ANALYSIS ON THE PRESCRIPTIVE PACKAGING FRAMEWORKS IN THE INDIAN DAIRY SECTOR A CLUSTER-BASED ARTIFICIAL INTELLIGENCE APPROACH

Abstract

India is the largest dairy producing market, which produces about a quarter of global supply. It contributes nearly 5% to the national economy, directly affecting the farmers and the small dairy owner. This sector is one of the largest women workforce sectors, having nearly 70% of the total workforce contributing to women. The sector assumes a compounded annual growth (CAGR) of about 6.8% a year. The Indian dairy sector is an example of operational efficiency, having milk collected from farmers and rural dairy owners. The industry is largely dominated by the cooperatives, having Amul and Mother Dairy as one of the largest milk processing units in the world. The country produces about 239.30 million tonnes of milk, with production growing year on year. The White Revolution with the introduction of the project “Operation Flood”, an idea of Dr. Verghese Kurien, India transformed itself from milk-deficient nation to the largest milk producing nation in the world The industry faces several problems in its way. The industry faces the problems of low cold storage, which is not effective in keeping the total national produce cold. Milk is a perishable item having 5-7 days with a temperature of 0oC to 4oC. Other dairy products also have similar on-shelf conversion. Due to this, cold-storage becomes a necessity rather than an option. 20-25% of the total produce is estimated to be wasted due to the inefficiency in the cold storage in India. Dairy products are highly susceptible to bacteria and fermentation, with bacteria forming instantly when kept at room temperature. Packaging becomes an important tool in the daily milk and dairy production. It is important to keep dairy products away from the bacteria and away from direct sunlight. Apart from the utility use, the packaging describes the product effectively. It can be used to generate an emotion in the minds of the v. people. With the growing urban population and the emergence of tier-2 cities, packaging holds all the more importance. The Indian dairy segment, due to its bulk nature, contains homogeneous packaging, ignoring the consumer construct in its entirety. The large scale restaurant, preparing thousands of dishes with various dairy products would require a different packaging than a normal consumer. The large scale nature of the industry ignores the end packaging. This is why this research has been done to ensure that the packaging remains in parallel with the efficient operational machinery of the industry, with recommendation and the implementation of the packaging segmentation based on the previous studies done on the packaging materials. The Wang, Wang & Cho (2022) is taken as the base of the research. The study concluded the utility behaviours of the users on the basis of packaging in the Chinese industry. The study looked at various features which concluded to the emotional and tasteful factors in addition to the product. Four features to doubt during the conjoint analysis were- shape (39.017 percent relative importance), graphics (31.330 percent), label text (15.495 percent) and colour (14.157 percent). During our study, we used elbow analysis to get the optimum number of clusters for which we would have to segment the total database. The database used was taken from the Kaggle community, named Dairy Good Sales dataset. Various clusters were formed using K Means clustering. Four behaviourally distinct consumer-transaction clusters were identified. Cluster C0, the Everyday Mainstream segment, accounted for 38.2 percent of transactions and was characterised by mid-range volume, low unit prices and a balanced channel mix dominated by Mother Dairy and Amul. Cluster C1, the Institutional and Bulk segment, accounted for 19.0 percent of transactions and was characterised by vi. very high quantities sold, the highest average revenue per transaction, and a tilt toward retail and wholesale channels. Cluster C2, the Premium Fresh Urban segment, accounted for 31.5 percent of transactions and was characterised by the highest average unit price, low to medium volumes and short shelf life. Cluster C3, the Shelf-Stable Specialty segment, accounted for 11.2 percent of transactions and was dominated by ghee and cheese, with mean shelf life approaching one hundred days. Perspective analysis done on the basis of earlier studies mentioned in the research to conclude the packaging type used along various clusters. The urban premium sector could use a gabblet of box with a preference in the shape as stated in the previous research having minimalist labels with bold content, optimised for quick commerce like Zepto and Blinkit. The traditional consumers could buy traditional pouches which are efficient in stackability and cost efficiency with warm colour such as Red and gold having concrete graphics, JBL top boxes could respond at a high cost which would be ineffective for the traditional everyday use consumers. Bulk buyers use squared shift containers which would be very useful for stacking up and bulk purchases. Lastly the products with high shelf life can be contained in tin boxes with warm tone graphics to ensure authenticity and richness. The GABDO model (Goals, Analysis, Build or Buy, Deploy, Optimise) and the TCPR readiness model (Time, Cost, Performance, Requirements) were applied to effectively provide a complete plan for the industry to roll out to end consumers. The study bridges the gap of descriptive and predictive contribution of the packaging material in the large Indian Dairy organisation. The limitation of the study remains that the previous study was done on a Chinese consumer sample; although Indian context adjustments were added in the study to give more accurate results.