Solutions that transcend Business Intelligence
Discover our tools with AI & Data Science engines and Machine Learning methodologies to optimize your business practices starting today.
AI & Data Science engines powered by BIsiona technology
At BISIONA, we understand that in an increasingly competitive environment, innovative solutions are needed that not only respond to market demands but also proactively anticipate them.
That is why, since 2019, we have been working on AI & Data Science technologies in collaboration with the Polytechnic University of Madrid. Together, we develop innovative methodologies and solutions applied to business cases in the pharmaceutical and healthcare industries.
As a result of this collaboration, we offer proven value models based on Machine Learning, AI, and Data Science, integrated into our “baia” module.
Advantages and benefits
The application of our Artificial Intelligence models allows us to solve common problems such as:
Active recommendations
Identifying patterns of success in commercial activity translates into active recommendations for implementation in specific territories, improving sales results cycle after cycle and boosting commercial performance in each region.
Territorial alignment
Intelligent optimization of the territorial alignment of sales networks using algorithms that generate ideal territory assignments.
These realignments pursue various objectives, such as:
➥ Reducing the territorial structure without affecting sales volume.
➥ Increasing potential sales volume, reassigning territories, and calculating the need for new salespeople.
➥ Optimally reorganizing the existing sales network..
➥ Creating a new territorial structure for product launches, among others.
Our intelligent AI assistant
Business Artificial Intelligence Angel “baia” is BISIONA’s new set of models and methodologies that integrates advanced AI and Data Science techniques.
With the application of our AI engine, we aim to help companies create more accurate business strategies and improve sales performance thanks to the active and predictive recommendations generated by the system.
To this end, at BISIONA we have developed a set of models and analysis methodologies based on the application of different statistical methods and algorithms of Machine Learning that enable both continuous and automated learning of behavior and the search for patterns of success.
This generates a unique and real differential value proposition for each of our clients.
The AI solutions we offer through “baia” are specific and concrete, tailored to each business, product, pathology, and objective. Thanks to the integration of multiple data sources, all associated numerical and discrete variables, and information analysis, we obtain a prediction of success patterns that allow us to improve:
- Sales performance through the application of more accurate recommendations.
- Company practices through the prediction of patterns of success.
Furthermore, because the system allows us to consider multiple scenarios, we can select the one that best suits our needs.
To do this, “baia” allows us to generate simulations taking into account multiple factors and variables, with the possibility of incorporating all kinds of allocation restrictions.
This makes this model a flexible, scalable solution that can be adjusted to all kinds of scenarios.
With the application of our AI engine, we aim to help companies create more accurate business strategies and improve sales performance thanks to the active and predictive recommendations generated by the system.
To this end, at BISIONA we have developed a set of models and analysis methodologies based on the application of different statistical methods and algorithms of Machine Learning that enable both continuous and automated learning of behavior and the search for patterns of success.
This generates a unique and real differential value proposition for each of our clients.
The AI solutions we offer through “baia” are specific and concrete, tailored to each business, product, pathology, and objective. Thanks to the integration of multiple data sources, all associated numerical and discrete variables, and information analysis, we obtain a prediction of success patterns that allow us to improve:
- Sales performance through the application of more accurate recommendations.
- Company practices through the prediction of patterns of success.
Además, gracias a que el sistema permite considerar múltiples escenarios, tenemos la posibilidad de seleccionar el más adecuado a nuestras necesidades.
Para ello, “baia” permite la generación de simulaciones teniendo en cuenta múltiples factores y variables, con la posibilidad de incorporar todo tipo de restricciones de asignaciones.
Lo que convierte este modelo en una solución flexible, escalable, y ajustable a todo tipo de escenarios.
This project has been co-financed by the European Regional Development Fund (ERDF) and the Center for Industrial Technological Development (CDTI), with the aim of promoting technological development, innovation, and high-quality research.
BISIONA BUSINESS SOLUTIONS, S.L.
‘RESEARCH AND DEVELOPMENT OF NEW ARTIFICIAL INTELLIGENCE TECHNIQUES FOR COMMERCIAL EFFECTIVENESS IN THE PHARMACEUTICAL INDUSTRY’ (IDI-20211219)
A WAY TO BUILD EUROPE
The objective of this project (12/2020-03/2022), located in Madrid, with a budget of €326,829, has focused on developing a predictive system that proposes the most appropriate actions to improve performance to the commercial network of pharmaceutical laboratories and healthcare products. An original methodology based on Artificial Intelligence (AI) techniques has been researched and developed to provide recurring recommendations to each component of the commercial network based on the analysis of a wide range of variables.
Thanks to this research, Bisiona has undertaken the experimental development of a prototype Intelligent Decision Support System (SIAD) for commercial efficiency in the pharmaceutical sector that acts as a centralizing element to aid commercial efficiency. Based on the predictions obtained from the analysis of the different variables in the instances, the system will propose different actions related to the dissemination of content, the execution of action plans, their adaptation, the optimization of routes and visit plans, and other actions derived from the analysis of indicators and the predictions provided by the solution.
