Home » Part A: Implementation of an organic market data collection system » A1 Why do we need good data on the organic market

A1 Why do we need good data on the organic market

A1.1 Introduction

In the rapidly changing global environment, the organic sector has now developed to the point where the need for improvements to statistical data is becoming particularly pressing. Market intelligence and other forms of information are a matter of primary importance for the organic sector, and it is necessary to guarantee its independence, correctness and transparency. The consequences of failing to address this are potentially significant, in both political and financial terms.

Currently in Europe:

  • consumers are spending more than 20 billion Euros annually on organic food, and demand is still growing at a higher rate than in other food sectors, even in the context of an economic slowdown;
  • policy makers are investing millions of Euros annually in organic farming support payments and other rural development policies that benefit the organic sector;
  • more than 300,000 production businesses are engaged with the organic sector in Europe. In addition to these, there are at least 40,000 processors and importers, as well as further players, such as retailers, wholesalers, inspection bodies, and consultants.

Therefore, the consequences linked to the risks of making incorrect decisions on the basis of poor statistical information can no longer be ignored. Also, the potential for future expansion, particularly in the emerging economies of central and eastern Europe, must be taken into account.

A1.2 Organic market data availability and quality are still poor

Despite the growth of the organic market, we still have little information about it.

Reliable market data and official statistics of the organic market are available for only in few European countries. Data are collected and published by various bodies, including national authorities, private companies and research institutions, and different methodological approaches are applied. The results often show contradictory trends, which can lead to very different interpretations of the market situation. At the same time, the majority of potential end users have limited access to reliable market-related information. In some cases, this can lead to incorrect entrepreneurial decisions, and this carries the risk of operators leaving the organic sector because they are not aware of opportunities in the market.

Organic market data quality is also relatively poor. Data quality is defined as "the capability of data to be used effectively, economically, and rapidly to inform and evaluate decisions" (Karr et al., 2005). Data of poor quality can lead to incorrect or inefficient decisions, at both the governmental (e.g., policy-making) and enterprise (e.g., investment, supply or sales strategies) levels. In academic research and policy evaluation, the use of poor quality data can result in incorrect theories or other biased scientific outcomes.

Data quality is highly context specific: a database can be adequate for one purpose, but not for another, which renders it even more difficult to evaluate the data quality. One of the key principles of data quality management is user orientation (Eurostat, 2002). The types of users are, however, manifold, and the relationships between the data users and data producers are very complex. It is probably impossible to make the data adequate for all purposes, but bearing in mind which stakeholders are the most relevant data users for any specific data type can help to address this problem.
Also, data quality can be assessed according to various dimensions and metrics. We will not explore this issue here in detail, although it is useful to report the following attributes of data quality (Karr at al., 2005):

  • Objectivity: whether disseminated information is accurate, reliable, and unbiased.
  • Utility: usefulness of the information for anticipated purposes of the intended audience.
  • Integrity: protection of information from unauthorised, unanticipated, or unintentional falsification or corruption.

Before we proceed further, we will list here the various challenges that are currently experienced when collecting, processing and disseminating organic market data.

  • Lack of data and incomplete data
    In most countries, only very basic data are reported, such as the data for certified organic farms, land areas, and livestock numbers. Currently, reliable detailed market data do not exist in most European countries; e.g., production volumes, and data on the domestic market, international trade and consumer prices. In some European countries, there are only rough estimates of the levels of production and consumption. When there are survey data available, the coverage is often incomplete, and this can result in biased statistics.
  • Lack of common definitions and classification/aggregation rules across countries
    There is a lack of standardised and harmonised procedures to ensure higher data quality. Almost every country uses different definitions, nomenclature and classification, and only few use the international classification (Denmark uses the UN’s Standard International Trade Classification [SITC]; the Czech Republic uses the CPA codes of EUROSTAT). As a consequence, country-to-country data comparisons are very difficult. In countries, where the domestic market data are collected from panel data, usually the nomenclature and classification of the major market research companies are used, and these vary between countries and can change from one year to the next; thus comparisons here are also difficult.

    Data is often aggregated, and a lot of the detail within the data gets lost in this aggregation. In many cases, only an incomplete breakdown by crop or product is available, and this can make the data of little use for some purposes (e.g., farmer decisions). What makes things worse is that there is no harmonised way of aggregating these data. For example, in Switzerland, Bio Suisse groups breakfast cereals with pet food. In addition, for retail scanner data, the aggregation can change from one year to the next, so that meaningful times series comparisons become impossible.

    With reference to non-standardised definitions, a good example is that of livestock data. The indicator used is “the head count”, which has been interpreted in different countries as “average stock per year”, “livestock at a given day” (e.g., 1 May in some German Laender), “number of places” (in stables), or “animals slaughtered”. These differences in the definition make country-to-country comparisons for livestock more or less impossible.
  • Other issues
    Exchange rate fluctuations can make country-to-country data comparisons very difficult. Some data are based on expert estimates, but often there are no checks to validate these data by other sources.

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A1.3 Previous and running EU projects involved in improving organic market data collection system

EU research projects like Organic Farming and the CAP (FAIR3-CT96-1794), OMIaRD (QLK5-2000-01124), EU-CEE-OFP (QLK5-2002-00917) and CERTCOST (KBBE-2007-207727) have shown that in many countries, regional or national data gathering takes place. The FP5 Concerted Action ‘European Information System for Organic Markets’ (EISfOM  - QLK5-2002-02400) was fully devoted to the building of a framework for reporting valid and reliable data for the European organic sector, to meet the needs of all of the stakeholders involved in organic markets. EISfOM concluded with a list of 24 recommendation that addressed: (i) improvements in the current situation of data collecting and processing systems; (ii) innovations in data collection and processing systems; and (iii) integration of conventional and organic data collection and processing systems.

Building on the outcomes of these projects, OrganicDataNetwork (FP7-KBBE-2011-5) aims to enhance the transparency, through better availability of market statistics in the sector, while also considering the needs of policymakers and key players in organic markets. The project brought together stakeholders and bodies from 11 countries that collect, publish and use data in the sector. For the first time, existing secondary sources of data on European organic markets were collated and cross-checked; limited data collection was attempted, to improve the current organic market data reporting in six case studies.

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