Context: In a majority of small and medium-sized Food and Beverage (F&B) companies, sales planning is executed using MS Excel. The inputs for the sales plan, sourced from various sales offices, are aggregated and adjusted based on historical sales averages, marketing promotions, and other key factors. Over time, this process has become increasingly complex, not only due to the expanding range of product categories and Stock Keeping Units (SKUs), but also due to the growing set of internal considerations, such as promotions, offers, and inventory, as well as external variables including competition, and in some cases, even weather – all of which exert an influence on sales. 

Challenge: CEOs of F&B enterprises are uncertain about the effectiveness of the sales planning process. Concerns arise regarding the potential oversight of crucial insights amidst the large volume of data inputs stemming from disparate systems. This lack of certainty is reflected in instances where stockouts in certain locations and surplus stocks in other locations occur concurrently. Further, these organizations encounter difficulties in deploying forecasting models and techniques, owing to the absence of in-house expertise and the unavailability of comprehensive input data in a single place. 

Capabilities: 

• Data centralization: The Spoggle unified analytics platform empowers business users to centralize data from diverse sources into a singular data warehouse, from which they can construct reliable forecasting models to synthesize, analyze, and visualize data from different sources.  

• Forecasting capabilities: The platform provides a variety of forecasting capabilities, encompassing time series analysis and the identification of seasonal trends grounded in historical data. It also offers an array of algorithms, enabling precise predictions that factor in influential elements such as promotions, pricing fluctuations, weather patterns, and stock-outs. 

Features: 

• Predictive modeling capabilities: The Tesser offering Platform encompasses advanced predictive modeling capabilities, enabling users to develop and train machine learning models for predictive analytics. The platform streamlines the preparatory and data-cleansing processes indispensable to accurate forecasting. The consolidation of data from multiple sources is seamlessly facilitated, with Spoggle's data blending and cleansing tools ensuring that the input data is accurate and ready for analysis.  

• Algorithms for businesses of all sizes: Among some of the capabilities that will be available soon are the ability to select from a library of algorithms, including linear regression, ARIMA (AutoRegressive Integrated Moving Average), exponential smoothing, among others, with each contributing to the formulation of accurate predictions. The platform has been designed to accommodate large datasets and intricate forecasting tasks, making it suitable for businesses of all sizes. 

Benefits: 

By adopting Spoggle, F&B companies can achieve the following benefits: 

• Reliable Forecasts: The ability to identify emerging trends and business prospects through reliable forecasts. 

• Enhanced Inventory Management: Prevention of inventory shortages and redundant stockpiles, thereby optimizing inventory management. 

• Elevated Procurement Practices: Streamlined procurement processes and enhanced risk mitigation strategies.