Sales Forecasting

We have developed a forecasting component based on objective data to improve planning reliability.

Client Situation
‍Challenge

A company that operates in the jewelry creation sector managed a production planning process characterized by high complexity and strong dependence on individual experience. The absence of advanced predictive tools made it difficult to anticipate workloads, with the risk of inefficiencies in resource management, delays in production times and waste of material. The need to introduce a forecasting component based on objective data has emerged as a strategic lever to improve planning reliability and respond more promptly to fluctuations in demand.

Our Approach

An innovation process was launched that involved the analysis of the current scenario and historical data, with the aim of developing a predictive model based on machine learning techniques. The model has been designed to:

· Analyze the history of production loads.

· Identify recurring patterns and seasonal trends.

· Generate reliable forecasts for subsequent periods.

· Improve progressively through continuous feedback mechanisms.

‍

Technological implementation

The project was divided into three main phases:

1. Analysis of the available processes and datasets.

2. Development and training of the predictive model.

3. Validation of results and operational adoption.

The model has been made available in an easily accessible environment, to support managers in daily planning.

Significant results of the project

Thanks to this structured and integrated approach, the organization has achieved tangible benefits both in operational and strategic terms:

Better operational planning

With a clearer and earlier view of future loads.

Reduction of costs and time

Thanks to a more efficient management of resources.

Greater reliability of decisions

Based on statistical data and models.

Model scalability

With the possibility of extending its use to other business areas, such as demand forecasting or supply management.

Smart management

This path represented a first step towards an intelligent and data-driven management of production, strengthening the organization's ability to react to changes proactively.

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We offer personalized on-site support to help companies manage and coordinate their projects directly at their offices. This includes assistance with planning, monitoring activities, managing resources, and resolving any operational issues.

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