Data analysis within the framework of customs management
Customs-related data analysis – an insight for practitioners
A practical and individually configurable IT solution for analyzing customs-relevant data (in particular declaration/master data and transaction data as well as external data) is a crucial prerequisite for a strategy- and compliance-oriented customs function in order to build efficient, flexible and transparent processes in the area of customs and foreign trade. The analysis and evaluation of customs key figures and key performance indicators is also crucial for corporate planning, in order to derive possible customs savings potential or to carry out scenario analyses. In addition, the preventive effect for the detection and prevention of weaknesses and violations represents a decisive added value of a data analysis and thus supports an already existing risk / compliance management system.
Data collection and data integration in tool environment
The ability to analyze data requires appropriate data availability and -collection as a prerequisite. Ideally, all customs-relevant data from the identified data sources should be harmonized and fed into an analysis system. Normally, the “Extract, Transform, Load (ETL)” approach is used to unify data from multiple, differently structured data sources into one target store.
With modern front-end tools, the customs function is ideally provided with the evaluation of current key figures summarized within dashboards at a glance. Through parameterization and individual filtering, company data can be narrowed down and visualized in a targeted manner.
Outsourcing vs. in-house data analysis
If the customs function is faced with the challenge of introducing a data analysis process, the first question is whether in-house data analysis capacity should be built up or whether this activity could be transferred to a service provider.
On the one hand, flexible, quickly implementable deployment and customization options as well as the option of deep integration into master data and ERP systems speak for the acquisition of an own data analysis tool. On the other hand, outsourcing the data analysis activity means a much lower commitment of personnel, time, and financial resources and allows data analysis to be performed ad hoc and with additional external expertise.
Feel free to learn more about AWB’s customs-related data analysis and reporting services at:
Use cases of data-based customs management
Reporting, i.e. the collection of customs data, forms the basis of data analysis and provides valuable insights and key figures at the same time. Classic applications of reporting are key figures such as import duties paid (per region/country/product/import duty type, etc.) or savings achieved (per region/country/product/preferential agreements/special customs procedures/incentive programs, etc.).
Compliance in the context of risk management
A decisive added value of customs-related data analysis is the identification of compliance and efficiency weaknesses as well as process-related improvement potentials by condensing and validating data from various sources. Examples of this would be the comparison of declared customs tariff numbers with stored master data, verification of invoice amounts declared vs. posted in the customs declaration, plausibility checks of declared delivery costs based on delivery conditions, comparison of the country of dispatch with the declared country of origin of the goods, overview of the submitted procedure codes, EU codes, TARIC codes and certificates, inconsistencies and anomalies in customs declaration data (e.g. with regard to preference codes, code numbers).
If a company already has a customs-specific risk management system as part of a compliance management system (CMS) or an internal control system (ICS), regular or ad hoc data analyses such as those described above can also contribute to increasing the level of compliance as preventive and detective controls or provide support in this regard.
Savings potential and corporate planning
The analysis of supply chain data from ERP systems (in particular from the areas of procurement, production and sales) allows the customs function to correlate supply relationships in purchasing, production sites and sales markets and thus identify starting points for customs savings. Here, it is important to know which role the company considered in the data analysis plays within the value chain:
- As part of the analysis, a supplier of primary products will look at where it can supply its goods and, if necessary, gain a competitive advantage over other co-suppliers by taking advantage of preferential agreements.
- A globally active producer of finished goods, on the other hand, will look at the entire supply chain. The following questions, for example, must be considered in the analysis:
- From which countries can the preliminary products be sourced cost-effectively, taking preferential agreements into account?
- Where are the finished products delivered to and can the goods be exported to the respective sales market on a preferential basis, if necessary taking into account cumulation of intermediate products?
- What customs procedures or local incentive programs can be used to achieve further cost reduction within the supply chain?
If the analyses described above are transferred to the company’s strategic planning with regard to sourcing, manufacturing and sales markets, a decisive added value can be created in the interaction of the relevant corporate functions with the customs function in the context of cost reductions and an increase in the compliance level.
Data analytics can enable your business in this way, to be the decisive step ahead in the highly dynamic customs world of our time. Automated data analysis gives customs managers more scope to make the best possible use of the strategic potential of cross-border trade relationships in the form of customs benefits.
For further information, please refer to the published article “Data analysis in the context of customs management” in the trade journal “ZOLL.Export” (December 2021 issue).