Analytics For
MANAGEMENT CONTROL
It collects the financial, accounting and analytical data present in the company and builds statistical and predictive scenarios in order to optimize and analyze the financial process and, therefore, have a more effective management of the company's financial and economic flows and cost centers, as well as for an analysis and interpretation of the Reclassified Financial Statements. is perfectly integrable with the management system already in use in your company.
HR
It is an innovative solution based on Artificial Intelligence techniques, allows you to organize human resources with respect to the real needs of your company. With the ability to build predictive scenarios of reorganization and business evolution. it can be perfectly integrated with the management system already in use in your company.
SUSTAINABILITY
The Nautilus ecosystem component enables the development of a corporate strategy aimed at sustainability, facilitating the analysis of different scenarios. This approach makes it possible to guide the company toward a "green" transition, improving reputation and market positioning. It results in optimization of processes and resources, reduction of waste and costs, along with a cultural revolution in working methodologies. It can be integrated with existing management systems, facilitating adoption and implementation.
Forecasting: the strategic value of foreshadowing scenarios
By virtue of the customized predictive models, Prometheus make the forecasting process reliable and efficient by making reliable and accurate predictions of the behavior of the process itselfIn fact Predicting a scenario such as a failure of a plant machine, its breakdown, the trend of a trend as well as The evolution of demand allows you to make decisions before the event itself happens by going from a logica reattiva, which as such always requires the occurrence of the event, to a pro-active logic that anticipates event itself.
This makes it possible to reduce risk and maximize profit.
Underlying the functioning of the model are the available data-whether internal or external to the company-which, properly processed, become inputs in turn for models that develop time series on the variables of interest taking into account specific factors such as seasonality, product type..... The models thus constructed identify the main dynamics of the system and thus foreshadow its evolution over time.
Demand Forecasting
It identifies needs in advance, seizes more opportunities, improves productivity and customer satisfaction. These solutions aim to prefigure scenarios to enable proactive management of the variables that govern the process itself. This allows a highly effective and efficient business strategy to be defined because the exact needs and resources required are defined.
This allows:
- Understand what variables/factors influence the market
- Improve both economically and operationally the management of stocks
- Reduce in risk of ineffective actions in the market.
- Reduce the risks of understock and overstock
Anomaly Detection
Leveraging predictive Machine Larning logics, current data are compared with the collected time series.
This makes it possible to calculate at any instant an expected value of energy consumption as well as to foreshadow the risk of malfunction or failure.
In both cases, corrective actions to be implemented to reduce abnormal consumption peaks are then identified as well as the predictive maintenance process optimized.
Cutomer churn - how to prevent customer abandonment
Determining in advance which customers will abandon the company and no longer purchase products/services is essential because it allows much more effective and less costly re-call actions to be planned. The models built by Prometeo capture data from heterogeneous historical sources: customer clusters, engagement, loyalty, order and market trends. This makes it possible to highlight, even on a per-user basis, what are the critical issues and the best actions to take to correct iol trend and intervene in a predictive manner.
Optimized planning - More efficiency in customer service
These solutions focus on using methodologies such as Machine Learning and Operations Research to optimize production planning, considering company-specific parameters and constraints. This approach optimizes production costs and reduces waste, while improving customer service levels. The algorithms analyze a number of elements, including production takt time, production lead time, costs, process constraints, customer orders, and inventory. Using statistical-mathematical models, they formulate an optimal production plan that can be applied to different industries, such as plastics molding, the chemical industry, and the ceramics industry.
Inventory optimization & Production Scheduling
This methodology makes it possible to find the right balance between different elements such as: optimization of occupied space, service level, financial fixed assets, demand volatility, shelf file, supply lead time and others. This allows for:
Minimizing production and assembly costs
Increase process productivity
Reduce the financial costs of the warehouse
Reduce delivery time to the customer
Avoid obsolescence in warehouse
Routing Optimization – Multiutility
Prometeo offers a solution to optimize travel routes, reducing costs and CO2 emissions. This technology is essential for sectors such as urban sanitation, home health care, home delivery, and meter maintenance, where there is a need to efficiently plan the movement of people or vehicles to deliver services or deliver goods. Prometeo's approach considers service-specific constraints, such as schedules, vehicle size, and traffic regulations, along with the number of points to be served. By using this solution, routes can be optimized with savings of up to 20 percent of kilometers traveled, thus reducing costs and CO2 emissions. In addition, it makes it possible to optimize the assignment to shifts based on the company's specific needs.
Model predictive control - The Intelligent Management of Plants
The use of automated control systems based on Machine Learning makes it possible to optimize plant management by anticipating the effects of changes in inputs on the plant itself. This approach ensures greater stability in plant control, leading to significant economic benefits. In the process, we integrate the technical and engineering know-how of plant operators with our expertise to create a Digital Twin and model the system, managing the underlying chemical and physical logic. After the data preparation and analysis phase, we use the data to test and train different models, thereby improving the performance and capacity of the plant management significantly.
Marketing recommendation engine – One-to-One Marketing
Personalization of marketing messages to reach customers more effectively has become critical in many marketing campaigns. Machine Learning-based recommendation systems offer an advanced solution over traditional models, as they overcome previous limitations and provide more relevant and personalized recommendations, thus helping customers in their choices.
These systems analyze large amounts of data on customer habits and characteristics, comparing them with recurring patterns to extract meaningful insights. This maximizes the likelihood of conversion through the delivery of targeted and relevant messages to each individual customer.
Next Product - Identifying the best product to propose
What is the product/service that is most likely to be purchased that my Customer has not yet bought? This is the central question of all the problems of Raccommendation, whether the product is included in a shopping cart as much as a new service from a telephone operator. Mathematical statistical models use a plurality of data sources precisely to identify which and how to suggest the best product/service to the Customer. This makes it possible to improve the strategies of up&cross selling and thus the relative business marginality.
Market Basket Analysis - How to determine the ideal price of a product
By accurately analyzing Customers' spending patterns and habits, insights can be identified that enable optimal pricing and sales strategy. The tools we provide in this area serve to do just that, highlighting patterns of behavior, product affinities, and better pricing modes.
Business intelligence
Business Intelligence (BI) represents a set of methodologies, processes, architectures and technologies aimed at capturing, historicizing and transforming data into useful information for decision makers within companies.
In an environment of increasingly dynamic and unpredictable markets, BI becomes an essential tool for companies that want to compete effectively. However, the implementation of a BI project is not only a technological activity: it also requires the consideration of organizational and business aspects.
Too often, the focus is exclusively on technical aspects, neglecting organizational and business elements, which can lead to increases in implementation time and costs. Prometeo has developed a comprehensive implementation methodology over the years that takes all these aspects into account, enabling its clients to implement BI systems while meeting defined time, cost and quality constraints.
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