The Cluster ObservatoryEvaluation Model
Regional Programmes & Cluster Programmes
Coaching &Implementation
Learning AcrossRegions and Clusters in Europe
Evaluation Model
Simpler
Surveys
TM
Surveys1. Surveys of member firms/organisations in cluster2. Surveys of cluster organisations3. Surveys of social media (text analysis)
1. Interviews(process tracing/confirmation stats)A Member firms/organisationsB Cluster LeaderC Cluster Organisation Board
2. Participatory observation
1. Benchmarking with otherA RegionsB ClustersC Cluster organisations
2. Peer Evaluation Teams
1. Company Financial Performance(Collection/Cluster definition/Control groups)A Value addedB WagesC Profitability
2. Statistical Analysis
Benchmarking&
Peer Evaluation
The Evaluation Model - Four Complementary Components
Level of Data and Variables
I
IIIII
IV
Method Data point Variables
SIMPLER Firm Value AddedProfitabilityWagesJobs
Survey Firm General performance: Innovation gaps:Cluster networking Firm-to-firmCluster identity Firm- researchTrust Firm - educationInnovation performance Firm- capitalBusiness development Firm - publicSustainability Firm - other clusters
Firm - globalCluster organisation Internal performance (memberships, workshops, projects etc.)
General external performanceInnovation gap performance
Interview Firm Participation within cluster activitiesEffects from activities (intended and unintended)Pros and cons being a memberExpectations from being a memberRecommended actions to cluster leader
Cluster leader & ObjectivesCluster board Financing
Internal and external performance
Benchmarking Region Up to around 50 variables measuring regional quality and attractivenessCluster Cluster observatory data rankings: size, specialisation and focus of cluster employmentCluster organisation Size, objectives, financing, performance of peers
I
II
III IV1. A Member firms/organisations B Cluster Leader
C Cluster Organisation Board
SIMPLERresults
Surveyresults
Interviewresults
Fullevaluation
The Full Evaluation Model - Timing
III 2. Participatory observation
II
3. Social media/Email server/text analysis
1.2.
3.
4.
Component Strengths Weaknesses
I SIMPLER 1. and 4. 2. and 3.
II Survey tools 1. 2. 3. and 4.
III Interviews 2. and 3. 1. and 4.
IV Benchmarking 1. and 4. 2. and 3.
Cluster Observatory Model 1. 2. 3. 4.
The Model is Designed to Capture Unintended Effects andControlling for Outside Explanations
TM
2012-06-12 © Grufman Reje 2012
All companies in X region 2010
2012-06-12 © Grufman Reje 2012
All companies in cluster X 2010
Cluster X
Cluster XRegion
Cluster X outperforms its peer cluster and the region in general
Change in value added among member firms in a cluster, as compared to
A) Firms in an unorganized peer cluster andB) All firms within the region within the cluster category
Peer Group
% Change in Value Added
IResults
Performance measurement over 5 years based on 3 indicators
European Cluster Observatory SIMPLER AnalysisComparison of 12 Clusters in a European Region 2006 - 2010 (unidentified names)
Value Added Growth Profitability % of Value Added Wages per employee
Total Rank Cluster Cluster Peer Diff Rank Cluster Peer Diff Rank Cluster Peer Diff Rank SUM1 A 38% 21% 17% 3 5% -13% 18% 2 17% 7% 10% 1 62 B 27% -1% 28% 2 12% 7% 5% 6 16% 8% 8% 2 103 C 8% -6% 14% 4 12% -4% 16% 3 3% -2% 5% 4 114 D 67% 21% 46% 1 12% 7% 5% 6 13% 11% 2% 6 135 E -11% -8% -3% 12 10% -16% 26% 1 12% 9% 3% 5 186 F 16% 4% 12% 6 -2% 1% -3% 11 17% 9% 8% 2 197 G 40% 28% 12% 6 3% -2% 5% 6 11% 10% 1% 8 208 H 31% 18% 13% 5 5% 5% 0% 10 13% 11% 2% 6 219 I 18% 11% 7% 9 0% -15% 15% 4 11% 11% 0% 9 22
10 J 29% 20% 9% 8 7% 1% 6% 5 8% 15% -7% 12 2511 K 33% 26% 7% 9 9% 8% 1% 9 13% 13% 0% 9 2712 L 45% 38% 7% 9 -4% 12% -16% 12 10% 14% -4% 11 32
Results
10 out of 12 Clusters perform better than their peer groupsin terms of financial results and wage development (productivity)
I
$
Companies
Research organisations
Education organisations
Government
Capital
The dream of dynamic clusters
II
Measured the degree of networking across innovation gaps:
Firm- to- firm (SMEs cooperate with large firms)Firm- to-research Firm-to-educationFirm-to-capitalFirm-to-public organisationsFirm-to- other clustersFirm-to-global markets
Results
Some clusters are much better at networking across the innovation gaps = area where SLIM helps out with learning across clustersSome clusters exhibit a negative development after the 2008 crisis
Come a long way
Large gaps still exist
IIResults – Innovation Performance
Cluster Firms have improved their innovation performance significantly by being members in clusters
Moderate effects on sales performance and very limited effects on equality and sustainability
2006 2007 2008 20090
10
20
30
40
50
60
70
80
90
Performance increases over time - by performance type
SalesCost BenefitsEmployment increaseNew investmentsBetter Products and ServicesNew Products and ServicesEqualityIntegrationSustainability
Innovation
Benchmarking regions IV
The Cluster ObservatoryEvaluation Model
Regional Programmes & Cluster Programmes
Coaching &Implementation
Learning AcrossRegions and Clusters in Europe
Evaluation Model [email protected]