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The global map of businesses is increasingly dominated by geographically concentrated groups of companies and related economic actors and institutions. These are called industry clusters, clusters of knowledge, or simply clusters. Interactions between companies, knowledge institutions and the public sector contribute to job creation, higher wages and surplus. The effects are attributed to clusters being an effective set-up for spurring innovation and competitiveness.

A range of international studies have presented results which indicate that clusters have a positive impact on innovation and economic growth. In light of this knowledge, a large number of countries and regions have embraced the concept of clusters and work to develop clusters through initiatives, programmes or cluster-specific innovation policy. On a European level, the Commission has taken on the role of addressing informational and networking needs of member countries, and facilitating knowledge-building on this topic.

In response to various requests for a more fact-based ground for cluster policy formulation in Europe, DG Enterprise and Industry proposed a working area focused on measuring the economic impact of cluster policies. The working area has involved a number of activities: identifying experts, hosting a workshop to present and discuss various good practice examples, and describing good practice examples using a common framework.

This document aims to provide an overview of existing good practice examples of different tools and analytical methods used during the cluster policymaking process. The ultimate objective with this work is to forge a strong, unbiased position from which to make recommendations on factbased cluster policy in Europe.

The result of the first phase of activities for the working area was the identification of experts who develop tools and analytical methods in order to help formulate public policy. Each analytical method was described using the same four headings: Policy use of analysis, Outcome of analysis, Object of analysis, and Data, illustrated by a categorisation wheel.

Several good practice examples of databases for benchmarking clusters, cluster-based economic strategies, industry and cluster studies, and policy-tailored cluster analysis were presented at the workshop in Copenhagen. The examples presented in Copenhagen are described in this document, by use of a categorisation wheel.

Databases for benchmarking clusters are powerful diagnostic tools that policymakers can use to map and benchmark clusters across regions and countries. Providing an overview of cluster composition, these databases highlight varying strengths, and help policymakers target emerging or declining areas for action. Examples are described in Chapter 3.

Cluster-based economic strategies are recommended action plans for a group of companies and related actors. These strategies can be used to understand business environment factors and cluster performance in a specific location, helping to inspire and inform policy formulation. These detailed strategies can also be used in implementation and learning phases to follow-up on cluster performance or changes in a cluster’s business environment over time, in order to evaluate the success of existing policies. Examples are described in Chapter 4.

Industry and cluster studies are broader examinations of the cluster and industry. These studies help policymakers identify areas of the economy on which to focus, explain general trends in the industry and how these may be handled differently in different geographical locations. Industry and cluster studies can be used during the justification, diagnosis and formulation phases to understand how business environment factors affect cluster performance in different locations. One example is presented in Chapter 5.

Policy-tailored cluster analysis encompasses the different analytical tools and methods that policymakers use at different stages of the policymaking process. Industry and cluster databases are used to identify areas of strength and weakness, highlighting possible targets for policy action. Other diagnostic analyses such as detailed cluster or benchmarking studies are used to provide insight on how different business environment factors affect cluster performance. Evaluation and benchmarking analyses are used at different periods of policy implementation. Chapter six presents examples of several countries (France, Finland, Scotland and Denmark/Baltic Sea Region countries) and how they use various tools and analytical methods as inputs throughout the policymaking process.

The summary chapter presents some general observations regarding the use of tools and analytical methods as inputs to cluster policymaking, as well as a summary of discussion from the Copenhagen workshop