- How can the quality of production processes be increased?
- Which customers could the company lose and why?
- When do machines need to be serviced?
- How can time-consuming decision-making paths be shortened?
- To what extent can the risk involved in making complex decisions be reduced?
Digital transformation changes the foundation of every company in the long term. Those who want to achieve the greatest possible benefit and best results in their business areas in the future are dependent on identifying risks at an early stage, optimizing business processes and deploying resources with maximum efficiency. Data Science & Advanced Analytics encompasses a wide range of tools that can examine business processes and help bring about changes and improvements.
We supported a customer from the automotive industry with both predictive methods and prescriptive analytics, enabling demand forecasting combined with optimized production planning. New orders are now scheduled quickly and reliably. Existing plans are simultaneously optimized to ensure that production runs as effectively as possible. This ensures that the customer receives his delivery on the desired date.
Find out how X-INTEGRATE can also use advanced analytics tools in your company and contact us!
Our Data Science & Advanced Analytics Expertise
Advanced Analytics offers a powerful palette that helps you to get to know your own company better and to comprehensively understand processes. With its help, collected data is better understood and valuable information extracted which leads to better, well-founded decisions. Evaluation can take place using what-if scenarios which help to automate decisions. All this improves your processes to positively differentiate your business from the market and remain competitive.
The success factor for efficient optimization of processes is the collected data. Cognitive technologies are able to process a company's data in depth and develop an understanding from it. To do this, they analyze data - natural-language as well as structured - and organize it into a semantic system so that it can be understood within a frame of reference. Such analyses can help companies shorten or analyze planning processes. Cognitive computing can be AI methods as well as classic chains of data mining and neural networks or predictive analytics. They serve the goal of offering planners several alternatives from which they can choose the one that suits the company best.
- Site Optimization
- Supply Chain Optimization
- Churn Prediction
- Production Optimization
- Warehouse Optimization
- Predictive maintenance
- Route Optimization
- Predictive Quality
- Corporate planning
- Purchasing planning