Novartis’ Forecasting Revolution: Sharper Insights for a Healthier Future

In the intricate world of pharmaceuticals, forecasting is not just about predicting the future; it’s about shaping it. Novartis, a titan in the healthcare industry, recognized the indispensable value of precise forecasting to reinforce its strategic decision-making across the globe. To refine their production capabilities, Novartis formed a strategic alliance with Sigmoidal, with the objective of developing an advanced forecasting and analysis system capable of delivering accurate financial and sales performance predictions across the myriad of markets they serve.

What was the business objective?

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.

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How did we accomplish it?

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.

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The Results

 Through Sigmoidal's AI consulting prowess, Novartis witnessed a 12% improvement in forecast accuracy and unlocked a series of operational benefits:

• A reduction in model training time by 20%, allowing for swifter iteration and deployment of predictive models.
• A 12% increase in the quality of predictions, enabling more reliable and actionable insights for sales and cash flow planning.
• The accelerated ability to reshape source code, making the entire forecasting process 2-3 times faster and more efficient.
• A more aligned sales force focused on high-revenue opportunities, leading to better win rates.
• Streamlined territory coverage and quota assignments, resulting in reduced time spent on planning.
• Mitigated risks in the sales pipeline and forecast, allowing for more precise budgeting and strategy formulation. 

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.