Every figure this model derived for SLB, the value it took, and
the element in the company's own XBRL it was read from — so any of it can be checked
against the filing rather than taken on trust.
As at 2026-06-30.
The figures, and where each came from
This is the part no other screener shows. Each figure below names the XBRL element it
was read from, so it can be checked against the filing itself.
The figures themselves rather than their scores — what somebody looking up
SLB on one particular measure came for.
Ratio
Value
current ratio
1.44
current ratio reported
1.44
deferred revenue growth
-30.88
dilution pct
0.07
ev owner earnings
19.78
ev sales
2.43
fcf margin
13.22
growth cv
1.12
owner earnings margin
12.27
revenue growth
2.5
revenue growth per share
2.43
sbc pct revenue
0.94
What to be careful about
What this model itself distrusts about SLB's figures. Written by the
derivation as it ran, not added afterwards.
operating income last tagged 2024-03-31, 821 days before the revenue period (2026-06-30); dropped rather than divided by current revenue
presents no operating result, and rebuilding it from the statement missed the reported pre-tax profit by 79.08% of revenue, so it is refused rather than used (no value anywhere for CostOfGoodsAndServicesSold)
no forward EPS estimate; growth rests on filings only. Analyst consensus is not published in XBRL, so it has to be fetched from a data provider or set by hand in overrides.yaml as `eps_growth_2y`
quality DROPPED from the total: only 2 of 5 inputs could be computed (operating margin, roic, cash operating margin not tagged), so the score is not meaningful. Its weight is spread over the other dimensions
valuation rests on 1 of 2 inputs; not tagged: ev ebit
durability DROPPED from the total: only 2 of 4 inputs could be computed (contracted coverage, gross margin stability not tagged), so the score is not meaningful. Its weight is spread over the other dimensions
resilience rests on 2 of 3 inputs; not tagged: interest cover
growth DROPPED from the total: only 2 of 4 inputs could be computed (margin trend, margin recent not tagged), so the score is not meaningful. Its weight is spread over the other dimensions
3 of 5 dimensions could not be measured (quality, durability, growth -- 60% of the model), so this row is not comparable with the others; its total rests on what was left