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Knowledge Management in Capital Goods Companies

Knowledge Management in Capital Goods Companies. Dr. Christian Hicks University of Newcastle upon Tyne. Capital Goods Companies. Products usually complex Customised to meet individual customer requirements Engineered-to-order Low volume demand. Competitive Factors. Product performance

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Knowledge Management in Capital Goods Companies

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  1. Knowledge Managementin Capital Goods Companies Dr. Christian Hicks University of Newcastle upon Tyne

  2. Capital Goods Companies • Products usually complex • Customised to meet individual customer requirements • Engineered-to-order • Low volume demand

  3. Competitive Factors • Product performance • Cost of ownership • Level of customisation • Capital cost • Delivery • Financing terms

  4. Business Activities • Tendering • Design • Manufacture • Assembly • Construction • Commissioning • Increasing interaction between processes, as concurrent engineering aims to minimise lead-times • Require feedback of operational experience to design and tendering

  5. Characteristics • Business processes, design and manufacturing systems are all complex, interacting and dynamic. • Capital goods companies have increasingly shifted towards design and project management as manufacturing is increasingly outsourced. • Knowledge base and knowledge management activities are major factors influencing success.

  6. Tendering • Preliminary development of conceptual design. • Definition of major components and systems. • Delivery, price, cost and performance commitments made. • Success depends upon understanding customer requirements, translating them into specifications and integrating components and subsystems into products. • Need to meet commercial, delivery and regulatory needs. • Customer requirements include explicit and tacit components.

  7. Company Structure • ETO companies are dynamic, often changing internal structure to match external requirements • Strategic alliances / joint ventures • Transitory supply chain relationships • Staff turnover / contract labour • Knowledge transfer / innovation through supply chains • Product model evolves as contract progresses. Problems with incomplete / partial information.

  8. Knowledge Management Practices • Required to capture and reuse knowledge gained from previous contracts. • Standard subsystems result in lower costs and are less uncertain than development subsystems. • Knowledge is shared between processes which are often separated by significant time delays and organisational boundaries. • Competitiveness may require controlled and secure access to knowledge.

  9. Research • Objective is to identify new or improved knowledge management activities which will yield benefits. • Some companies have established processes, whereas others develop them as required on a project basis. • Knowledge workers operate within defined business processes and informal routines • Business processes and routines established through observation of processes and routines. • Formal methods used for mapping business processes (SSADM/IDEF)

  10. Routines • Identification of drivers and actors • People / system driven • Identification / dissemination of internal / external knowledge

  11. Knowledge Classification • Knowledge processing - generation, transfer, utilisation, identification, capture / retrieval, format, codification, assurance • Domains - internal/ external, technical area, focus • The part of the organisation’s performance affected by the knowledge management activity • Formality - time and location dependency, MIS

  12. Case Studies • Product development • Manufacturing efficiency improvement • Tendering processes • Design of business processes

  13. Product Development • Design team habitually re-specified components and systems for new orders • Led to excessive costs and lead-times • Business processes were mapped and links between tendering, design and manufacturing were made explicit. • Some personal routines were formalised and included with formal processes. • This lead to increased standardisation, reduced costs and lead-times.

  14. Conclusions • ETO companies are complex and dynamic organisations • Interactions between wide range of processes that may be separated by a time lag. • Formal processes have been modelled. • Current research is focused upon identifying, classifying and documenting routines • Objective is to identify improved KMA’s. The performance of the associated business processes will be compared.

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