Abstract

The growth of big data is evident as organizations’ application of information technology
continue to improve and data storage costs continue to fall. The growth of big data presents an
opportunity for organizations to better understand their customers, develop strategies that will
generate additional revenue, and grounds for business model innovation. However, a very small
portion of data collected by organizations gets analyzed. This scenario creates a loophole that
may deny established business additional revenues, and threatens their long-term existence if
new market entrants explore this weakness. Intelligence-driven organizations analyze data to
generate actionable insights that guide decision making. Customs administrations generate
huge amount of unstructured data, but what percentage gets analyzed? This paper presents two
frameworks that can be customized by customs to develop strategies for intelligence-driven
operations. First, is the SCALE framework that defines attributes of intelligence-drive
organizations and secondly, the data-value framework that defines how organizes can transform
data to value. These frameworks are enhanced by a review of three customs services in the
world. In summary, two key lessons are reviewed. First, is the focus on enterprise-wide
adoption of analytics and secondly, is the role data in becoming intelligence-driven. The paper
concludes by highlighting use cases where customs can leverage machine learning capabilities
to enhance operations.