Improving Spatial Data Supply Chains Learnings from the Manufacturing Industry

Government spatial data holdings are the basis of many Geographic Information System applications and users have come to depend on this information for reliable evidencebased decision making. However, many spatial data supply chains, particularly those that span multiple organisations and different levels of government, are not effective and users are having to make do with out-of-date and incomplete information. The manufacturing industry has a long history in supply chain analytics and well established models. This paper discusses five traits that have generated production efficiencies in manufacturing and can be applied to effectively produce spatial data that is fit for purpose in the user’s context. The successful supply chain traits are: a) formalized extended supply chain strategies; b) information metrics and measures; c) closed loops; d) traceability; and e) the ability to effectively communicate quality and purpose to end-users. A supply chain framework incorporating these traits is proposed for