Supply planning made easy with AI

Yes, these elements are an integral part of the data taken into account.

Flowlity allows you to configure supplier calendars, i.e., your partners' working/non-working days. For example, if a supplier is closed in August or only delivers from Monday to Thursday, the supply plan will automatically take this into account: no deliveries will be scheduled outside of their time slots.

This avoids unnecessary overstocking or waiting for impossible deliveries. Similarly, the solution manages product launch and end-of-life dates.

Our algorithms integrate the item lifecycle:

You can indicate that a new product starts on a certain date (with a possible ramp-up profile) or that an existing reference will be obsolete from a certain date. Flowlity “tracks product lifecycles (new products, end of life, etc.)” and adapts forecasts and recommendations accordingly. For example, as an end-of-life approaches, the tool will gradually reduce replenishment proposals and then stop generating them beyond the end date, to avoid unsold items.

Conversely, during a launch, Flowlity can use analogies (similar products) or market data to initialize the forecast, so as not to start from scratch. In short, calendar constraints – whether they come from suppliers or your product cycle – are well managed by Flowlity.

This ensures realistic planning aligned with operational realities.

Absolutely.

Even without finished goods inventory, upstream planning remains crucial.

In Make-to-Order (MTO) mode, raw materials and production capacity must be managed to meet customer orders on time.

Flowlity helps you anticipate these needs.

Our forecasting algorithms integrate economic and historical data to estimate future demand, even in the context of custom orders. This allows you to prepare your supplies of critical components and smooth out the production load.

In addition, the solution offers scenario simulation capabilities: you can test the impact of a sudden increase in orders or a supplier delay on your schedule. With a supply chain optimization tool, MTO manufacturers make more data-driven decisions, adjust their capacity more precisely, and become more responsive to fluctuations.

In short, Flowlity secures your MTO supply chain by avoiding component shortages and reducing lead times, while limiting unnecessary surplus.

Absolutely.

Even without finished goods inventory, upstream planning remains crucial. In Make-to-Order (MTO) mode, raw materials and production capacity must be managed to meet customer orders on time. Flowlity helps you anticipate these needs. Our forecasting algorithms integrate economic and historical data to estimate future demand, even in the context of custom orders. This allows you to prepare your supplies of critical components and smooth out the production load.

In addition, the solution offers scenario simulation capabilities:

You can test the impact of a sudden increase in orders or a supplier delay on your schedule. With a supply chain optimization tool, MTO manufacturers make more data-driven decisions, adjust their capacity more precisely, and become more responsive to fluctuations. In short, Flowlity secures your MTO supply chain by avoiding component shortages and reducing lead times, while limiting unnecessary surplus.

Yes, the Flowlity solution takes your operational constraints into account in its replenishment calculations.

Specifically, you can set MOQ (Minimum Order Quantity), batch sizes, purchasing units, and even full truckload constraints.

The planning engine will verify that all these constraints are respected in order proposals.

For example:

If you have an MOQ of 100 units or a truck that only leaves when full, Flowlity will integrate these rules and group requirements accordingly. Flowlity's Order module allows you to group requirements by supplier and ensure that conditions such as MOQs, batch multiples, or truckload are properly applied. This means that the supply orders generated are directly usable, realistic, and aligned with your actual logistical constraints.

By reducing split or suboptimal orders, you optimize your transportation and storage costs.

Yes, Flowlity is suitable for both make-to-stock (MTS) and make-to-order (MTO) models. In Make-to-Stock mode, the solution uses its forecasting algorithms to project future demand and recommend optimal stock levels, as for any stocked product. For example, it calculates dynamic safety stocks to ensure a high level of service while minimizing dormant stock. In Make-to-Order mode, where production or procurement is triggered only upon customer order, Flowlity adapts by using firm orders as demand input. In this case, the tool will primarily optimize the components, raw materials, or intermediate products needed to fulfill these orders on time, ensuring the availability of upstream supplies. Flowlity can manage hybrid workflows where some references are in MTS (stock built on forecast) and others in MTO (produced or purchased on demand), which is common in manufacturing and distribution. Thanks to flexible settings, you can define the appropriate planning mode per item or product family, and Flowlity will adjust its behavior accordingly. In short, whether you need to plan on stock or on order, the tool ensures optimal management of resources and stocks, aligning with your operational model.

Flowlity is an all-in-one solution that covers all supply chain planning needs, from forecasting to operational planning, with the help of artificial intelligence.

Its main features include:

• ‍Demand Planning: Flowlity generates reliable sales forecasts by leveraging your historical and external data. Its probabilistic forecast algorithm produces several scenarios and identifies the most likely one, also providing a confidence interval to visualize uncertainty. This helps you anticipate demand more accurately than with traditional methods.‍
• Inventory Optimization: The solution recommends optimal inventory levels (safety stock, minimum/maximum inventory) for each item and location. By taking into account variations in demand and supplier lead times, Flowlity calculates dynamic replenishment thresholds. Intelligent alerts alert you to the risks of imminent shortages or overstocks, so you can act proactively.‍
• Supply Planning: Flowlity develops replenishment proposals for your warehouses or stores, synchronizing upstream and downstream. You view the orders suggested to suppliers or the recommended production orders, adjusted according to constraints (for example, MOQs – minimum purchase quantities, lead times, capacities). The planning engine aims to ensure product availability up to +50% higher by avoiding shortages while reducing excess inventory.‍
• Production planning: For manufacturers, Flowlity allows them to build an optimal production plan while taking into account capacity constraints. The tool can integrate bills of materials (BOM) and calculate net component requirements. It helps determine where to position buffer stocks on multi-level chains to maximize OTD (On Time Delivery) and make existing MRP more reliable.‍
• S&OP and reporting: As mentioned, Flowlity offers real-time monitoring dashboards and key indicators (KPIs) for supply chain management. These reports help align departments during S&OP and make data-driven decisions thanks to global visibility of the situation (stock coverage, shortage projections under different scenarios, etc.).‍
• Supplier-customer collaboration: Flowlity offers a collaborative space to share forecasts, needs and order confirmations with your partners. This streamlines communication and reduces uncertainty throughout the supply chain.‍
• Contingency management and resilience: Thanks to AI, Flowlity detects disruption signals early (abnormal demands, announced delays) and suggests corrective actions (for example, bringing forward a supplier order or repositioning stock from one site to another). This intelligent automation helps teams navigate uncertainty and make the supply chain more resilient to unforeseen events.

In summary, Flowlity stands out for its algorithmic power (probabilistic forecasts, multi-echelon optimization) and its ease of use.

It automates up to 95% of planning activities while letting the planner retain control of important decisions. Supply Chain managers appreciate this approach which combines time savings (reduced manual tasks) and better performance (stock reduced by up to -60% in some cases while improving the service rate). ‍

For more details on each module, we can provide you with a dedicated presentation – do not hesitate to contact us to find out more.

Flowlity's calculation of supply recommendations is multi-criteria.

Our stock sizing and ordering algorithm takes into account the following parameters:

• ‍Forecasted demand (and its variability) over the replenishment horizon – derived from your historical data, commercial forecasts, demand sensing AI, etc.‍
• Current and current stocks – available stock, supplier orders already placed, customer orders in the pipeline (to calculate a net requirement).‍
• Supply lead times – supplier or production lead time, to cover the period until the next delivery. The longer the lead time, the more safety stock the algorithm must provide.‍
• Target service level – you can define a service rate (e.g., 99% on product A, 95% on B, etc.). Flowlity calculates the corresponding safety quantities by probabilizing the risks of shortages.‍
• Supplier variability – the reliability of delivery times or quantities. For example, if a supplier is unreliable or prone to delays, the system can increase the buffer stock.‍
• Purchasing constraints – MOQ, batch size, pallet packaging, order frequency, etc., as mentioned above. We will not order below the MOQ and we will respect the required multiples.‍
• Capacities or schedules – the supplier's production or delivery capacity (working days, holidays), as well as your own constraints (available storage space, monthly budget).

By combining these parameters, Flowlity calculates when and how much to order for each item and stock point, so as to avoid both shortages and overstocks.

In short, the recommended quantities are the result of a multi-parameter optimization integrating your service objectives, anticipated demand and all your logistics and supplier constraints.