CLUSTER MAPPING APPROACHES Originators: Foundation for MSME Clusters (FMC), UNIDO

Reducing poverty through sustainable industrial growth What is Cluster Mapping?  Cluster mapping is the process of identification of geographical concentration of SMEs that are defined for its product range, number of firms, employment, turnover, etc., based on: How big an area: village/city/district How wide a product How many firms What will be the criteria? Turnover, export, employment,… The key is inclusivity The key is joint action

Reducing poverty through sustainable industrial growth The Italian Experience in Mapping  First attempt to formally identify SME Cluster in Italy: Fabio Sforzi for Italian Statistical Institute (ISI) based on the definition of Local Productive Systems. Local manufacturing system where the share of manufacturing workers is higher than national average. LQm = (Ama/Ata)/ (Ami/Ati)>1,000 SME manufacturing local systems where the share of workers in SMEs is higher than the national average. LQ250, m = (A250,ma/Ama)/ (A250, mi/Ami)>1,000 Industry of specialization of the local system where the share of employment is higher than the national average. LQp = max (Asa/Ama)/(Asi/Ami) SME employ more than half of the total local employment in the sector of specialization. Ip= (A250,pa/Apa)> 0,50  In 1991, simpler approach was introduced, wherein SME clusters are defined as “areas characterized by high concentration of small enterprises and by a particular productive specialization..”

Reducing poverty through sustainable industrial growth The Italian Experience in Mapping  In 1995 – 5 parameters for mapping: IndexesRequirementTuscanyLombardy Index of manufacturing industrialization (Total workers/ manufacturing workers) Over 30 % of national average Over 85%...> 18.5 per cent of regional average Index of manufacturing entrepreneurship (Manufacturing local unit/ population) Higher than National average Same Index of productive specialization (Workers in specialized field/ total manufacturing workers Over 30 % of national average Higher than national average 20% of regional average Intensity of specialization (Workers of the specialized field) Over 30% of manufacturing worker Over 23% SMEs in specialized field (Workers in SMEs) Over 50% of the total workers Over 50% of local workers

Reducing poverty through sustainable industrial growth The Italian Experience in Mapping Example: Cluster Map of Italy

Reducing poverty through sustainable industrial growth The UK Experience in Mapping  A Location quotient (LQ) is calculated to measure the area’s share of a given industry’s national employment relative to the area’s share of total national employment: LQ= (Eij/Ej)/ (Ein/En) or LQ= (Eij/Ein)/ (Ej/En). Identification of regional highs LQ review LQ>1.25 Emp Review Emp>0.2% Non allocated SICs reviewed LAD Review Regional cluster Less significant clusters or other conc. of eco activity Allocate to Feedback cluster definition Cluster classification Depth Development stage Employment Geographic significance Grouped to form Allocate to

Reducing poverty through sustainable industrial growth The UK Experience in Mapping  Classification of clusters based on 4 criteria: Stage of development Depth: Deep/ Shallow/ Unknown Employment dynamics: Growth of employment Significance Small in relation to UK Embryonic Either functioning of could do so Potential for future entry and cluster develpment Established As ‘full’ as it likely to gt Entry difficult or unattractive Matures

Reducing poverty through sustainable industrial growth Another Approach (Proposal)  From macro to micro level understanding  Process of iterative validation using secondary and primary data

Reducing poverty through sustainable industrial growth Another Approach (Proposal)  Sector Profiling: Identifying Key Sub-sectors Use all available national, provincial and district level data Identify significant sectors to national economy in terms of:  (a) Principal sub-sectors  (a.1) number of firms (a.2) turnover, (a.3) employment, (a.4) inter-sector linkages  (b.1) presence in various province/district/municipality, (b.2) all key indicators as in a.1 to a.4 Gaps and likely national and regional institutions who can provide further economic parameters on concentration Conflicting macro data due to different sources and period coverage and defining the product Maximizing Inclusion, especially the informal sector

Reducing poverty through sustainable industrial growth Another Approach (Proposal) As defined in India:  UNIDO project in India: 100 MSMEs – industrial clusters and/or turnover more than USD 250, firms for micro enterprises  Operational at the Ministry level: At least 30 units for industrial clusters At least 20 units for common infrastructure for industrial clusters, 10 firms for exceptional cases 50 units for micro firms

Reducing poverty through sustainable industrial growth Another Approach (Proposal) Validate with primary sources: (a.1) Product definition, (a.2) Geographical area, (a.3) Number of firms, (b.1) Employment, (b.2) manufacturing systems Industry stakeholders 1. National Chambers of Commerce 2. Sectoral association 3. Division level chambers 4. Cluster level associations 5. Product based association Other stakeholders 1. Technical Institutions 2. Food technology colleges 3. Researchers 4. Policy makers 5. Export promotion Council Walk through market assessment Through visit and visual overview of the market place Discussions with retailers REGIONAL WORKSHOPS