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Advanced Analytics

Advanced Analytics

Technologies and analysis to measure the future

With our solutions of Advanced Analytics, organizations shape the future through data. The data-driven approach means to master predictive analytics, mathematical algorithms, and cutting-edge technological solutions. Applied to business, Advanced Analytics allows companies to configure possible future scenarios and adapt variables to drive the change.

Process Mining

Process Mining

Reading from event logs, processing data and analysing the digital traces of activities allow your company to reconstruct workflows and verify their KPIs. Through a well-defined business process analysis, it is possible to intervene to manage it.

Demand Planning

Demand Planning

To analyze and manage the production planning process according to the market demand and the historical sales data.
It is possible to integrate the business ecosystem data in order to analyze multiple variables and make the forecast process more efficient.

What if Analysis - Simulazione di scenari commerciali per la gestione del pricing

What if Analysis – Pricing Simulation

Models for future scenario simulations are based on linear regression models, composed by governable and non-governable variables, dependent and independent. After a comprehensive study of the market and the business, it is possible to use levers (that are simulations of governable and dependant variables) to get possible future scenarios. Through the variable simulation, the knowledge about the impact of the change reduces uncertainty and let the company aim at its goals.

Advanced Integration: R – Python

Advanced Integration: R – Python

As some analysis need huge computing power, we use programming languages like R or Python. R is mainly used for statistical analysis, Python instead provides a 360° approach to Data Science.
Thanks to AP or other communication channels, you can integrate these platforms – both in asynchronous or synchronous mode – into Advanced Analytics models.

Analisi Gettato

Scrap Analysis

The scrap management and the optimization of related business process are sensitive topics. The Scrap Analysis concretely aims at reducing the waste, with no uncertainty due to possible variables. Getting information about the condition of waste formation, in other words before products become waste, it is possible to invervene in order to optimize the impact and reduce the waste management costs.

Market Basket Analysis

Market Basket Analysis

The Market Basket Analysis help you better understand your customers and their buying behaviour. It also allows you to predict dynamics according to emerged patterns.
After a comprehensive study of the business, the Market Basket Analysis detects customer clusters allowing you to understand what are the best selling products, according to multiple analysis dimensions and related variables.

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