IIM Ahmedabad | India
Sumit Tripathi | Prerna Jha | Ashish Mendhekar | Parul B
Supply chains is one of the backbone and bridges to connect the businesses with the customers as well as the vendors. Often, many businesses end up incurring losses both in terms of physical losses and the opportunity losses from the mismatched in resource planning with the demands as well as the poor supply chain system. ShAIn aims to revolutionise the way businesses, especially the ones with higher number of items and SKUs to manage like supermarket and SMEs, work around with the supply chains. The conventional method of relying on the internal data and industry reports to predict the trends and consumers is often classified as a lag indicator. Shain on the other hand incorporate different external factors that may affect the sales of a particular items from temperature, seasons and time purchased, or the holidays to map the correlation with the existing inventory and derive insights. The autoregression and machine learning model can also be used to create feedback model that can predict the demand for particular items so that businesses can make better decision on which items to stock and which items to clear. ShAin's interactive interface ensures user-friendly search and tracking option for each and every item. It can also help predict and automatically reorder items to fill the warehouse once the items are reduced to the threshold identified. ShAin's open environment makes sure that it always incorporates new information received and updates its model constantly. It also make it easier for people across the firms to connect on the go and access the information easily with the least technical barriers required to access the information and facilitate better decision making process on the ground level.