Research Approach

Methodological transparency, data support, willingness to be challenged

Data limits are stated, not hidden. A first number published and later corrected is preferable to a perfect number never released. This page brings together, in one place, the sources used across all Vespri reports and the limits of each — instead of leaving them scattered in the appendices of individual issues.

§ 01 — Positioning

Where Vespri sits

Four defining traits.

01

Vertical

Vespri segments engineering into operating industries — a methodological choice, not a standard taxonomy — and covers them in depth, rather than spreading coverage across a wider range of topics. A defined scope, read thoroughly.

02

Quantitative

Vespri starts from structural data — employment, financials, skills — and uses geopolitical context to explain it, not the other way around. The reading of events is always anchored to a verifiable number, not just to who has an interest in what.

03

Independent

Vespri operates at independent scale, based in Italy, following the data wherever it leads — Europe, the United States, Asia — without geographic boundaries fixed in advance by organizational structure.

04

Dual-track

Vespri keeps separate two functions that elsewhere tend to intertwine into a single funding source: free editorial on one side, paid advisory on proprietary data on the other. Two distinct tracks, so that one does not steer the other.

§ 02 — Principles

Three editorial rules

01

Verifiable sources

Public statistical and institutional bodies, public company financial statements, job-posting aggregators and recruiting portals with accredited data access — always within each source's terms of use.

02

Stated limits

Every report includes a methodology sheet: what the data captures, what it doesn't, and where a figure should be read as a lower bound, not an absolute value.

§ 03 — The sources

Four sources, four different reliability profiles

Employment

Institutional restructuring monitoring

A public monitoring database on European corporate restructuring: 31,427 events, 2002-2026, 29 countries (EU-27, Norway, United Kingdom). It records the year of announcement, not the year jobs actually disappear — a multi-year plan weighs in full on the announcement year. UK coverage stops after January 31, 2020 (Brexit). Industry classification is heuristic, based on company-name recognition and spot-checked: roughly 90% of all events concern non-engineering industries and are excluded from the analysis.

Finance

Public company financial statement data

81 listed European stocks, multi-industry, 2022-2025 history.

Skills

Accredited job-posting aggregator

A job-posting aggregator with API data access: breadth across multiple industries, four geographic areas, dozens of companies — but only a truncated snippet of the description. Percentages from this source are a lower bound on the real prevalence of each skill, not an exact share.

Skills

Corporate recruiting portals

Direct access to the public endpoints exposed by the recruiting platforms of the companies analyzed: full posting text, but only for the 27 companies — out of 93 total — that expose an accessible endpoint. 5,887 of the 16,386 total postings, averaging 4,199 characters per posting.

§ 04 — Stated limits

What to keep in mind

Limits collected here explicitly

Employment The database covers 29 European countries, not Serbia (where Stellantis has a strategic plant in Kragujevac) nor other non-EU countries. The industry classification is not an official code in the database: it is an attribution by company-name recognition, corrected multiple times over the course of the analysis.
Finance — margins and leverage Automotive leverage is structurally inflated by the captive finance companies (customer financing) present at Volkswagen, Stellantis, BMW and Mercedes-Benz — not comparable at equal operating risk with an industry like Defense. The Energy industry aggregates upstream oil&gas, integrated utilities and a pure renewables player: structurally different businesses, so the aggregated figure is indicative, not a homogeneous average.
Skills — job postings The Country field remains partly unresolved in the full-text data (~90% "Other/N.A."): which is why the analysis is aggregated by industry across all countries together, not split by geography. The classification is heuristic (keyword matching): a starting point to be refined, not an official figure. Academic background, seniority and role function are captured only when the posting states them explicitly — their absence does not mean the requirement doesn't exist. Coverage is not uniform between the two sources (93 companies on the posting aggregator, 27 on full text): the deeper subset is not necessarily representative of the entire industry.

Questions about the data, before citing it

Full methodology available on request for anyone citing a Vespri figure in a report, an internal note or an article.