Optimal data preparation: efficient analyses for your supply chain

Optimising data analysis for supply chains: preparing data for modelling

As a supply chain manager, logistics manager or data expert, you know how important it is to make informed decisions when designing or managing a supply chain. However, even the best tools, such as anyLogistix, can only deliver their full potential if the data is perfectly prepared. Without well-structured and valid data, you risk inaccurate models and suboptimal decisions.

Why is data preparation so important?

  • Improve the quality of your analyses: incomplete or inconsistent data leads to incorrect results. With careful data preparation, you ensure that your models are accurate and reliable.
  • Standardise your data sources: Do you use data from ERP systems, transport protocols or supplier databases? Harmonised integration of these sources facilitates analysis and provides a basis for informed decisions.
  • Reduce complexity: Supply chain analyses can quickly become confusing. Structured preparation of your data helps you to focus on the essential factors.
anyLogistix_Steps in data preparation for supply chain modeling
anyLogistix_Steps in data preparation for supply chain modeling. Source: The AnyLogic Company

How to prepare your data optimally

  1. Collect data
    • Gather all relevant information from internal systems (e.g. ERP, CRM, WMS) and external sources (supplier data, market trends).
    • Important parameters: delivery times, costs, inventory levels and transport routes.
  2. Cleanse data
    • Eliminate duplicates, add missing values and standardise formats.
    • Errors such as outdated inventory data or incorrect product codes are a thing of the past.
  3. Integrate data
    • Consolidate your data sources into a central structure to ensure seamless interaction.
    • Automated data pipelines can significantly simplify this process.
  4. Transform data
    • Convert raw data into the formats required by tools like anyLogistix.
    • Calculate metrics such as safety stock, transport costs or create demand forecasts.
  5. Validate data
    • Check your data for consistency and accuracy – either manually or using benchmarks and business rules.
    • Use visualisation tools to understand and optimise the data flow.

Support through ETL frameworks

For efficient data preparation, we recommend the use of ETL (Extract – Transform – Load) frameworks. They enable simple and standardised data preparation and help you to convert your data into model-ready inputs for anyLogistix:

  • Data catalogue: Clearly defines how your data is stored and processed.
  • Nodes and pipelines: Structure the process from raw data processing to the finished model.
  • Visualisation: Each step of your data processing is visualised, making it easier to validate.

For example, data from multiple supplier databases can be cleaned, combined and converted into a unified table. This table helps you to model optimal delivery strategies with anyLogistix.

Your advantage: Better data, better decisions

Careful data preparation saves you time and enables more precise analyses. With ETL tools and AnyLogistix, you can lay the foundation for optimised processes, reduced costs and informed decisions.

Source: The AnyLogic Company

Do you have questions or would you like to optimise your supply chain? Contact us for a personal consultation.

On 6 February, our next webinar on SCM simulation and supply chain optimisation will take place. We would be happy to exchange ideas with you on your topics there!

Or contact our supply chain expert Till Fechteler directly for an individual consultation on your supply chain.