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The COCOO-Eurostat Doctrine: A Strategic Model for Macroeconomic Warfare

This doctrine establishes the protocol for interrogating the Eurostat Structural Business Statistics (SBS) database. This is not a simple data portal; it is a macroeconomic weapon. We will use this platform to move beyond single-company analysis and operate on the level of entire industries and national economies. Our mission is to use this official, harmonized data to build unimpeachable, evidence-based narratives of systemic market failure, identify sectors ripe for consolidation or disruption, benchmark our targets against their entire peer group, and find the statistical proof of harm needed to launch our most ambitious FOC DAM and USP campaigns. This platform is the engine for our Benchmarking, Porter analysis, and SIMPLEINDICATORS strategies.[1, 1, 1]

1. Core Principles of Interrogation

Our use of Eurostat is governed by the most strategic principles of the COCOO framework. We are not looking at statistics; we are looking for the pressure points in the European economy.

  • The Unimpeachable Benchmark: Eurostat data is the gold standard for cross-country comparison. When we claim a company or an industry is underperforming, we will use Eurostat data to benchmark it against its EU peers. This transforms our arguments from opinion into statistical fact, providing the hard evidence needed for Benchmarking and Porter analysis.[1, 1]
  • The Noisefilter for Systemic Trends: While other platforms show us individual corporate actions, Eurostat shows us the tide. It is the ultimate Noisefilter, allowing us to see if a problem reported by one company is an isolated incident or a systemic, sector-wide crisis affecting thousands of firms. A decline in profitability across an entire NACE code is not noise; it is a signal for a major intervention.[1, 1]
  • The FOC DAM Census: The “Find Other Claimants, Monetize Damages” doctrine requires us to prove widespread harm.[1, 1] Eurostat provides the census data. If a dominant player’s actions are harming one small business, we will use Eurostat’s business demography data to show that thousands of similar small businesses in that sector are experiencing higher “death rates” and lower profitability, proving systemic injury.
  • The USP Justification Engine: Every Unsolicited Proposal (USP) must be based on a clearly defined problem.1 We will use Eurostat data to prove the existence of that problem on a macroeconomic scale. Example: A USP to a government to streamline regulations in a specific sector will be backed by Eurostat data showing that sector has a lower enterprise birth rate and lower productivity than the EU average.

2. Weaponizing the Platform’s Arsenal: Capabilities and Search Rules

Mastery of Eurostat requires understanding its structure as a multi-dimensional database, not a text search engine. The “search” is a process of surgical data extraction and filtering.

  • Official Search Rules & Functionality: The Eurostat database is navigated via a data tree. The key is to select a specific dataset and then customize it by manipulating its dimensions.
    • Data Navigation Tree: The primary navigation method. As seen in the screenshot, we start at Structural business statistics (sbs) and drill down into specific datasets like Enterprise statistics on the whole business population (sbs_ovw) or Regional structural business statistics data (sbs_r).1
    • Customisable Data Selection (The “Filters”): Once a dataset is selected, a customization panel appears. This is our primary control interface. We can filter and select data based on several dimensions:
      • GEO (Geopolitical entity): Allows filtering by individual EU member states, candidate countries, or aggregates like the Euro area (EA) and the entire EU.
      • NACE_R2 (Statistical classification of economic activities): Our most powerful filter. It allows us to select data for specific industries, from broad sections (e.g., C – Manufacturing) down to highly specific classes (e.g., C25.11 – Manufacture of metal structures).
      • INDIC_SB (SBS indicator): Allows us to select the specific economic variables we want to analyze, such as “Number of enterprises,” “Turnover,” “Value added at factor cost,” “Gross investment in tangible goods,” or “Personnel costs.”
      • SIZECLAS (Size class): Allows for filtering by company size (e.g., “Less than 10 persons employed,” “From 10 to 49 persons employed,” etc.), which is critical for analyzing the health of SMEs versus large enterprises.
      • TIME (Time): Allows for selecting annual data points to create time-series for trend analysis.
    • Data Export: The platform allows for the download of any customized data table in various formats, including Excel (XLSX) and CSV, for offline analysis and integration into our reports.

3. Strategic Interrogation: The Questions We Ask

We interrogate Eurostat to find the macroeconomic evidence that supports our micro-level strategic plays.

  • For Benchmarking & Competitor Analysis:

    • “What is the average ‘Value added per person employed’ in the German automotive manufacturing sector (NACE C29) compared to the French and Italian sectors over the last five years? This provides a hard benchmark for the efficiency of major players like Volkswagen versus Renault or Stellantis.”
    • “How does the profitability (measured by Gross operating surplus) of the UK’s Financial Services sector (NACE K) compare to that of Luxembourg and Ireland? This provides context for the competitiveness of the City of London.”

  • For StealthConsolid & Market Structure Analysis:

    • “What is the enterprise ‘death rate’ and average number of employees per enterprise in the Accommodation sector (NACE I55) in Spain versus the EU average? A higher death rate and rising average size could be a statistical footprint of a StealthConsolid operation by large hotel chains.”
    • “Show me the number of enterprises in the Computer programming, consultancy sector (NACE J62) broken down by size class. Is the number of small enterprises (1-9 employees) growing or shrinking relative to large enterprises? This reveals trends in market fragmentation or concentration.”

  • For FOC DAM & Systemic Harm:

    • “A new environmental regulation was imposed in 2022. Show me the annual ‘Turnover’ and ‘Gross investment’ for the EU Chemicals manufacturing sector (NACE C20) from 2018 to the most recent year. Is there a statistically significant drop after 2022, providing evidence of systemic economic injury for a FOC DAM campaign?”
    • “A major retailer is accused of squeezing its suppliers. What is the trend in the ‘Gross operating rate’ (profitability) for the Manufacture of food products sector (NACE C10) over the last 10 years? A long-term decline supports a narrative of systemic abuse of buying power.”

4. The COCOO-Eurostat Strategic Playbook: A Model for Action

The following playbooks provide standardized workflows for using Eurostat to generate powerful, data-driven intelligence.

Playbook A: The “Sectoral Autopsy” (Benchmarking Engine)

  • Objective: To create a definitive, data-driven profile of a target industry’s health, structure, and performance relative to its European peers.
  • Execution:
    1. Define the Market: Identify the primary 2-digit or 3-digit NACE code for the target industry (e.g., C21 – Manufacture of basic pharmaceutical products).
    2. Select Key Indicators: In the Eurostat database, navigate to the main annual enterprise statistics dataset. Select key performance indicators (INDIC_SB) such as “Turnover,” “Value added,” “Personnel costs,” and “Number of persons employed.”
    3. Select Peer Group: In the GEO dimension, select the target country and 3-4 key competitor countries (e.g., UK, Germany, France, Switzerland, Ireland for pharmaceuticals).
    4. Select Time Period: Choose a 5-10 year TIME period to analyze trends.
    5. Extract and Analyze: Download the data. Calculate key ratios like “Value added per employee” (productivity) and “Personnel costs as a % of Value added.”
  • Strategic Outcome: This playbook produces a powerful “Sectoral Health Dossier” that can be used to prove a market is underperforming, justify a USP for a turnaround strategy, or provide irrefutable Benchmarking data in a complaint to a regulator like the CMA.

Playbook B: The “SME vs. Giants” Analysis

  • Objective: To find evidence of market dynamics that disproportionately harm Small and Medium-sized Enterprises (SMEs), creating an opening for a WPI (Public Interest) campaign.
  • Execution:
    1. Define the Sector: Select a NACE code where large players and SMEs coexist. Example: G47 – Retail trade, except of motor vehicles.
    2. Isolate by Size: In the dataset customization, use the SIZECLAS dimension. Select data for “Less than 10 persons employed” and “250 persons employed or more” as two separate queries.
    3. Compare Performance: For both size classes, extract time-series data for indicators like “Enterprise birth rate,” “Enterprise death rate,” and “Gross operating rate” (profitability).
    4. Find the Discrepancy: Analyze the trends. Is the death rate for SMEs increasing while their profitability is falling, whereas large enterprises are stable or growing? This is strong evidence of a market structure that squeezes out small players.
  • Strategic Outcome: This playbook generates the statistical proof of a “two-tier” market. This evidence is invaluable for lobbying regulators, launching a media campaign about the decline of small businesses, and positioning COCOO as the champion for SMEs against large, dominant corporations.

Playbook C: The “Pre-USP Market Scan”

  • Objective: To use macroeconomic data to identify and quantify a problem that will form the core justification for a high-value Unsolicited Proposal (USP).
  • Execution:
    1. Formulate Hypothesis: Start with a strategic hypothesis. Example: “The renewable energy sector in Country X is underdeveloped compared to its potential.”
    2. Find Supporting Data: Go to Eurostat. Select the NACE code for Electricity, gas, steam and air conditioning supply (D35).
    3. Benchmark Investment: Compare the “Gross investment in tangible goods” for this sector in Country X against the EU leaders (e.g., Germany, Denmark, Spain) over the last 10 years.
    4. Quantify the Gap: If the data shows that investment in Country X is significantly lower as a percentage of value added, you have quantified the problem.
    5. Deploy the USP: Approach the government of Country X with the USP: “Our analysis of Eurostat data reveals your nation’s energy sector investment lags significantly behind EU leaders, representing a major missed economic and environmental opportunity. COCOO has developed a proposal to create a new investment framework to attract the capital needed to close this gap.”
  • Strategic Outcome: This playbook uses the EU’s own official data to prove to a government that they have a problem they need to solve, positioning COCOO not as a mere consultant, but as a strategic partner with the data-driven insight to identify and fix national-level issues.

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