Optimize inventory in a world of variable demand and supply chain complexity
“Reduce inventory levels and free up working capital, but don’t run out of stock”: such is the eternal dilemma of inventory managers, trying to strike the right balance between demand and supply for hundreds of thousands of spare parts and SKUs, each with a specific demand pattern and different service level requirements.
Getting it right should be a science, but for many organizations, the shortcomings of traditional planning solutions and ERP systems, together with an incomplete overview of the supply chain and a lack of understanding of individual SKU behaviors, make it a bumpy road filled with guesswork.
Unreliable forecasts force demand and inventory planners to stay on the safe side, leading to excessive inventory, costs and waste.
Removing uncertainty is only part of the plan
It’s simply impossible to optimize inventory without a structured methodology and powerful analytics.
Undoubtedly, using machine learning approaches to model the impact of internal and external variables on demand will significantly improve your forecasting accuracy. But reducing forecast errors and removing uncertainty is only part of the solution.
Many other must be considered in order to make optimal planning decisions, such as supplier lead times and disruptions, inventory movements, production orders, inventory costs, quality and production issues, and bills of material. Collecting all this information is often a time-consuming endeavor.
We solve this problem with an integrated planning process combining all available data in a single system, to get a full picture of what is going on and provide automated and up-to-date recommendations on how many items to keep in stock, minimizing costs but not compromising on service level.
Planners get notified when their input is required. They can react quickly to changing conditions and simulate the impact of their decisions on inventory and supply chain costs in real time.
The benefits of AI-driven demand forecasting & inventory optimization
Reduced inventory costs and better cash flow
Less uncertainty thanks to better forecasting
Greater productivity for planners
Greater productivity for planners & operators
Quicker decisions and real-time insights
Demand planning & Inventory Optimization
The European sales and distribution arm of the Japanese bioscience company is using our demand forecasting and inventory optimization solution. The solution is tuned to their specific need to deal with the complexity of changing shelf lives of their products and lot switches.
Multipharma is one of the largest pharmaceutical distributors in Belgium. Our demand forecasting and inventory optimization solutions is integrated with their legacy system helping to manage the daily planning process for more than 40.000. Stock levels were reduced with more than 10%.
Aldipress is the leading distributor of printed press in The Netherlands. Advanced time series analysis and operations research are used to optimize the assortment planning and order generation process for more than 6000 stores. Daily more than half a million forecasts and optimizations are generated by a highly automated demand planning and inventory optimization system.
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The Grain success stories
These clients have chosen to optimize their inventory with The Grain.
Combining industrial intelligence and data science.
The way we combine industrial intelligence with our data science skills is what makes us unique: our starting point is your process, not the data. We know how assets work and our domain experts work with you to understand the specifics of your operations. Our data scientists use those insights to translate your business challenge into an analytical use case and ensure the right data and algorithms are used. We build models from scratch or configure our accelerator kits with pre-built model components to meet your specific needs – whichever will give you the best results.