Novartis’ Forecasting Revolution: Sharper Insights for a Healthier Future
Nov 16, 2023
Nov 16, 2023
The ability to generate accurate sales forecasts is a critical aspect of maintaining competitive advantage and operational excellence. Novartis was in pursuit of a system that would provide a reliable forecast of sales and financial health, serving as the backbone for strategic planning across various departments, from finance to production and from sales operations to supply chain management.
The challenge was multifaceted: Novartis required a predictive model that could adapt to the volatility of the pharmaceutical market, account for the complex dynamics of dozens of countries, and align various departmental strategies to the company’s overarching revenue goals.
The journey to revolutionize Novartis' forecasting capabilities was an exercise in precision, collaboration, and innovation. Sigmoidal's bespoke AI consulting approach merged deep industry knowledge with cutting-edge data science,delivering a solution that resonated with Novartis' stature in the pharmaceutical sector.
Event Storming as a Catalyst: The project commenced with an Event Storming workshop, enabling us to visualize Novartis' forecasting ecosystem and to pinpoint areas for innovation.
Data Diversification and Analysis: A comprehensive audit of available data was conducted, ranging from structured numerical data to unstructured textual records. Our team deployed Big Data analysis techniques to decode this diverse data set, preparing it for the predictive modeling phase.
Code Transformation and Efficiency: A strategic decision was made to transition the forecasting model from R to Python. This rewrite was not a mere change in coding language; it involved a restructuring to enhance model training efficiency, tapping into Python's extensive libraries and thriving support community for ongoing development and scalability.
Predictive Modeling and Machine Learning: The core of our solution was the development of predictive models using advanced machine learning algorithms. These models were trained and refined to predict sales and cash flow with enhanced accuracy.
Deployment and Monitoring: We utilized Amazon SageMaker for its robust capabilities in model deployment and monitoring, ensuring that the predictive models were not only precise but also seamlessly integrated into Novartis' operational framework.
Through Sigmoidal's AI consulting prowess, Novartis witnessed a 12% improvement in forecast accuracy and unlocked a series of operational benefits:
In transforming the project from R to Python, Sigmoidal implemented a Knowledge Sharing and Product-focus Method, which significantly accelerated the product's growth, allowing Novartis to reach the market-ready phase sooner than expected.
Ultimately, our solution empowered Novartis to proactively monitor market shifts across multiple countries, boosting revenue and enhancing supply chain operations with timely material purchases.
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Natural Language Processing: We turned unstructured textual data into meaningful insights, which fed into the predictive models to improve their output.
Data Visualization and Reporting Tools: We brought complex data to life, enabling stakeholders to visualize and understand forecasting trends with clarity.
Big Data Analysis and Processing: We harnessed the power of big data, ensuring that every piece of information from Novartis’ global operations was analyzed for predictive modeling.
Machine Learning Algorithms for Predictive Accuracy: We advised the use of sophisticated machine learning algorithms to refine predictive modeling, enhancing the accuracy of sales and cash flow forecasts.
leading to more agile and responsive forecasting practices.
Improved the accuracy of sales and cash flow predictions, enabling better financial planning and strategy.
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