Challenges
The manufacturing sector is constantly evolving: we are now witnessing the beginning of a new era, the “4th industrial revolution”, also known as “Industry 4.0”. Technological and digital progress in bringing innovations of such magnitude that executives are forced to review the very core of their industrial strategy.
Solution
Tomorrow’s factories need to be “smart” to cope with the challenges ahead. The production means need to be more adaptive and reactive to demand. Moreover, more efficient use of resources is necessary to guarantee competitiveness and productivity.
Flowlity fits every specificity: automotive, aerospace, food manufacturing, pharmaceutical and health, CPG, …
Flowlity helps you tackle all your supply chain challenges
Consumption forecasts (DDMRP 2.0 intelligent)
Procurement of raw materials or components
Optimization of safety stocks throughout the chain
Inventories optimization (VMI and GPA)
Demand forecast of finished products
Distribution in a multi-echelon network (DRP)
Synchronization and connection with suppliers
Intelligent CPFR
Use cases
Case N°1
Optimization of components stocks of a tier 1 supplier in the automotive industry
Flowlity is now used to plan the procurement of a big name of the CAC 40, a tier 1 automotive supplier. We met two challenges with this manufacturer, minimizing the stock level and increasing the availability of components.
When we launch the tool’s deployment at a customer, we often ask: “Why is it so difficult to know what is the right level of stock?”
Our client’s primary response was: “our customers’ fixed order horizon is five days while we have to commit over two months with our suppliers.” The consequence is that the supply plan must be made based on the consumption forecast.
We also heard:
- our supplier complains of a too high safety stock level because it is on consignment, yet sometimes we go out of stock on their parts
- items we have under our management also have a too high stock level
- our suppliers complain about the quality of our consumption forecasts
- SAP is not well configured and our planning is still done in excel (every planner uses their file, and the transfer of skills is complicated)
Reduction of the overall stock level
The implementation of Flowlity has enabled a reduction of the overall stock level of 40% for items under own management and those managed in consignment.
Consignment suppliers saw their average inventory level decrease. It was then easy for them to accept to follow the requests of our client to increase the safety stock in risky periods, thus ensuring a reduction of shortages.
Thanks to artificial intelligence algorithms, the accuracy of consumption forecasts has also significantly increased. This allows us to communicate to suppliers a more reliable replenishment plan earlier.
Finally, the Flowlity tool has won over users and managers with its pleasant interface and ease of use.
Following this success, we plan to deploy the tool over a larger geographic area.
Case N°2
Optimization of finished products stocks
In this case, we are interested in optimizing stocks of finished products of a manufacturer producing spare parts for the medical industry.
Our customer manages consignment and VMI stocks for his clients, who are large European assemblers. Our client manages inventory in its facilities and VMI stocks at each of its clients.
Artificial intelligence algorithms to decrease inventory and stock-outs
By using Flowlity on our client’s data and applying a combination of artificial intelligence algorithms, we were able to show an overall decrease in inventory of over 45% and a decrease in stock-outs of over 60%.
In a second step, we plan to deploy Flowlity as a trusted third party to recover the production plans of the different assemblers.
This will allow us to increase further the gains observed during the first stage.
Manufacturers who trust us
