A story about informed recommendation

Problem Statement - Challenge

A major bottling company in America, renowned for its extensive network of thousands of bottling plants and services, faces significant challenges in demand forecasting. The company relies heavily on manual processes at points of sale, leading to various operational inefficiencies, issues with inventory management, and high unnecessary costs. Despite having existing models, the diverse and large-scale operations of the company require personalized models tailored to each customer to cater to their specific needs. This complexity necessitates a more sophisticated approach to accurately predict demand and optimize operations across their vast network.

Proposed Solution

Based on our discovery, we developed a Prophet model, a leading tool for time series forecasting that considers holidays to predict future sales accurately, factoring in sporadic events and dates. This customization ensures versatility in demand forecasting.

The Prophet model is evolved to create customized models for each client, making highly personalized predictions at an individual customer and product level. For each customer, a detailed regression analysis is performed, providing extremely specific insights that make customers feel heard and valued.

Both the personalized models and general analytics coexist on a single platform where bottling companies can upload their data and generate predictions. This platform facilitates the transition from manual processes to automated, data-driven decision-making. Sales representatives at points of sale can move from simply taking orders to becoming sales advisors who know their customers well and offer personalized recommendations based on regular purchase patterns.

Results

The implementation of Kin Analytics' demand forecasting solution led to significant improvements for bottling companies. Enhanced inventory management was achieved through precise inventory planning, reducing holding costs and stockouts while improving order fulfillment rates, which resulted in higher customer satisfaction.

For instance, companies have reported a sales increase of 20% after implementing these personalized, data-driven strategies.

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