Optimizing pharma sales using data analytics
Application screenshots
Problem statement
Difficulty in predicting demand: Without taking historical sales patterns and seasonal patterns into account, it can be difficult for a company to accurately predict future sales and plan for future growth.
Limited visibility into future performance: Inability of predicting future performance and identify potential risks or challenges.
Difficulty in identifying key drivers of sales: Challenges in identifying key drivers of sales, such as seasonality, promotions, or external factors like economic conditions.
Complexity in forecasting for new markets: Inability to forecast sales in new markets and identify potential opportunities.
Difficulty in tracking performance over time: Without proper analysis of historical sales data, it can be difficult to track performance over time and identify areas for improvement.
Solution overview
Utilizing AI for sales forecasting can provide a competitive edge for companies in any industry.
Predictive solutions assist businesses in planning for future growth and implementing effective risk management strategies to improve sales.
Many successful companies, such as McDonalds, Colgate, Amazon, and Netflix, have implemented predictive analytics to optimize sales and cater to customer demands.
We have collaborated with a pharmaceutical company to develop an AI-based forecasting solution that accounts for seasonal patterns in sales and generates monthly and quarterly predictions for analysis.
Several models such as ARIMA, SARIMA, and Facebook Prophet were tested and the best performing model was chosen for implementation.
Business impact
Improved decision-making: Provides insight into historical sales patterns and trends, which can be used to make informed decisions about product development, resource allocation, and future growth.
Increased efficiency and cost savings: Provides visibility into future performance, which can help a company to identify potential risks or challenges and take proactive measures to address them, leading to increased efficiency and cost savings.
Better understanding of key drivers of sales: Identifies key drivers of sales, such as seasonality, promotions, or external factors like economic conditions, which can help a company to make data-driven decisions and fine-tune the sales and marketing strategy.
Better forecasting in new markets: By Ability to forecast sales in new markets, which can be beneficial for pharmaceutical companies that are planning to expand their product offerings.
Better tracking of performance over time : Monitor performance trends over time and pinpoint areas for improvement, enabling data-driven decisions and strategic adjustments to sales and marketing efforts.
