell 0.1%, and the load factor reached 46.0% — two points higher than a year earlier, and still below half.
Cargo load factor, August 2026. Source: IATA press release, 29 September 2026. Load factor is weight-based and includes belly capacity.
For 2026 as a whole, IATA projects revenue of USD 162 billion, 7.2% above 2025, on volumes of 71.7 million tonnes — just 0.2% more than the previous year. The divergence is the story: the industry is earning more per kilo, not moving more kilos.
Revenue versus volume growth, 2026 forecast. Source: IATA financial outlook, June 2026, via Air Cargo News.
The pressure behind that divergence is cost. IATA expects the fuel bill to rise from USD 252 billion in 2025 to USD 350 billion in 2026 — roughly 40% more — while industry net profit falls from USD 45 billion to USD 23 billion.
Fuel cost versus industry net profit, USD billion. Source: IATA financial outlook, June 2026.
03 · The noise
🗂️ Five data sources, one decision each
Cargo teams do not lack data. They lack a clean mapping between a data source and the decision it is supposed to improve. This is the audit that most digitalisation programmes skip.
| Source | What it can decide | How it turns into noise |
|---|---|---|
| Air waybill and CASS settlement | Real revenue per shipment, customer and lane | Miscoded commodity or weight breaks; revenue that never reconciles to the invoice |
| Flight and capacity schedule | What can be sold, when, in which configuration | Stale capacity after a gauge change or cancellation |
| Rate sheets and tariffs | The floor and the published price | Versions circulating by email; discounts agreed outside the system |
| Booking and quote log | Conversion, elasticity and response time | Quotes never registered, so the loss is invisible |
| Competitive and market feeds | Position of the rate versus the corridor | Benchmarks that mix lanes, products or incoterms |
The cost of getting this wrong is measurable. Gartner puts the average annual cost of poor data quality at USD 12.9 million per organisation; an IBM analysis published in January 2026 found that more than a quarter of organisations estimate losses above USD 5 million a year for the same reason. Those figures are not cargo-specific — which is precisely the point: cargo adds perishability and a 24-hour decision window on top of the generic problem.
04 · The horizons
⏳ Accuracy means nothing without a horizon
Vendors quote forecast accuracy as if it were a single number. It is not: a model that is excellent for next week can be useless for next quarter, and a budget forecast has different error tolerance than a spot quote.
| Horizon | Decision it feeds | What matters more than accuracy |
|---|---|---|
| 0-7 days | Accept, reject or re-price a specific booking; overbooking level | Freshness of capacity and show-up data |
| 8-12 weeks | Allotments, contract renewals, seasonal capacity | Bias: consistently under- or over-forecasting destroys trust faster than error |
| 12 months | Sales targets, budget, network and fleet decisions | Traceability of assumptions, not decimal precision |
This is where the RTS portfolio splits cleanly. Velocity forecasts capacity, show-up rates and origin-destination demand, and evaluates each booking for profitability. Foresight turns those forecasts into revenue and sales targets per flight, lane and market. AcceleRate converts them into a recommended rate. Three horizons, three products, one data spine — or none of it works.
05 · The comparison
📊 Three ways to price a shipment
Most cargo organisations sit somewhere between three operating models. The table compares them on the dimensions that decide whether pricing survives a bad quarter.
| Dimension | Experience-led | Spreadsheet + BI | RM + pricing engine |
|---|---|---|---|
| Quote speed | Hours to days | Hours | Minutes |
| Consistency | Depends on who answers | Partial: template-dependent | Same logic for every request |
| Coverage | Key accounts only | Reported lanes | Every lane with data |
| Elasticity | Intuition | Monthly averages | Modelled per customer and lane |
| Explainability | Narrative after the fact | Formula visible in cells | Inputs recorded per recommendation |
| Governance | Discounts by relationship | Approval by email | Exception policy and audit trail |
| Cost to run | Low tooling, high variance | Analyst time | Licence plus data engineering |
Comparison built by Technova from the capabilities RTS describes for Velocity, AcceleRate and Foresight. It describes operating models, not measured performance of any named airline.
06 · The hierarchy
🧮 Four inputs, and what happens when one is missing
A pricing recommendation is only as good as the weakest of its inputs. This is the most useful comparison in the whole discussion, because it turns an abstract claim into a diagnostic.
| Input | Question it answers | If it is missing |
|---|---|---|
| Competition | What is the market charging on this lane, with what capacity? | The rate is an opinion; you learn the truth after losing the booking |
| Customer value | What does this account contribute across products and seasons? | You optimise the transaction and damage the relationship |
| Elasticity | How likely is this customer to accept this price? | Win the rate, lose the shipment — or leave money on the table |
| Cost | What does it cost to carry this position? | You sell below the floor and call it market share |
RTS describes AcceleRate as weighting exactly those four dimensions, and producing not just a number but a rate sheet that sales can negotiate and distribute. That last part is the difference between analytics and operations: a recommendation that cannot be quoted, in the format the customer expects, does not exist.
07 · The plumbing
🔌 The data standard changed in January 2026
None of this is only about software vendors. On 1 January 2026, ONE Record became IATA's preferred standard for end-to-end cargo data exchange. The survey behind the rollout is the clearest read on how ready the industry actually is.
Awareness and readiness among cargo industry survey respondents. Source: IATA survey, 10 December 2025. More than 30 pilots were active worldwide at publication.
The gap between 70% awareness and 50% readiness is the practical bottleneck. A pricing engine is only as current as the shipment record it reads, and the electronic air waybill is already the norm: IATA reports that more than two out of three shipments now use an e-AWB. IATA puts the scale of the prize at more than 33% of global trade by value, less than 1% of volume and about USD 8.3 trillion of goods a year — which is why a data error on a single lane can cost more than a month of software.
What ONE Record changes for pricing
| Before | With a shared record | Pricing consequence |
|---|---|---|
| Shipment data re-keyed at each handover | One record, many parties | Fewer mismatches between quoted and flown weight |
| Status by phone or portal | Event-based status | Delays visible before they become penalties |
| Rate agreed by email | Structured rate reference | Contract terms survive the handover |
08 · The measurement
📐 Ten thresholds that tell you if the signal is real
These are working thresholds proposed by Technova, built on the metrics the RTS products expose. They are not vendor targets and not industry benchmarks: they exist so a team can tell in one page whether its pricing data is trustworthy.
| Signal | Threshold to watch | Why it matters |
|---|---|---|
| Forecast bias by lane | Within ±5% | Bias destroys trust faster than random error |
| Capacity data freshness | Under 24 hours | A stale schedule turns every recommendation into a guess |
| AWB data completeness | Above 98% | Missing commodity codes break yield analysis |
| Quote response time (spot) | Under 2 hours | Perishable cargo does not wait for tomorrow's meeting |
| Recommended-rate acceptance | Above 60% | Below that, the model is not being used at all |
| Discounts outside policy | Under 5% of bookings | Measures whether governance exists in practice |
| Quote-to-book by lane | Trend, not absolute | A falling ratio after a price rise signals elasticity error |
| Yield versus corridor benchmark | Within 2 points | Detects lanes priced by inertia |
| Load factor versus route plan | Explained variance | Occupancy without yield is discounted scarcity |
| Documented exceptions | 100% | Undocumented exceptions are where margin disappears |
Thresholds proposed by Technova Software. They are diagnostic defaults, not published performance claims by RTS or by any airline.
09 · The product
🧩 Which signal each module is built to serve
| Module | Signal it consumes | Decision it produces |
|---|---|---|
| Velocity | Capacity, show-up rates, O&D demand, booking profitability | Overbooking level; accept or reject a booking |
| AcceleRate | Competition, customer value, elasticity, cost | Recommended tariff, contract and spot rate; rate sheet |
| Foresight | Forecasts by flight, lane and market | Revenue and sales targets; budget allocation |
| Compass | Network, curfews, slots, range | Schedule and fleet allocation |
The most useful proof that the three-module workflow can run together is still the Saudia Cargo implementation: selected in July 2022, live in March 2024, after two phases covering capacity forecasting, overbooking optimisation, origin-and-destination demand forecasting and allotments, plus dynamic pricing, upsell and cross-sell offers, rating-engine refinement and network optimisation. Oman Air Cargo, LOT Cargo and Air India selected the same core combination afterwards.
10 · The test
✅ Six questions before buying another dashboard
“Intelligence built for action” is a fair ambition and a hard standard. These six questions separate a decision system from a reporting system.
- Which decision does this change? Name the person and the moment, not the department.
- How fresh is the input? If capacity is a day old, the answer is history, not a forecast.
- What is the error by lane and horizon? An average accuracy figure hides the lanes that lose money.
- Can the recommendation be explained to a customer? If not, sales will revert to instinct under pressure.
- Who can override it, and is the override recorded? Undocumented exceptions are the real pricing policy.
- What would make us turn it off? A tool nobody would notice going dark is not part of the operation.
On the current numbers, the case for investing in this layer does not rest on growth. It rests on a 46.0% load factor, a fuel bill rising about 40% and revenue that has to come from price rather than volume. In that arithmetic, the expensive option is continuing to decide by feel.
11 · Sources
📚 Where every figure comes from
- RTS company post on LinkedIn, October 2026: “More signals, less noise, better decisions” (screenshot supplied by the client; quoted verbatim in section 01).
- RTS. AcceleRate for Air Cargo, Velocity, Foresight and Compass: capabilities as declared by the vendor.
- Business Wire. Saudia Cargo goes live, 7 March 2024: two-phase scope; Oman Air Cargo, 1 May 2024; LOT Cargo, 4 September 2025; Air India, 15 September 2025.
- IATA. Air cargo demand grows in August 2026, 29 September 2026: demand +4.4%, capacity −0.1%, load factor 46.0%, Latin America +5.1%.
- IATA financial outlook, June 2026, reported by Air Cargo News: 71.7 million tonnes, USD 162 billion revenue (+7.2%), yields +6.5%, fuel USD 252bn to USD 350bn, net profit USD 45bn to USD 23bn.
- IATA full-year 2025 data reported by Aviation Business News, 2 February 2026: demand +3.4%, capacity +3.7%, yields −1.5%, regional split.
- IATA. ONE Record survey, 10 December 2025: over 70% awareness, nearly 50% readiness, more than 30 active pilots.
- IATA. ONE Record programme page: preferred data-sharing standard from 1 January 2026; e-AWB used for more than two out of three shipments.
- IATA. Cargo programme page: more than 33% of global trade by value, less than 1% by volume, about USD 8.3 trillion a year.
- Gartner. Data quality research: poor data quality costs organisations at least USD 12.9 million a year on average.
- IBM. The true cost of poor data quality, January 2026: more than a quarter of organisations estimate annual losses above USD 5 million.
Disclosure: this advertorial is based on public sources and on a screenshot of an RTS company post supplied by the client. It does not include an interview with RTS. Product capabilities are as published by the vendor and were not verified in operation; the thresholds in section 08 are Technova's proposals, not RTS figures.
📡 Is your data changing any decision?
If the dashboards are full and the pricing table has not moved, the problem is upstream. Let's audit the signal before buying another system.