Peer benchmarking is no longer just about EBIT and margins. Investors and consultants need to see how headcount, sales productivity, and capital efficiency shape performance.
Yet most databases ignore workforce structure, and consultants spend weeks reconstructing it. With only company names and countries, we resolve registry IDs and websites, then deliver EBIT, ROCE decomposition, solvency, headcount growth, sales productivity, and foresight signals — normalized, quartiled, and commented in 72h.
Matches your peers from a client list or sector taxonomy.
Standardizes financials and computes ROCE, margins, and capital employed.
Harmonizes headcount and function mix under a unified taxonomy.
Combines financials, workforce, and strategic signals into one view.
Delivers quartiles, trends, and an explainable comment on performance drivers.
Provides results in hours, not weeks.
This segment is activated with a blend of trusted sources and your own inputs
AI reasoning
User Input
Curated APIs
Web intelligence
A ready-to-use peer pack where each row is one company, aligned on the same fiscal year. You see financial drivers (EBIT, ROCE, capital employed), people data (headcount, function mix, productivity per sales FTE), and web signals (innovation, expansion, M&A mentions). Each row ends with a plain-language comment linking the ratios back to ROCE drivers. Confidence scores are shown field by field.
Headcount-powered peer packs with ROCE decomposition.
Workforce productivity: revenue per employee, turnover per sales FTE.
Peer medians & quartiles with explainable comments.
Exports ready for Sheets/CSV/API and BI.
Your questions on this segment, answered
Your questions on this segment, answered
How can the packs be integrated into workflows (ERP, CRM, BI, consulting models)?
Outputs are workflow-ready in CSV, Sheets, JSON, or via API. They plug seamlessly into ERP, CRM, BI, or financial models for direct use.
How does Starzdata compare to traditional databases like Orbis, Capital IQ, or credit bureaus?
Traditional sources focus on financials but rarely cover workforce or web signals. Starzdata fuses financials, headcount, and strategy signals, adds confidence scoring, and delivers in hours instead of weeks.
How are strategic signals (innovation, expansion, M&A) identified and used?
Structured web intelligence surfaces innovation scores, expansion mentions, and M&A signals. These add context to financial and workforce data, highlighting future positioning.
What makes your ROCE analysis more insightful than a standard margin/asset review?
ROCE is decomposed into margin × asset intensity, making it clear whether performance comes from profitability or capital efficiency. Each line includes a plain-language comment linking ratios to drivers.
How do you calculate and validate productivity metrics like revenue per employee or turnover per sales FTE?
Productivity ratios are derived directly from revenue and headcount, using harmonized function classifications. Outliers are flagged, and each ratio carries a confidence score.
How reliable are the workforce and function mix data?
Workforce metrics are based on structured taxonomies and enriched with official disclosures. AI reasoning harmonizes roles across companies, and confidence scores show source reliability.
How do you ensure financials are comparable across countries and accounting standards?
All financials are normalized to EUR and aligned on the same fiscal year. Differences in accounting scope or standards are flagged and reflected in the confidence scores.
How do you define and select peer groups?
You can provide your own peer list, or use our sector taxonomy to identify relevant comparables. Each company is matched to registry IDs and websites to ensure clean identity resolution.
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