Cluster Management Makes the Difference

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Cluster Management Excellence Makes the Difference

Findings and conclusions from the first

Pan-European cluster management and cluster programme

benchmarking exercises

Gerd Meier zu Köcker

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Participants

− 10 European countries− 14 Cluster programmes− 142 cluster managements from 8 countries

Purpose: − Promotion of good cluster policy− Promotion of cluster management excellence− Promotion of mutual learning by comparing cluster organisations based on

voluntary benchmarking− Testbed for harmonised quality indicators for cluster organisations within

Europe− Verify whether non-political criteria for organisational cluster excellence are

accepted and applicable

Initiated and financed by

Project duration: October 2010 until June 2011

Key Figures of the NGPExcellence Project

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Grappes d'entreprises

Participating Programmes

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Benchmarking of cluster managements has several advantages compared to other approaches:

Comparison with others reveals the current position compared to others / to the best shows specific strengths and weaknesses motivates to learn from the best provides findings that can be used in the practical work no good or bad, nor ranking or rating provides interested parties with valid information about the competitive position

of a cluster compared to others

Results of the benchmarking provide valid input to cluster organisations and policy makers towards cluster management excellence

NGPE-Benchmarking of Cluster Managements - Why?

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Recommendation: Offering Tools

for Enhancing Excellence of Cluster

Management

NGPE-Benchmarking of Cluster Managements - Why?

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NGPE Benchmarking of Cluster Managements at a Glance

Benchmarking of cluster managements:

Based on 30 indicators

Focus on cluster organisations, but also clusterrelated indicators are regarded

Voluntary for the cluster organisation

Reasonable efforts, a four-eye discussionleading to a self-assessment by the cluster managers

Local benchmarking experts involved

No ranking or rating

Full benchmarking report, incl. strengths / weaknesses,recommendations for improving actions

Conformity assessment with the European Cluster Excellence Initiative included

High flexibility in terms of comparative portfolio and indicators to be applied

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History of the NGPE Benchmarking Approach

National Level

1st cluster benchmarked

Presentation of benchmarking

approach towards international community

(San Sebastian)

2007

Finalisation of benchmarking

approach

2006

International Level

25th cluster benchmarked


1st foreign cluster

benchmarked


Development of the bench-

marking approach

2008 2009 2010 2011

?

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Statistical Findings

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Where the Participants Came From

Total: 143 cluster organisations

1% 3%7%

8%

11%

14%

18%

38% Austria

Iceland

Finland

Sweden

Norway

Poland

Denmark

Germany

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Age of Cluster Organisations by Countries

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Average Size by Country

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Regional Focus of Clusters by CountryShare of members within a distance of about 150 km from the cluster managers’ office

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Public Funding Rate by Country

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Share of Clusters Gained More than 80 % Private Financing

Cluster with a share ofprivate financing higher than 80 %

Cluster with a share of private financing less than 80 %

27 clusters

114 clusters

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Key Findings

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Key Findings Related to the NGPE-Benchmarking

of Cluster Managements

1. Research driven clusters are much more similar to industrial driven clusters than expected

2. Structure, governance and impact of clusters are strongly influenced by certain determinants

3. Country specific patterns are partly a result of national cluster funding schemes

4. Structure and governance of clusters with high and low public funding rates are quite similar, but the impact is different

5. Size and age have a strong influence on attractiveness of the clusters and impact on SME

6. The technological domain has a strong influence on structure, governance and outcomes of clusters

7. Clusters providing a higher impact on business activities of SME have a more active cluster management in force

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Key Findings Related to the NGPE Benchmarking


Research driven clusters are much more similar to industrial driven

clusters than expected

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Research Driven Clusters are More

Similar to Industrial Driven Clusters than Expected

0

25

50

75

100

125

150Age

Share of highly specialised clusters

Number ofmembers

Share of clustermembers within 150 km

Share of clusters havinga dedicated of legal form

Share of clusterswith highly centralisedgovernance structure

Share of clusterswith high clarity of tasks & roles

Private financing rate

Share of clusters withhighly assured financing

Median value

R&D driven clusters

Industrial driven clusters

Percentage of median value [%]

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Share of clustershaving initiated many

successful co-operations

Share of clusterswith high appearance

in press / public

Impact on R&Dactivities of SME

Impact on R&Dactivities on research institutions

Impact on businessactivities of SME

Impact on internationalisation

activities of SME

Median value

R&D driven clusters

Industrial driven clusters

Percentage of median value [%]

Research Driven Clusters are More

Similar to Industrial Driven Clusters than Expected

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Key findings Related to the NGPE Benchmarking


Structure and governance of clusters with high and low

public funding rates are quite similar, but the impact is different

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Structure and Governance of Clusters with High and Low Public Funding Rates are Quite Similar…

Percentage of the median value [%]

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25

50

75

100

125

150

175

200Age


Number ofmembers

Share of clusterswith a high Industrial

orientation

Share of clustermembers within 150 km





Share of clusters withhighly assured financing

Share of clusters having a strategy

Median value

Public funding rate > 75 %

Private financing rate > 75 %

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…. but the Impact Seems to be Different


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in press / public


Impact on R&Dactivities on research institutions



activities of SME

Median value

Public funding rate > 75 %

Private financing rate > 75 %

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Key findings Related to the NGPE Benchmarking


Size and age have a strong influence on attractiveness

of the clusters and impact on SME

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Size and Age of Clusters Have a Strong Influence on their Attractiveness and Impact on SME


0,0

25,0

50,0

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150,0




in press / public



Less than 50 members

More than 50 members

Younger than 5 years

5 years or older

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Interesting Observations when Comparing Large / Small and Young / Well Matured Clusters


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Less than 50 members

More than 50 members

Younger than 5 years

5 years or older

Share of clusters having a legal form

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Key findings Related to the NGPE-Benchmarking


The technological domain has a strong influence on structure,

governance and outcomes of clusters

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The Technological Domain has a Strong Influence on Structure, Governance and Outcomes of Clusters


0,0

25,0

50,0

75,0

100,0

125,0

150,0

175,0Age


Number ofmembers


orientation



Biotechnology & health

Production & processes

Energy and environment

Service and non-technicalinnovations

ICT

Micro & Nano & Optic

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0,0

25,0

50,0

75,0

100,0

125,0

150,0

175,0Age


Number ofmembers


orientation



Biotechnology & health

Production & processes

Energy and environment

Service and non-technicalinnovations

ICT

Micro & Nano & Optic

0,0

25,0

50,0

75,0

100,0

125,0

150,0







activities of SME

The Technological Domain Has a Strong Influence on Structure, Governance and Outcomes of Clusters


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Key findings Related to the NGPE-Benchmarking


Clusters providing a higher impact on business activities of SME have

a more active cluster management in force

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-50,0%

-40,0%

-30,0%

-20,0%

-10,0%

0,0%

10,0%

20,0%

30,0%

40,0%

50,0%

Hig

h R

&D

orie

ntat

ion

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orie

ntat

ion

Less

than

50

mem

bers

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e th

an 5

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embe

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You

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5 ye

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or o

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%

Priv

ate

finan

cing

rate

> 7

5 %

De

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ind

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Selected cluster comparison groups

Deviation From the Average Impact Index for DifferentComparison Groups

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-50,0%

-40,0%

-30,0%

-20,0%

-10,0%

0,0%

10,0%

20,0%

30,0%

40,0%

50,0%

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ntat

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orie

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embe

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5 ye

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or o

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ate

finan

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> 7

5 %

De

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fro

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imp

act

ind

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Selected cluster comparison groups

Deviation From the Average Impact Index for DifferentComparison Groups

What are the main prevailing determinants ?

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How Differ Clusters Providing Higher Impact on

Business Activities of SME ?


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Correlation Between Impact on SME and Intensity of

Related Services Provided by the Cluster Management

few

act

iviti

es

m

any

activ

ities

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0,6

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1,0

1,1

1,2

1,3

1,4

0,70 0,80 0,90 1,00 1,10 1,20 1,30

Low impact and low intensity of services offered by cluster managers

<-- low impact Business Impact Index high impact -->

High impact and high intensity of services offered by cluster managers

Clusters with a high R&D orientation

Clusters with less than 50 members

Clusters with a high industrial orientation

Clusters with more than 50 members

Clusters with a private financing rate > 75 %

Clusters with a public funding rate > 75 %

<--

low

Clu

ster

man

agem

ent s

ervi

ce in

dex

high

-->

.


Related Services Provided by the Cluster Management (I)

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0,9

1,0

1,1

1,2

1,3

1,4

0,70 0,80 0,90 1,00 1,10 1,20 1,30

Low impact and low intensity of services offered by cluster managers

<-- low impact Business Impact Index high impact -->

High impact and high intensity of services offered by cluster managers

<--

low

Clu

ster

man

agem

ent s

ervi

ce in

dex

high

-->

.


Related Services Provided by the Cluster Management (II)

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Lessons Learned Related to NGP Excellence

High number of excellent cluster managements Many of them can be considered as hidden champions Broad spectrum of excellent and very innovative services implemented

High acceptance of the NGPE-Benchmarking approach and its indicators

Confidentiality of the reports was key for cluster managers to

participate

Even the discussions during the benchmarking interviews were considered to be very helpful Participation can be considered as a clear indication for commitment to cluster management excellence

Excellent base for the upcoming ECEI approach Most indicators are the same

Participants gained first level of recognised cluster management excellence

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Lessons Learned Related to Policy Makers

Cluster managements can make the difference Their performance is one of the prevailing success factors

Proactive support and capacity building seems to be more promising than “only” funding cluster managements

Striving for cluster management excellence should be an important element in all cluster support schemes

Clusters vary – but not as strong as usually expected

Technological domain has a huge impact on structure, objectives, governance and impact of clusters

Tailor-made support schemes for clusters and cluster managements

seem to be a key for more efficiency and additionality of public funding

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Lessons Learned – Intended to Cluster Managers

Cluster managements can make the difference Tailor-made and demand oriented services combined with

professionalism are keys for success and sustainability

Continuous improvement should become a core element in future cluster strategies

Let the others know what you did Many hidden champions

Huge number of impressive success stories – but often unknown

Communication strategy might be an option to better inform members, policy makers and third parties why you are good

Use tools like benchmarking (or in the future ECEI labelling) for mutual learning and demonstrating cluster management excellence

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Framework conditions

Areas for Improving Competitiveness of Clusters

Cluster actors

Cluster organisation

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Thank you very much for your attention

Interested in benchmarking according to EGPExcellence ?

[email protected]