AI-driven demand planning & inventory management for the food industry beverage industry
Why are you still relying on time-consuming supply chain planning with Excel?
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An AI-driven demand planning software tailored to the needs of the food & beverage industry
Our cloud solution is perfectly tailored to the needs of food & beverage manufacturers, wholesalers and retailers. We predict the exact demand for your products using historical sales data and secondary data such as weather, high demand events, promotions and many more.
Optimized inventory management to avoid food waste & stock-out situations
Our automated inventory management module reduces your inventory levels while maintaining the right safety stock. This avoids stock-out scenarios on one side and overproduction on the other – the right quantity at the right place at the right time!
Efficient production planning for food & beverage producers
Our automated production planning module provides a cost-optimal production plan. The module decides on the best production plan by balancing the service level, product waste and supply chain costs. This module is also able to collect user feedback on the production plan, which provides a valuable feedback loop to feed the machine learning models continously.
We provide relevant KPIs for your company’s life cycle assessment (LCA)
Our cloud solution offers particularly relevant KPIs for the food and beverage industry, such as food waste and product waste, which help to systematically track and assess the potential environmental impact of your products.
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Frequently Asked Questions
Why is a sophisticated demand planning software so important?
A big problem for SMEs are issues related to poor demand forecasting software. Since demand planning is the first step in supply chain planning, any impact on the demand accuracy reverberates with increased impact through the supply chain planning. SME`s in general suffer more from this problem due to the lack of scale and lack of technical resources to utilize advanced demand planning software. Stockouts and failure to deliver is a major issue for any company due to loss of customer trust and loss of revenues. However, food and beverage manufacturers experience the impacts of poor demand planning software also on the overstocking case, since their products have expiration dates. Next to food waste, overestimating the demand will also lead to increased inventory of items and overproduction on the production line. Although this is a major problem for Small and Medium Enterprises in the Food and Drink sector nearly all enterprises still use Excel as their main demand forecasting software. Without the help of sophisticated & advanced planning tools, 70% of those food and drink manufacturers experience stock-out situations or waste due to poor demand planning.This over reliance on Excel is due to the fact that smaller companies cannot afford the technical and financial resources to acquire and operate sophisticated demand planning software with complex machine learning demand prediction models.
What is our competitive advantage?
Currently on the market there are several players working in demand prediction, but most of the existing companies rely on standard statistical forecasting algorithms. This kind of software performs a statistical fit of existing statistical models on past data and can automatically select the statistical formula with for the prediction. It is important to notice that this decision is made based on the past. Most of these models do not leverage existing Machine Learning techniques in order to do demand forecasting. While you can make predictions based on statistical models (called statistical inference), the statistical models are usually built for inference about the relationships and variables and not for having the most accurate predictions. One clear example is that all statistical models are interpretable – a human can look at the model and infer some information about the process and about the data. Machine Learning, on the other hand, has the goal of having the most accurate predictions. Many Machine Learning models are not interpretable – it is not evident what the weights on the neurons on an Artificial Neural Network mean. By using Machine Learning there is much to be improved on prediction accuracy for demand planning. Although using Machine Learning would make the most sense, Machine Learning is a complex topic, requiring a deep knowledge and understanding of the field to select the best models to be trained and deployed. After using the models for prediction, it is important to monitor performance since a model performance tend to decay over time, via a process called concept drift.
With our technology StreamWiser, we streamline the process of model monitoring and performance tuning. Our technology is able to automatically decide which models are best for a given prediction – and adjust in real time to changes of scenario. You can consider StreamWiser to be your Data Science department focused solely on getting the best predictions possible.
Let our tech do the heavy lifting of demand prediction – training models, selecting models, monitoring performance – so that you can focus on what really adds value: your business.
How much data do we need?
Our AI demand planning software is more accurate the more data you feed into the model to be trained and tested. Thus, for our demand forecasting software to reach its full potential we need at least 6 months of data. But we are aware of the fact, that there are many start-ups out there who are new to this business and are keen on using sophisticated demand planning software from day one as well. For those start-ups, we have customized models. Feel free to contact us we can get a better insight into your exact business situation and understand your needs.
How long is the implementation process for our demand forecasting software?
Depending on the settings of your ERP system the implementation can be done within one hour or one day at the latest.