For players in the food industry in particular, it is important to identify market opportunities and market risks at an early stage and to plan and calculate them appropriately. More accurate and improved sales forecasts give companies a decisive edge in a very dynamic and volatile market environment.
The most important added value and at the same time the biggest challenge is to know the demand as precisely as possible – in advance!
My area of expertise.
Agnes Tholen
Director Sales & Marketing (ppa.)
Sales planning is a popular area of application for applied AI in the food industry: thanks to the ability of AI technologies to manage even complex interrelationships and evaluations, a fundamentally different, significantly better planning of inventories with more precise forecasts is possible.
As a result, costs are minimized and profit increased, and control of production, demand and capacity is possible in an optimized form. In addition, the company using it is breaking away from person-based planning and from programs that serve as planning aids, such as Excel.
And: Precision and forecast quality are increasing vehemently!
By using AI models, more accurate forecasts can be made by analyzing large amounts of data and identifying complex patterns and relationships in the data.
Traditional forecasting methods are often based on historical data and simple, statistical methods such as trend analysis or linear regression. However, these methods can be inaccurate because they do not account for complex relationships or changes in the data.
AI models, on the other hand, can take into account a variety of factors that can affect forecasting, including seasonal patterns, weather conditions, customer behavior, and other external influences. The models may also be able to update and adjust themselves as new data becomes available.
By using AI, companies can create more accurate forecasts that can help them plan and make decisions. For example, they can make more accurate sales forecasts to optimize their production and inventory levels or anticipate demand for specific products. By improving forecasting, companies can also improve operational efficiency and reduce costs.
Competitive advantages in dynamic markets.
Demand as accurately as possible – in advance!
Minimize costs.
Control of production, demand and capacities in an optimized form possible.
Detachment from person-based planning and from programs that serve as planning aids.
Vehement increase of precision and forecast quality, because the algorithms learn continuously.
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CompanyMind GmbH & Co KG
Marie-Curie-Straße 1
D-26129 Oldenburg
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