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Supply Chain Analytics

We help you to leverage the potential of your company data. 

The evaluation of business data in various areas of the company – such as production, human resources, finance and marketing – helps to identify strengths, weaknesses and development potential, and thus supports the achievement of corporate goals. As one of our first steps, we schedule a consultation with our customers to gain an understanding of the processes. Then we offer a customized solution for individual needs across the entire spectrum of the data analysis process. 

As a next step it is essential to validate the outcomes in an iterative process – which happens in a cooperation with the process owner – to make sure that our understanding of the customer’s business model is accurate and whether further optimization of the model is required. Consultation with the company and validation of the results are therefore iterative. The following diagram shows the main process steps of our analysis. 

We are working with the following tools: Python, R, Power BI, Tableau, Azure, GCP, Databricks, GitHub, SAP S4 HANA, SAP ABAP, SQL, JavaScript. 

We are also open to address other challenges in the field of data analysis.

Your challenges

  • Data preparation: Creating a database according to the available data and the analysis task. If necessary: data cleansing, imputation, use of external data sources (e.g. geodata, web scraping). 

  • Exploratory analysis: Identification of patterns in the data using statistical and machine learning methods, subsequent interpretation of the results and determination of possible causes. 

  • Modeling/predictive analytics: Forecasting, simulations and what-if analysis to understand what to expect in the future under changing conditions and in different business scenarios. 

  • Visualization: Development of interactive dashboards and reports to support data-based decision-making processes. 

  • Data integration: Creation of a data warehouse from different data sources (e.g. from warehouse management systems and ERP systems) to enable the use of real-time data.

Our solutions

Step1

CONSULTING

  • Identification of bottlenecks in the processes 
  • Prediction optimisation approaches 
  • Definition of necessary management KPIs 
  • Potential assessment of data integration 
Step2

PLANNING

  • Data preparation 
  • Building a data lake 
  • Exploratory analytics 
Step3

EXECUTING

  • Prediction with Machine Learning and AI 
  • Interactive management-KPIs | Dashboards (PowerBI) 
  • Data integration: Data warehouse with transparent real-time data (Azure Synapse)
Step1

CONSULTING

Step2

PLANNING

Step3

EXECUTING