Introduction and challenges
Artificial intelligence (AI) and machine learning are no longer mere futuristic trends but have become fundamental components of all business activities.
Decision-making in fields such as supply chain, sales, finance, procurement, human resources, and maintenance increasingly relies on massive volumes of data, which, in their raw state, hold untapped potential. Data Science serves as the means to give structure to both structured and unstructured data, revealing correlations with external information sources like social media variables and macroeconomic indicators.
The implementation of advanced analytics and Machine Learning empowers companies to significantly enhance their performance while reimagining processes to reduce the time spent on repetitive manual tasks and redirect it towards tasks requiring expertise.
AI applications consistently demonstrate their ability to enhance operational performance within companies. Identifying the optimal blend of business acumen and data expertise enables the development of pragmatic, easily deployable, and scalable solutions.
How we can help
Our team of experts comprising data scientists, data engineers, and data analysts help our clients leverage profound expertise in operations alongside technological and data science knowledge. We empower our clients to tackle advanced AI projects, addressing real-world business challenges effectively.
We apply our machine learning and advanced analytics algorithms to a variety of use cases, including:
- Sales forecasts
- Forecasting logistics activity
- Merchandising and assortment optimisation
- Supplier and distribution lead-time prediction
- HR sourcing and recruitment optimisation
- Standard cost modelling and margin management
- Prediction of quality defects in production environments and optimisation of process parameters
- Inventory simulation and optimisation of MRP/DRP parameters
- Environmental impact modelling