Customer Profile

3F Industries Limited (formerly Foods Fats & Fertilizers Ltd), embarked on its journey in 1960 with a single plant in Tadepalligudem. Today, it stands as a distinguished Indian multinational corporation with an impressive legacy of over 60 years. Operating across India and abroad, 3F Industries Limited is renowned for its diverse product range, manufactured across multiple facilities.

With a presence in overseas markets such as Singapore, the Middle East, Vietnam, and West African countries, our client serves a global clientele. Boasting a workforce of over 1500 employees, our client's customer base includes some of the world's most prestigious companies.

The company's extensive portfolio encompasses a wide array of products, including Bakery Fats, Fats for Frozen Desserts, Fatty Acids, Deoiled Cakes, Glycerin, Margarine, Refined Oils, Soap Noodles & Toilet Soaps, Specialty Fats & Confectionery Fats, Stearic Acid, dimer fatty acid, Waxes, and more. Additionally, our client is involved in Power Generation, International Trading in Commodities, and R&D initiatives.

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Problem Statement

A manufacturing company in the FMCG segment had an ERP system implemented which meticulously provided a consolidated sales projection month-wise. This system was used by the plant managers to plan their monthly production. The manufacturing decision, raw material inventory planning, etc. was made meticulously using the data captured by the ERP system. However, the problem was under or over production resulting in revenue loss, customer complaints, and enhanced friction between the sales and operations team. It was a case of decisions turning bad due to a unidimensional view of the data.

To completely understand the information flow and data flow of the current system between multiple stakeholders and departments and bring consistency in overall process flow. Apart from that, it is also critical to mine the existing data and validate it for the readiness to run the statistical analysis.

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Solution

An  AI-based production planning system not only takes the demand requirements as captured by the ERP system but also looks at historical patterns and trends.  Taking into consideration the sales projections vs actual sales, product sales time, the behavioral pattern of sales, external triggers/events, seasonal sales, the pattern of goods movement (ex: goods with sufficient shelf-life vs before expiry dates), etc. our algorithm analyses and recommends the insights about sale predictions. A comprehensive system will also analyze the true sales pattern, interpret the reason for a sale, and provide recommendations for sales strategy.

AI-based

Results

The true power of AI is realized when a holistic view is taken of all of the data. The operations planning system powered by AI helped the plant to move on to ‘in-time on-demand’ production without transferring the inventory to the regional sales team and while meeting the demand of the sales team.

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