Product Assembly & Ancillary Industries

Product assembly and ancillary industries, often part of the Micro, Small, and Medium Enterprises (MSME) sector, are key employment generators in any economy. Examples include auto parts forging, cold press industries, plastic products manufacturing, toy production, cloth printing and dyeing, leather goods manufacturing, and packaging. Despite their diversity, these industries face common business challenges, such as manpower management, inconsistency in raw material supply, raw material price fluctuations, and managing payment cycles. Data science can offer significant solutions to these issues.

Predicting Price Fluctuations in Raw Material

Raw material price fluctuations can significantly impact the profitability of MSMEs, which operate on thin margins. Data science can create models based on factors like location, weather, logistics rates, and manpower availability to suggest the best procurement methods. These models can also recommend multi-vocational procurement strategies to maintain profitability, helping businesses navigate price fluctuations effectively.

Managing Manpower

Manpower in these industries often consists of gig workers with variable expertise. Data science can build models to efficiently deploy workers, maximizing productivity and ensuring optimal use of human resources.

By leveraging data science, MSMEs can boost profitability and productivity, ultimately resulting in a better return on investment.