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Case Study: Optimizing Big Data & AI Capabilities for a World-Class Pharmaceutical Company
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A leading life sciences & pharmaceutical company headquartered in Switzerland aimed to reimagine medicine by bringing in big data and digitization. To do so, it established its global capability center (GCC) in India to capitalize on the nation’s rich talent pool and advanced technological infrastructure.
Business Challenges
Aiming to power its product launches in new markets through advanced analytics and artificial intelligence, the company faced four major challenges ~
- Inaccurate sales forecasting, resulting in overstocking or understocking, consequently leading to increased operational costs.
- A complex pricing strategy due to operating in diverse markets with varying economic landscapes and competitive environments, impacting revenue growth and market positioning.
- A slow, manual competitive analysis, hindering the company’s ability to respond swiftly to market changes and capitalize on new opportunities.
- Lack of real-time visibility into the supply chain, resulting in operational disruptions, suboptimal resource allocation, excess inventory levels, and a lack of agility in responding to changing market demands.
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Our Solution
Established in Hyderabad in 2006, the company’s GCC created new technological capabilities to solve its business challenges, transforming how entire verticals functioned.
- AI-driven Advanced Forecasting: By deploying advanced forecasting techniques such as neural networks and predictive analytics algorithms, the GCC could substantially refine sales forecast accuracy. The team also implemented predictive modeling algorithms to analyze historical data and forecast future demand and supply fluctuations. Overall, this integration of AI-driven models enabled better resource allocation and strategic decision-making for the organization.
- Dynamic Pricing Algorithms: Combining data analytics and AI to analyze market trends and customer behavior, the GCC developed pricing algorithms that could adapt swiftly to changing market conditions. By considering factors like demand elasticity and competitive pricing, these AI algorithms helped maximize profits while staying competitive in the market.
- Data Integration: The team seamlessly integrated diverse data sources, including production, inventory, and demand data, creating a robust foundation for analysis.
- Real-Time Visibility: The tech team also created a dashboard providing real-time visibility into the entire supply chain, enabling them to monitor inventory levels and identify potential inefficiencies promptly.
Results & Impact
$9.1 Bn
Invested in research and development, with 200+ projects under clinical development
