Key Highlights
- Our Project focuses on enhancing pharmaceutical sales forecasting to navigate dynamic market conditions and regulatory changes, crucial for the client’s business operations.
- The challenge involved inaccurate and incomplete sales data, significantly compromising forecasting accuracy and impacting inventory management.
- We deployed AI-driven forecasting with advanced data cleansing and imputation to ensure reliable sales predictions. This provided a solid basis for accurate analysis.
- Our solution improved sales accuracy and streamlined inventory management. Automation reduced operational costs and enhanced market responsiveness, giving the client a competitive edge.
Problem Statement
01
Dynamic Sales Patterns: Identifying seasonal trends in pharmaceutical sales is complicated by shifting market dynamics and regulatory changes, demanding robust analysis to distinguish genuine patterns.
02
Data Quality Issues: Inaccuracies and missing values in sales data hinder accurate forecasting, requiring thorough data cleaning and imputation to maintain reliability.
03
Model Complexity and Optimization: Choosing and refining forecasting models for pharmaceutical sales involves addressing various characteristics and ensuring data compatibility, leading to time-consuming processes.
Solution Overview
01
AI-driven forecasting plays a pivotal role in capturing and preserving seasonal sales patterns, ensuring accurate sales predictions.
02
Implemented advanced data cleansing and imputation techniques to address inaccuracies and missing values, ensuring high-quality data for reliable analysis.
03
A range of forecasting models, including ARIMA, SARIMA, and Facebook Prophet, have been utilized to identify the most effective performer.
04
Our team has fine tuned the parameters of selected models and validated their performance against historical data.
05
We have developed automated pipelines for data preprocessing, model training, and evaluation to streamline the forecasting process.
Business Impact
ABOUT THE
Project
This project implements an AI-driven approach to sales forecasting within the pharmaceutical industry. By addressing dynamic sales patterns, ensuring data quality, and optimizing forecasting models, we aim to significantly improve sales accuracy. This enhanced accuracy will lead to better inventory management, cost savings and a competitive advantage through proactive decision-making based on real sales trends.
Tech Stack
Testimonials of Our Happy Clients
Ken Kisner
Global Head of Digital R&D
My experience has been incredibly positive. They were incredibly easy to work with, even with changing requirements.
They are incredibly competitive, but are only a fraction of the cost of US companies.
They are definitely the most professional of the foreign companies that we were looking into.
Nyswyn K.
Director of Software Development
Our journey with OptiSol has been nothing short of remarkable. For over 7 years, we have partnered with them on our digital transformation, and the results have been truly transformative.
Over the years, we have come to trust OptiSol Business Solutions as a reliable and strategic partner.
Al Bagiro
CTO, Auto Insurance Company
The AI engine was completed on time and trained to 90% accuracy. Their eagerness to learn new knowledge impressed us.
Their team is large to handle multiple projects at once, and likes to resolve challenges as well as learn new things. They also welcome regular communications, and of course, needless to say, develop everything in sprints.
Dan Talken
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OptiSol Business Solutions has shown youthful skill and dedication to the projects. Moreover, they have been quick to implement their solutions without sacrificing the quality of each platform.
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CEO MachineVantage
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Rick Tigges
CFO, Bemodo
They are very responsive and able to shift focus quickly as we have needed it for business reasons.
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