Enhanced production planning has helped Snellman optimize frozen stock by over 20% and reduce losses due to expiration dates by over 25%. For the company, this translates into significant cost savings. In the future, artificial intelligence will assist in creating even more accurate production plans, for example, by predicting demand spikes and seasonal variations.
Snellman Group is known for its high-quality products and strong brands. The company’s vision is to be the most sustainable food company, with a value chain where everyone has the opportunity to succeed. Snellman’s partners are also actively guided by their values and ethical principles.
The cooperation between Pinja and Snellman dates back more than a decade, when the development of operations started with production planning. Since then, cooperation has significantly grown and diversified, aiding Snellman in optimizing its operations and achieving substantial cost savings.
With static and rigid production planning based on ERP and Excel, Snellman found it difficult to meet business challenges. In the meat industry, the well-being of animals and the environment must be respected, without compromising on quality.
iPES is expanded to the entire Snellman Group, and will be part of the daily operations. All measures aim to ensure that raw materials are used as efficiently, food is produced to defined quality standards, and that production capacity is adjusted to meet demand.
In the future, artificial intelligence and machine learning will help Snellman to make more realistic production plans, for example by anticipating demand peaks and seasonal fluctuations.
Over 20% diminished cold storage
Over 25 % reduction in waste
The food industry is a complex and sensitive sector. For example, the meat industry must respect animal and environmental welfare without compromising quality. At the same time, production must also be flexible enough to respond to changes in demand – you cannot produce large quantities of meat for storage.
With static and rigid production planning based on ERP tools and Excel spreadsheets, Snellman found it difficult to meet the business challenges.
Snellman Group has undergone a project to modernize manufacturing control in all its factories. For production planning, Pinja’s iPES system was selected and integrated into the existing MES factory system. Over the years, the use of iPES has been extended to all Snellman’s product units.
– iPES is currently used in all production units of Snellman Group. Without it, we would not be able to function at all. The system has paid for itself very quickly, summarizes John Aspnäs, Snellman’s Head of IT.
Today, the system is not only used for production planning, but also for sourcing, optimization of raw materials, i.e. the meat balance, and sales forecasting. All measures aim to ensure that raw materials are used as efficiently as possible, that food is produced to strictly defined quality standards, and that production capacity is adjusted as flexibly as possible to meet demand.
In 2023, artificial intelligence was also harnessed to support sales forecasting. A project is underway to further automate sales forecasting.
– We believe that AI will help us make more reliable sales plans. Forecasting demand or taking seasonal variations into account helps us make more realistic production plans.
With iPES, the working hours required for production planning have been significantly reduced – now planners can come to work at 7am instead of the previous 5am. The planning horizon has also been substantially extended: before the system was introduced, production could be planned a day ahead, but now it can be planned for a whole week. Spikes caused by holiday demand can now be better anticipated and managed.
Improved planning has helped optimize stock levels and shelf life, resulting in clear cost savings. It is now possible to reduce frozen stock by more than 20%, and date losses by 25%. Similarly, at the upstream end of the process, it is now possible to optimize raw material requirements more precisely.
Change management and communication between sales, planning and production in general has become faster and better.
According to Aspnäs, the main reason why Snellman decided to implement Pinja’s solution in the first place was its strong industry knowledge and skilled experts.
– Pinja’s experts were familiar with the problems we were struggling with. The fact that we spoke the same language helped us trust that we could also solve problems together.
Aspnäs recognizes the threats often associated with system acquisition. In his mind, the system is only as good as its users.
– At Snellman, we are committed to developing our operations together. We have built a good team around things, which takes things forward as agreed. The cooperation with management is flexible and we share a common vision for further development, he says.
An optimal production plan is based on factual information on the status, capacity and materials of the supply chain.
Artificial intelligence and machine learning bring new efficiency to production and the supply chain.
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