Distribution Forecasting
Distribution Forecasting
Data-Driven & What If Analysis
The ability to evaluate different viable strategies in a quantitative and predictive manner is increasingly important in the economic and business environment in which we live.
- Description and benefits
- Application examples
The Data-Driven & What If Analysis solution provides companies with a tool to assign each entity of interest to a class (e.g. financial risk classes, execution times, quantities processed or produced, etc.). This way, it is possible to optimize processes and plan specific interventions on various classes.
Our solution also simulates how the expected scenario would vary as the parameters that the company governs change, and therefore to evaluate the effect on the classes composition.
Targeted interventions
Thanks to accurate predictions, actions aimed at resolving any issues (e.g. reducing exposure risk, procurement risk etc.) can be implemented
Predicting impacts
By studying different scenarios in advance, one can predict the occurrence of certain eventualities and prepare for them or make the "first move"
Optimal strategy
By comparing different scenarios, one can identify the best course of action
Sectors
Application examples of Data-Driven What If Analysis
Industrial
Forecasting raw material requirements to drive procurement
Utilities
Assessing the evolution of credit exposure by predicting the proportion of unpaid invoices
Services
Credit risk simulation according to the characteristics of its debt holders
Deepening
Operating logic
Our solution is based on a machine learning algorithm that provides, for each entity, the probability of belonging to certain definable classes such as time, risk, quantity and more.
Success story: application of Data-Driven What If solution
The solution for a utility market operator
A major operator of the free energy market uses Data-Driven & What If Analysis to manage big data to analyze, predict and simulate scenarios.
C.F. e P.IVA 07015910966 | Via Schiaffino 11, 20158 Milano