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Fuel Impact Forecast — Methodology

Companion to: fuel-impact-2026-06-01.html Generated: 2026-06-01 by build_report.py (fuel-impact-report skill, MC-3483) Purpose: step-by-step record of every input value used — verify the math from this doc alone.

1. Data Sources

# Source File Last read
1 IATA Jet Fuel Price Monitor ~/Dropbox/Safair/Reporting Data/Data Fuel.xlsx 2026-06-01
2 B4i Fuel Feedback (Bernd Feucht) ~/PKA/SecondBrain/wiki/concepts/Fuel-Prices-B4i.md embedded as base64 in HTML
3 Radixx route surcharge ~/PKA/SecondBrain/wiki/concepts/fuel-surcharge-data/surcharge_history.json embedded as pivot JSON in HTML
4 FinDash kpi_data ~/PKA/Projects/findash/data/kpi_data.json 2026-06-01
5 May MTD dashboard ~/Dropbox/Safair/Reporting Data/dashboard/dashboard_data.json 2026-06-01

2. Schedule Constants (only non-actuals in CONSTANTS)

Parameter Value Basis As-of
MAY_FLIGHTS 4,929 flights May 2026 ACTUAL flown 2026-06-01
MAY_SEATS 931,362 seats May 2026 ACTUAL capacity 2026-06-01
JUNE_FLIGHTS 5,059 flights kpi_data.json 2026 months[5] 2026-06-01
JUNE_SEATS 956,151 seats kpi_data.json 2026 months[5] 2026-06-01

2026-06-01 note: MAY_FLIGHTS/MAY_SEATS updated to ACTUAL (commercial/Radixx). JUNE_FLIGHTS/JUNE_SEATS added from kpi_data.json schedule.

MC-3517 note: March + April estimate constants removed. All cost fields now read directly from kpi_data.json actuals (fuel_r, fuel_uplift, avg_fuel_per_liter_uplifted, total_costs, pbt_r). NON_FUEL_PER_FLIGHT derived at runtime from April actuals: (total_costs − fuel_r) / flights.

3. Mar Actuals (kpi_data.json, year 2026, months[2])

Metric Value kpi_data key
Flights 5,640 flights
Pax 952,399 pax
Seats 1,062,072 seats
Load Factor 89.7% load_factor
Yield R1,329 yield
Revenue R1,233.5M revenue_r
Fuel uplift 28.613M L fuel_uplift — ACTUAL
Fuel R/L delivered R14.62 avg_fuel_per_liter_uplifted — ACTUAL
Fuel cost R418.4M fuel_r — ACTUAL
Non-fuel cost R717.8M = total_costs − fuel_r derived
— Direct (ex-fuel) R388.1M = total_direct_costs − fuel_r kpi_data
— Overheads R329.7M = total_overheads kpi_data
Total costs R1,136.3M total_costs — ACTUAL
PBT R127.4M pbt_r — ACTUAL
Reconciliation check revenue − fuel − non_fuel = R97.2M vs pbt_r R127.4M gap R30.22M

4. Apr Actuals (kpi_data.json, year 2026, months[3])

Metric Value kpi_data key
Flights 5,307 flights
Pax 861,063 pax
Seats 999,135 seats
Load Factor 86.2% load_factor
Yield R1,628 yield
Revenue R1,427.2M revenue_r — ACTUAL
Fuel uplift 26.637M L fuel_uplift — ACTUAL
Fuel R/L delivered R26.52 avg_fuel_per_liter_uplifted — ACTUAL
Fuel cost R706.5M fuel_r — ACTUAL
Non-fuel cost R683.5M = total_costs − fuel_r derived
— Direct (ex-fuel) R360.2M = total_direct_costs − fuel_r kpi_data
— Overheads R323.3M = total_overheads kpi_data
Total costs R1,390.1M total_costs — ACTUAL
PBT R43.7M pbt_r — ACTUAL
Reconciliation check revenue − fuel − non_fuel = R37.2M vs pbt_r R43.7M gap R6.54M
Non-fuel/flight R128,797 April reference; May uses direct per-flight + overheads flat (Mar–Apr avg)
L/flight 5,019 apr fuel_uplift / apr flights — used for May

5. Recovery Analysis

Lens Result
Per-pax yield recovery R299 ÷ R381 = 78%
Per-flight rev recovery R50K ÷ R59K = 85%
Network revenue ÷ fuel hike R194M ÷ R288M = 67%
Total absorption (rev + nonfuel saving) ÷ fuel hike R228M ÷ R288M = 79%

May (projection) column. The Recovery + comparison tables in the HTML report carry a third May (proj) column = the headline Base-case projection (rev R1,184.0M · fuel R594.3M @ R24.02/L · PBT −R68.1M). It is a projection, not a closed month, and is excluded from the recovery ratios above: those measure absorption of the March→April fuel hike, whereas April→May fuel falls (smaller, lower-volume month + B4i easing) — there is no hike to absorb into May.

6. May (Actual Revenue) & June Forecast

6a. May Fuel R/L Derivation Chain (MC-3517)

Step 1 — April actual delivered R/L anchor:

Apr fuel_r = R706.54M  (kpi_data fuel_r)
Apr fuel_uplift = 26.637M L  (kpi_data fuel_uplift)
Apr actual R/L = 706.54M ÷ 26.637M = R26.5200/L

Step 2 — May fuel R/L derivation (M2 priority chain):

Priority 1 (preferred): May MTD actual avg_fuel_per_liter_uplifted from kpi_data.json
  → Used when present: NOT AVAILABLE — fell through to IATA estimate
Priority 2: Apr actual R/L × (IATA×FX latest) / (IATA×FX Apr)
Priority 3: Apr actual R/L × IATA ratio only (FX unavailable)
Priority 4: Apr actual × 0.97 (IATA unavailable; B4i-corroborated 3% ease)

Actual source used: Apr actual R26.52 × IATA ratio (159.85/167.96=0.9517). USD/ZAR not available — excluded from scaling. CAVEAT: monthly contracts lag IATA weekly spot.

April IATA $/bbl reference = 167.96
Latest IATA $/bbl = $159.85  (May 22, Data Fuel.xlsx)
May base R/L result = R25.2400

CAVEAT (M2): IATA-scaled estimates assume supplier contracts track IATA weekly spot. Monthly contracts lag IATA weekly; April delivered R26.52 rose while IATA fell in that period. A Rand move can flip the sign of the implied R/L change. This estimate is directional. Superseded by May MTD actual delivered R/L (priority 1) when kpi_data.json is updated.

Step 3 — B4i corroboration (direction check): May B4i tariff data shows broad decreases: Astron −332cpl, Shell −215cpl, PetroSA −171cpl, Engen −222cpl. This corroborates the downward IATA direction. Base R/L of R25.24 is anchored to actual April R26.52 minus documented easing.

Step 4 — Scenario band: Opt = base − R1.50 = R23.74 Base = R25.24 Pess = base + R2.00 = R27.24

6b. May MTD Signals

Metric Value Source
Period N/A dashboard_data.json
Flights N/A dashboard_data.json
Pax N/A dashboard_data.json
Revenue N/A dashboard_data.json
Yield N/A dashboard_data.json
LF N/A dashboard_data.json

6b-ii. Base Full-Month LF Projection Chain (MC-3517 follow-on)

May MTD LF is a partial-month observation (~14 days). Bookings continue to mature. The full-month projection uses April actual full-month LF as the maturity proxy.

May MTD LF        = N/A  (from dashboard_data.json kpis_mtd — partial, ~14 days)
April actual LF   = 86.2%  (from kpi_data.json months[3] load_factor — ACTUAL full month close)
Projection method = MTD 80.2% @14d → full-month 86.2% using April actual full-month close
                    as maturity proxy; assumes April-like booking maturation
Flag              = if May booking pace differs materially from April, this proxy
                    will over- or under-state full-month LF

Base — MTD actual vs full-month projected:

Variant LF Revenue Fuel Non-fuel PBT Margin
[live MTD] 82.0% R1,207M R624M R661M −R79M -6.5%

6c. Schedule + Cost Inputs

Parameter Value Basis
Flights 4,929 May schedule
Seats 931,362 May schedule
L/flight 5,019 Apr actual fuel_uplift ÷ Apr flights
Non-fuel/flight R128,797 Apr actual (total_costs−fuel_r)÷flights
Non-fuel total R661M direct (ex-fuel) per-flight + overheads flat (Mar–Apr avg)

6d. Three Scenarios (+ Base dual-line)

Scenario Fuel R/L Yield LF Revenue Fuel Non-fuel PBT Margin
Optimistic R23.74 R1,627 84.0% R1,273M R587M R661M R24M 1.9%
Base case [live MTD] R25.24 R1,580 82.0% R1,207M R624M R661M −R79M -6.5%
Pessimistic R27.24 R1,533 80.0% R1,142M R674M R661M −R193M -16.9%

6e. May ACTUAL Revenue Block (2026-06-01)

Revenue is ACTUAL from commercial/Radixx dashboard (forward/monthly, May 2026). Label: 'ACTUAL (commercial/Radixx — X3 close supersedes)'. Only fuel R/L varies across scenarios (revenue is locked).

Input Value Source
Revenue R1,184.0M ACTUAL — commercial/Radixx
Flights 4,929 ACTUAL flown
Capacity 931,362 seats ACTUAL
Pax 762,490 ACTUAL
LF 81.9% ACTUAL (762,490 / 931,362)
Yield R1,552.84 ACTUAL
Fuel volume 24.74M L 4,929 flights × 5,019 L/flight (April basis)
Non-fuel R657.9M R67,872.42/flight × 4,929 + R323,331,269.87 overheads

May PBT oracle (spec ±R0.5M):

Scenario Fuel R/L Fuel PBT Margin
May Optimistic (actual rev) R23.02 R569.5M −R43.4M -3.7%
May Base — central (actual rev) R24.02 R594.3M −R68.1M -5.8%
May Pessimistic (actual rev) R25.02 R619.0M −R92.8M -7.8%
Stress test — April fuel held flat (<10% tail) R26.52 R656.1M −R129.9M -11.0%

6f. June Forecast Block (2026-06-01)

Schedule from kpi_data.json 2026 months[5]: flights=5,059, seats=956,151. Forward day-1 corroboration: R455.5M booked, 47% of prior-yr revenue; prior June R968.6M / LF 86.13% / pax 842,001. Revenue: YoY-softened prior June LF 86.13% by −4.6pp to 81.5% base. Costs: April basis (R67,872.42/flight direct ex-fuel + R323,331,269.87 flat overheads). Fuel: April L/flight 5,019 × 5,059 flights = 25.39M L. Fuel R/L: one further month easing vs May (−R3.50 vs April): opt 22.02 / base 23.02 / pess 24.02 / floor 26.52.

Input Value Source
Flights 5,059 kpi_data.json 2026 months[5]
Seats 956,151 kpi_data.json 2026 months[5]
Fuel volume 25.39M L 5,019 L/flight × 5,059 flights
Non-fuel R666.7M R67,872.42/flight × 5,059 + R323,331,269.87 overheads

June PBT oracle (spec ±R0.5M):

Scenario LF Yield Fuel R/L Revenue Fuel Non-fuel PBT Margin
June Optimistic (forecast) 81.5% R1,520 R22.02 R1,184.0M R559.1M R666.7M −R41.8M -3.5%
June Base case — central (forecast) 77.2% R1,492 R23.02 R1,100.0M R584.5M R666.7M −R151.2M -13.7%
June Pessimistic (forecast) 71.5% R1,489 R24.02 R1,020.0M R609.9M R666.7M −R256.6M -25.2%
Stress test — April fuel held flat (<10% tail) (floor) 77.2% R1,492 R26.52 R1,100.0M R673.4M R666.7M −R240.1M -21.8%

7. Reconciliation Assertions (A4 dual-gate)

Assertion: (revenue − total_costs) ≈ pbt_r. Gap = non-operating IS items (finance costs, tax, other income) not captured in total_costs. Warn gate: max(R15M, 1% revenue) — amber NOTE in report. Fail gate: R50M — red WARNING block in report.

Month rev − costs pbt_r Gap other_is Warn gate Status
Mar R97.2M R127.4M R30.2M R30.2M R15.0M WARN
Apr R37.2M R43.7M R6.5M R6.5M R15.0M PASS
May (proj) −R68.1M −R68.1M — — — proj — operating only (rev−costs≡PBT; no non-op IS projected)

7b. IS-Bridge Waterfall (A4 — sums exactly to fuel hike)

Identity: revenue_Δ − fuel_hike + nonfuel_saving + other_IS_movement = −pbt_drop

Revenue increase:     +R193.7M
Fuel hike:            −R288.1M
Non-fuel saving:      +R34.3M
Other IS movement:    −R23.7M  (apr_other_is=R6.5M, mar_other_is=R30.2M)
PBT drop:             −R83.7M
Bridge check:         R288.1M ≈ R288.1M

7c. Year-on-Year + Calendar YTD (closed actuals only)

All figures are closed-month ACTUALS from kpi_data.json (fuel_r, fuel_uplift, pbt_r, revenue_r, pax, flights, avg_fuel_per_liter_uplifted). No estimates, no MTD month. CY (2026) and LY (2025) summed over the SAME closed months for a like-for-like view.

YTD window: Jan–Apr (Jan, Feb, Mar, Apr) — no months excluded

Headline impact (the two side-by-side numbers):

YTD extra fuel spend vs 2025 = Σ fuel_r 2026 − Σ fuel_r 2025
                            = R1,726.5M − R1,339.8M = +R386.7M
YTD PBT delta vs 2025       = Σ pbt_r 2026 − Σ pbt_r 2025
                            = R256.1M − R532.6M = −R276.5M
Fuel hike absorbed (not in PBT) = extra fuel + pbt delta = R110.2M

YTD table (Jan–Apr):

Metric 2026 2025 Δ
Fuel cost R1,726.5M R1,339.8M +28.9%
Fuel volume 107.4M L 101.8M L +5.4%
Blended R/L R16.08 R13.16 +22.2%
Revenue R4,633.4M R4,394.9M +5.4%
PBT R256.1M R532.6M −51.9%

Apr 2026 vs Apr 2025 (actuals month YoY):

Metric Apr 2026 Apr 2025 Δ
Fuel cost R706.5M R347.3M +103.4%
Fuel R/L R26.52 R12.66 +109.5%
Revenue R1,427.2M R1,275.2M +11.9%
PBT R43.7M R255.0M −82.9%

8. Caveats

Generated 2026-06-01 · build_report.py · MC-3483/MC-3517/fuel-impact-jun2026