FAQ – Flowlity

Flowlity is an all-in-one solution covering all supply chain planning needs, from forecasting to operational, with the help of artificial intelligence. Key features include: Demand Planning: Flowlity generates reliable sales forecasts by leveraging your historical and external data. Its probabilistic forecasting algorithm produces multiple 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 stock levels (safety stock, minimum/maximum stock) for each item and location. Taking into account variations in demand and supplier lead times, Flowlity calculates dynamic replenishment thresholds. Intelligent alerts warn you of imminent stockouts 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 MOQ – minimum purchase quantities, lead times, capacities). The planning engine aims to ensure product availability up to +50% higher by avoiding shortages while reducing excess stock. • Production Planning: For manufacturers, Flowlity allows you to build an optimal production plan 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 projection 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 allowing the planner to retain control over important decisions. Supply Chain managers appreciate this approach, which combines time savings (reduced manual tasks) and improved 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: • Forecast demand (and its variability) over the replenishment horizon – from your history, commercial forecasts, AI demand sensing, etc. • Current and ongoing stocks – available stock, supplier orders already placed, customer orders in portfolio (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 subject to delays, the system can increase the buffer stock. • Purchasing constraints – MOQ, batch size, pallet packaging, order frequency, etc., as mentioned above. Orders below the MOQ will not be placed and the required multiples will be respected. • 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.

Flowlity and DDMRP (Demand Driven MRP) share a common goal: to better position buffer stocks to absorb uncertainties and avoid the bullwhip effect in the supply chain. However, their methodological approaches differ significantly. DDMRP is a deterministic method that defines stock buffers at fixed decoupling points and adjusts these buffers mainly according to predefined rules (green-yellow-red colors based on consumption, for example). This works well for products with relatively stable demand, but can show its limitations on products with high volume volatility. Flowlity, on the other hand, adopts a dynamic and probabilistic approach: the solution continuously calculates optimized safety stocks based on updated consumption forecasts and uncertainty assessment via AI. In practice, Flowlity will dynamically adjust your buffer stocks based on detected risks (sudden increase in demand, supplier delays) rather than sticking to a fixed buffer size until the next review. This is a “flow-driven” approach where buffers are recalculated frequently thanks to forecasts and early detection of variations, whereas classic DDMRP often provides for a more spaced periodic review. Note that Flowlity also identifies critical decoupling points in the chain (as recommended by DDMRP) in order to decouple demand and supply in the right places, but the difference is that these points are managed in a more intelligent and adaptable way thanks to machine learning. In short, Flowlity takes the spirit of demand-driven while adding the power of AI to improve responsiveness. Companies that find DDMRP too rigid or manual will appreciate Flowlity's ability to automate the recalculation of parameters (buffers, replenishments) on a continuous basis. (Moreover, according to Flowlity, pure DDMRP "finds its limits" on highly volatile products - this is precisely where Flowlity's AI approach makes the difference by better absorbing uncertainty.)

Yes, we can support the ABC/XYZ classification of your items. Flowlity knows how to prioritize high-value/fast-moving products and low-impact products to adapt planning strategies. ABC analysis classifies SKUs by importance (e.g., A = 20% of products representing 80% of the value), while XYZ analysis classifies them according to demand regularity (e.g., X = regular demand, Z = highly fluctuating demand). Combining the two (9-box matrix) yields categories such as AX (critical products, stable demand) or CZ (low-value products, erratic demand). Flowlity can integrate these segments: for example, apply finer replenishment frequencies to A items with stable demand, and more agile methods for highly volatile C items. In practice, our calculation engine uses a lot of data (value, variability, lead times, etc.) to automatically prioritize SKUs, which amounts to dynamic classification. We also provide reports that highlight items by class, so you can fine-tune your parameters (higher target service level for A, etc.). This approach helps you "prioritize resources, optimize inventory levels, and improve forecast accuracy" for each product category. In short, Flowlity integrates ABC/XYZ principles into optimization to treat strategic and less critical products differently, for better overall inventory control.

Absolutely. Flowlity offers a simulation module that acts as a true digital twin of your supply chain. You can test different scenarios by adjusting, for example, service levels, supply parameters, or the composition of your product portfolio. The idea is to be able to assess the impact of strategic decisions or market changes without risk, before implementing them. For example, you can simulate what would happen if you increased the safety stock level on a category A, or if a key supplier extended its delivery time. Our solution thus allows you to simulate the inventory and purchasing strategy by adjusting service levels, or even to test the parameters of supplier agreements (MOQ, delivery frequencies). Thanks to this scenario analysis, you can make your decisions (stock vs. service arbitrations, investment choices, etc.) with full knowledge of the facts. This is a valuable asset for S&OP and risk management: you can visualize the effect of sales growth, a supply disruption or a product launch on the entire chain, and thus be proactive in your action plans.

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 it would 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. With 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 by stock or by order, the tool ensures optimal management of resources and inventory, aligning with your operational model.

Absolutely. Flowlity provides reliable, up-to-date data that can fuel your S&OP process and facilitate decision-making during meetings between sales, operations, and management. The platform provides a consolidated view of forecast demand, projected inventory levels, and supply needs, allowing for a single, quantified reference during S&OP stages (demand review, supply review, etc.). In addition, Flowlity integrates a real-time management module similar to IBP (Integrated Business Planning): ready-to-use dashboards, indicators, and reports provide instant visibility into the health of the supply chain. This helps align operations with strategic objectives—for example, by simulating different scenarios (surge in demand, major supplier delays) to assess their impact on the supply plan and finances. Flowlity doesn't replace your existing S&OP processes, but complements them by adding a layer of analysis through AI and simulation. You can test hypotheses in Flowlity (product launch, promotional campaign, logistics incident) and then discuss the results in S&OP meetings with confidence. Thanks to Flowlity, S&OP becomes more responsive and accurate, which is an asset for medium to large companies facing volatile demand.

Yes, the Flowlity solution takes your operational constraints into account in its replenishment calculations. Specifically, you can set MOQs (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 ensures that the supply orders generated are directly usable, realistic, and aligned with your actual logistics constraints. By reducing split or suboptimal orders, you optimize your transportation and storage costs.

The quality of historical data is a key factor for reliable forecasts. Flowlity therefore offers a data cleaning process prior to modeling. Concretely, this involves identifying and correcting anomalies in your sales or consumption history. For example, we detect outliers (an exceptional sales spike due to a promotion or an input bug), missing or inconsistent periods, and we handle them appropriately. Cleaning involves several steps: standardizing units and formats, removing or smoothing outliers, and imputing missing data if necessary. As a general data cleaning approach describes it, it involves "identifying and correcting errors, filling in missing values, and putting the data into a consistent format" before analysis. Flowlity uses business rules (e.g., ignoring zero sales during a factory shutdown) and algorithms to achieve this. For example, a statistical method can replace an abnormal spike with a value more representative of the trend. Furthermore, our demand forecasting AI is capable of integrating external data (market trends, weather, etc.) and detecting breaks in the history to avoid biasing forecasts. In practice, during onboarding, our teams assist you in auditing your history: we identify unreliable data with you (for example, a reference whose coding has changed during the year) in order to adjust or exclude it. This cleansing phase ensures that the forecasting model is working on a sound basis. Finally, since Flowlity is a learning solution, the cleaning is continuous: over time, the algorithm learns new behaviors and can rule out future anomalies on its own. You, of course, retain control over validating or adjusting any processing of historical data.

New product planning is challenging because there is little or no sales history. Flowlity addresses this challenge by combining human expertise and artificial intelligence. The solution allows the use of analogous (substitute) products or market data to build an initial demand forecast for a new product. Furthermore, Flowlity provides forecasts even for references with very little history by relying on intelligent algorithms capable of generating trends from partial information. Concretely, the planner can manually adjust the initial demand assumptions for a new product in Flowlity (for example, based on the launch of a similar product), then the AI refines these forecasts on the fly as soon as the first actual sales data arrives. This hybrid approach ensures that new product launches are factored into the supply plan, avoiding stockouts during launch while avoiding overstocking a product whose success is still uncertain. Flowlity therefore ensures agile planning of new products, highly appreciated in retail as well as in B2B trading where range renewals are frequent.

Flowlity was designed as a collaborative platform connecting the various links in the supply chain, particularly between a client (manufacturer, distributor) and its suppliers. In concrete terms, the solution can act as a trusted third party where suppliers and customers share information transparently. For example, suppliers can access (via a portal or dedicated interface) consumption forecasts or supply needs that concern them, and thus better anticipate upcoming orders. Similarly, Flowlity allows suppliers to track performance (on-time performance, reliability) and trigger alerts in the event of potential delays. This shared visibility helps quickly adjust plans: if a supplier reports a capacity constraint or a longer lead time, Flowlity readjusts recommendations to avoid a disruption downstream. In addition, the platform offers the possibility of collaborating on supply plans: online validation of order proposals, exchange of comments, jointly approved modifications, etc. This eliminates the need for multiple email and Excel file exchanges and makes supplier-customer relationships more reliable. For both B2B distribution companies and manufacturers, this improved collaboration means fewer unforeseen events and a more agile supply chain. (Because Flowlity is a cloud-based solution, your partners can easily connect—under the control of your administrators—to share this data. Contact us to learn how to implement supplier collaboration on Flowlity in your context.)

Flowlity was designed to deliver rapid benefits at a controlled cost. First, in SaaS mode, you don't have to finance heavy infrastructure—a simple subscription and light integration are sufficient. Second, concrete results generally allow you to quickly justify the investment. For example, Saint-Gobain estimated a return on investment in less than 18 months after observing a 27.6% drop in stockouts and an 11% reduction in inventory thanks to Flowlity. Similarly, La Redoute reduced its packaging inventory by nearly 50% on average after implementation—significant savings. To compensate for the lack of IT resources, Flowlity offers comprehensive support: our teams can handle a large part of the integration (ERP data extraction, configuration, etc.), which frees up your technicians. For example, we can start with a Proof of Concept using your existing data: during one project, a client tested our tool on 6 months of supplier history and was convinced by the reliability of the forecasts and the inventory reduction achieved in a few weeks. In short, even with a tight budget and busy teams, you can initiate the project on a small scale and gradually ramp up. The rapid gains in performance (improved customer service, freed up time for suppliers, etc.) will make the investment profitable and appreciable from the first months.

During a Flowlity project, your teams are obviously involved, but Flowlity is committed to minimizing the internal workload thanks to its turnkey support. Here are the main roles and implications on the client side: • Project manager / Internal sponsor: It is important to appoint a project manager on the company side (often a Supply Chain manager or an IS supply project manager) who will be the main contact with Flowlity. Their role is to coordinate internally (mobilize the right people, validate business decisions) and monitor progress. This role is typically expected on any project, with a moderate workload (a few meetings per week). • IT team (DSI): Since Flowlity is a SaaS software, the IT effort is mainly focused on extracting data from your source system (ERP, WMS, etc.). Your IT teams will need to provide Flowlity with the necessary data (usually via automated exports, SQL views, or API opening). Flowlity offers standard connectors for common ERPs, which significantly reduces development work. The IT department must also ensure that security and compliance are respected (see Integration & Tech section). In short, the IT department is called upon at the beginning of the project to connect the systems, then on an ad hoc basis to validate the flows and updates. • Supply Chain business experts / Key users: These are your planners, demand planners, pilot suppliers who will work with Flowlity. Their involvement is crucial to configure the business rules in the tool (for example, validate product families, supplier groupings, constraints such as MOQ or supply frequency) and especially to test and validate the recommendations. During the acceptance phase, they are asked to compare Flowlity's proposals with their current practices, identify gaps, and provide feedback. This step allows us to adjust the tool so that it matches the reality on the ground. Typical involvement is a few hours per week for these key users during the heart of the project. Once the tool is in production, these same people will be the main users of Flowlity on a daily basis. • Supply Chain / Demand Planning Management: Management plays a sponsor role (providing the impetus and objectives – e.g. “reduce stock by 20% without degrading service”) and change management. It is important that management leads the project, communicates internally on the expected benefits, and supports the process change. Concretely, this involves regular updates, possibly participating in a demonstration at the end of the project to mark adoption. Flowlity, for its part, takes care of most of the technical and methodological work: configuration of the AI, advanced settings, proper functioning tests. Our business consultants will guide your key users to define the right parameters (e.g. forecast freeze horizon, replenishment policy, etc.) based on best practices. In short, your teams bring the business knowledge of your company, and Flowlity brings the tool and supply chain expertise. The project is a close collaboration, but one that's calibrated so your employees can continue to perform their daily tasks at the same time. Many of our clients are reassured by the light internal footprint: no need for a full-time army; just a few key people are enough to successfully implement the project. (Our methodology includes short, effective workshops so as not to monopolize your resources—we'll explain all this to you in detail at the project launch.)

Yes, Flowlity offers a POC (Proof of Concept) as part of its commercial approach. We understand that it is important for a company to concretely validate the benefits of the solution before fully committing. A Flowlity POC generally takes place over a few weeks and allows us to test the solution on a small but representative scope. For example, we can choose a selection of items or a product category, in one or two pilot warehouses, with a few suppliers, in order to simulate the complete operation (from forecasting to procurement recommendations). How does it work? We define the POC objectives together (e.g., verifying that we can reduce stock by X% on family Y while reducing stockouts, or observing the savings in planning time on a given process). Your teams provide the basic data for the chosen scope (sales history, current stock, current orders, etc.). The Flowlity team configures the tool for this scope and then delivers the results to you in the form of a report and a feedback workshop. Specifically, you'll be able to view the forecasts generated by Flowlity's AI, safety stock recommendations, and replenishment proposals, and compare them to your current practices. Often, this POC highlights quick wins: for example, identifying obvious overstocks or preventing a future shortage that the previous method hadn't anticipated. The POC is also an opportunity for your users to experience the Flowlity interface for the first time. They can log in, explore the dashboards, and understand the logic of alerts and recommendations. Their feedback is valuable and is taken into account to refine the configuration if we decide to pursue a widespread deployment. In terms of investment, a POC is offered at a reasonable cost and in a time-limited format, to facilitate your decision. The goal is to give you confidence in the solution. If the POC results are conclusive (which is generally the case), you can then extend to other areas by capitalizing on what has been learned. If not (for example, if the POC revealed unforeseen constraints), you have the freedom to reevaluate the project. In any case, it's a win-win situation. Many of our current clients have gone through a POC that has convinced operational teams and management thanks to quick wins demonstrated in real-life situations. (If you are interested in a POC, contact us: we can define a scenario adapted to your specific challenges and propose a rapid action plan.)

The duration of a Flowlity project can vary depending on the scope and complexity of your supply chain, but on average, we find that projects are much shorter than traditional supply chain tool implementations. Typically, an initial Flowlity deployment on a first scope (for example, a product family or a pilot warehouse) takes between 8 and 12 weeks. During this period, the main steps include: project scoping and objective definition (1-2 weeks), data integration from your ERP into Flowlity and initial testing (4-6 weeks), parameter adjustments and user acceptance (2-3 weeks), and then go-live on the defined scope. For a global deployment (multi-warehouses, multi-subsidiary), the project can extend over a few additional months, often divided into waves. For example, after a successful initial pilot implementation, other product categories or other sites are rolled out, which can bring the overall project to 4 to 6 months in total. This remains very fast compared to traditional APS solutions. Flowlity relies on an agile approach: we deliver concrete results quickly, then we scale up. This way, your teams quickly see the benefits (for example, a reduction in inventory or better availability on the pilot scope), which creates buy-in to continue. Note that thanks to Flowlity's SaaS architecture, production launches are simplified (no software deployment on your servers, just a connection to the data). Our experience shows that even large companies (several hundred thousand references) have been able to have an initial set of operational Flowlity recommendations in around 3 months. Of course, each project has its specificities: if your data requires significant cleaning work or if you decide on a very broad functional scope from the outset, this can extend the duration a little. But in all cases, Flowlity's objective is to deliver value as soon as possible. (Concrete example: Sport 2000, a retailer, started its collaboration with Flowlity on an S&OP angle and saw results within a few months. Similarly, other industrial clients were able to see rapid gains. We can provide you with detailed timelines and examples during a personalized exchange.)

Feedback shows significant gains thanks to Flowlity, both in forecast accuracy and in inventory reduction and service rate improvement. On average, our customers observe up to 60% inventory reduction and a 50% improvement in product availability by leveraging our solution. For example, La Redoute was able to reduce its average inventory of packaging consumables by nearly 50% in one year of use. On the forecasting side, Flowlity continuously improves demand reliability. During a deployment at Saint-Gobain, consumption forecast reliability reached 95.4% (measured by comparing it to actual sales at 3 months) and stockouts decreased by 27.6%, while lowering inventory levels by 11% compared to previous practice. These operational results translate into a rapid ROI: Thales estimates the return on investment for Flowlity at less than 18 months. Other clients, such as the Lemoine Group, aimed to reduce their inventory by €1 million and achieved this goal faster than expected, largely thanks to Flowlity. In addition to the figures, the organizational benefits are worth noting: planners save time (fewer emergencies to manage, more reliable planning), which allows them to focus on higher value-added tasks. The service rate improves, increasing customer satisfaction and revenue (fewer sales lost due to stockouts). In summary, with Flowlity, you can expect less inventory, fewer stockouts, more sales – and therefore financial and operational optimization of your supply chain from the first year of use. Indicators such as inventory turnover, OTIF (On Time In Full), and service level are seeing significant improvement thanks to the increased reliability of forecasts and the continuous optimization of supplies.

Excel and ERPs are valuable tools but have limitations for advanced planning. Two out of three companies still use Excel in their supply chain, but this reliance results in manual and error-prone processes. An ERP manages daily transactions, while Flowlity provides dedicated planning intelligence: automating 95% of repetitive tasks, detecting anomalies, and proactively adjusting them. With Flowlity's AI, your historical and MRP data is converted into probabilistic forecasts and optimized recommendations. In practical terms, this means fewer Excel sheets to update and more informed decisions. By adopting a specialized tool like Flowlity, you move from reactive management to proactive optimization of your supply chain, resulting in reduced inventories and a better service level.

Yes: calendars (working/closing days of suppliers) can be configured, and the start/end of life dates of the products are taken into account to enable or disable supply recommendations for these references. These technical parameters are configured once in the system and are then automatically taken into account by the algorithm when calculating needs.

Flowlity complements your ERP, it doesn't replace it. A newly deployed ERP manages your master data (orders, inventory, etc.), and Flowlity plugs into it to provide a layer of intelligent optimization. Our solution integrates with existing ERPs to enrich planning: for example, it uses the ERP's MRP data and cross-references it with predictive algorithms to offer dynamic inventory and alerts in case of risk. IT integration is simple and fast: Flowlity is a cloud platform, connected via API, which allows for rapid deployment without disrupting your existing systems. In practice, our customers find that Flowlity helps them "regain control over ERP parameters", for example by optimizing reorder points or stock security levels. Even if your ERP is new, you can therefore accelerate its ROI by adding Flowlity to reduce excess inventory and avoid stockouts. Flowlity seamlessly interfaces with your environment – “integrates with ERPs to reduce disruptions” – without excessive workload for your IT teams.

Yes. Flowlity is a user-friendly SaaS solution that doesn't require a large IT team to run. The tool has been designed to be easy to set up and simple to use: our customers confirm it is "user-friendly, easy to implement" and "very easy to use", while providing effective inventory control. For a small supply chain team, this means you can be up and running quickly, without lengthy training or advanced technical skills. What's more, Flowlity isn't a black box: the results are understandable by business users, allowing your team to make better decisions independently. In short, even a small team can benefit from advanced planning without increasing its workload, and focus on what matters most – analysis and optimization – while Flowlity automates the tedious tasks.

Flowlity is a SaaS solution, based on a subscription. A one-time implementation fee is added upon contract initiation. The subscription price is determined by the number of SKUs or inventory value, depending on the nature of the customer's business.

The solution is available in French, English, Spanish and Russian

Flowlity is an all-in-one solution covering all Supply Chain planning needs, from forecasting to operational, with the help of artificial intelligence.

Among its main features are:

• 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 stock levels (safety stock, minimum/maximum stock) for each item and each location. Taking into account variations in demand and supplier lead times, Flowlity calculates dynamic replenishment thresholds. Intelligent alerts alert you to imminent stockouts or overstocks, so you can act proactively.
• Supply Planning: Flowlity develops replenishment proposals for your warehouses or stores, synchronizing upstream and downstream. You view suggested orders to suppliers or recommended production orders, adjusted according to constraints (e.g. MOQ – minimum purchase quantities, lead times, capacities). The planning engine aims to ensure product availability up to +50% higher by avoiding shortages while reducing excess stock.
• Production Planning: For manufacturers, Flowlity allows you to build an optimal production plan 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 projection 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 keep 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.)

Tech

• AI is a set of algorithmic systems capable of learning from data and making decisions or recommendations.
• In the context of the supply chain, the paradigm of good inventory management is crucial to avoid overstocks, stockouts, and maintain an optimal level of service. This is why our research teams have developed our own AI, which allows us to address the following topics: Probabilistic demand forecasts Optimized recommendations based on estimation and reasoning around the chosen risks Processing data in a contextual manner Recommendation of similar products Dynamic pricing
• The data used to predict future stocks is of two types. We use internal company data since the Flowlity solution integrates with an ERP, as well as external data (weather, economic data, etc.)
  

Dora: For my industry, I don't think it works, it's very specific I do MTO, I don't have stock We are a small team, I'm afraid it will be too expensive for us If I just want to reduce stocks and not have a stockout problem, the ROI might not be interesting enough I already have a solution in place that looks like this I already have technical projects underway so no bandwidth for that, let's talk about it later I've been doing this job for a long time, I know what I'm doing, it works very well We have just implemented / are implementing an ERP, I already want to see what it brings, maybe I don't need more than that No budget for this year Too expensive the first year if license + project to pay. I'm afraid the implementation will be too time-consuming, we're a small team VS We're in MTO (Make to Order) mode and not MTS (Make to Stock), so there's no inventory to manage. It's already working very well with the tools we have in place. The IT teams are overwhelmed, so it's not possible to add new projects currently. No budget has been voted for an APS this year. We're in the middle of changing and implementing a new ERP. I've been in this business for a long time; I know what I'm doing and it works. AI won't change that. Our structure is too small for this type of investment. The price is too high; it costs almost as much as our ERP, with much less functionality than an ERP => JB

As a modern cloud-native application, Flowlity is highly scalable and can handle large volumes of data without performance loss. We support mid-sized companies with a few hundred SKUs as well as large groups managing millions of references and complex logistics networks. For example, at a multi-brand distributor, one of the configurations processed included "more than 1.2M SKUs." This complexity was successfully modeled by Flowlity. Our customers such as Sport 2000, EDF, and Saint-Gobain use Flowlity across large scopes, which illustrates its robustness. In terms of volume, the platform can absorb years of sales history, hundreds of thousands of order lines, and daily stock updates without any problems. The cloud architecture (hosted on secure servers) dynamically allocates the necessary resources based on the load: distributed computing, optimized database, etc. So, even if your item or database doubles in size, the solution adapts. In addition, the calculation frequency is adjustable: forecasts and plans can be recalculated daily, or even in real time for certain indicators, without clogging the system. In short, whether you have 100 SKUs or 10M SKUs, Flowlity can manage them with the same efficiency. Scalability has been proven by our production customers, and we continue to optimize performance to process ever more data (for example, integrating IoT data, real-time logistics flows, etc. in the future). So you can evolve with confidence, the solution will support the growth of your business in volume and complexity. Do you have other questions? If this FAQ has not covered all the points you would like to clarify, do not hesitate to contact us. Our teams will be happy to answer your specific questions, provide you with concrete use cases, or support you in your thinking about optimizing your Supply Chain. Flowlity is aimed at ambitious Supply Chain Directors, logistics managers seeking agility, and more generally at any company wishing to enter the era of the AI-driven Supply Chain. Want to see Flowlity in action? We can organize a personalized demo of the solution with your scenarios. This is often the best way to project yourself and imagine the benefits for your organization. Join the community of companies (retail, trading, manufacturing, etc.) who have already made the choice of intelligent planning. Contact us today to start the journey towards a more efficient and resilient supply chain! —- FAQ Subcategories: Business

Flowlity attaches great importance to support and change management, because implementing a new planning tool is above all a human project. Our project methodology is structured but flexible, inspired by best practices in Supply Chain project management: • Scoping phase: We start with scoping workshops to understand your current planning process, your pain points and your objectives (KPIs to improve, specific constraints). During this phase, we co-construct with you the deployment plan, the functional and technical scope, as well as the project team (on your side and Flowlity's side). • Data integration: Very quickly, we move on to the integration part. Our data experts work with your IT department to connect Flowlity to your systems (via data export, API, etc.). We use test datasets to ensure that everything is consistent. This step is done in parallel with the next phase. • Configuration and prototyping: Rather than waiting until the end to show something, we set up a working prototype as soon as possible with your data. This allows us to validate the first forecasting and optimization results in Flowlity. We adjust the parameters (calculation periods, demand segmentation, stock policy, etc.) in collaboration with your key users. Rapid iterations allow us to achieve a satisfactory scenario. • Training and user testing: Once the tool is configured on the target scope, we train your end users. The training is concrete, on your data, so that they can immediately project themselves. Then, we launch a test phase where your planners use Flowlity in parallel with their old system for a cycle (a few weeks). They compare the decisions proposed by Flowlity and their usual decisions, and give us feedback during regular updates. This double run phase is crucial to gain confidence. • Phased production: When everyone is comfortable, we formalize the switchover: Flowlity becomes the reference tool for the scope, and the old operating mode is stopped (or kept as a backup at the beginning if necessary). We remain very present during the first weeks of production to help refine if necessary and ensure success. • Post-deployment monitoring: After the go-live, the project is not abandoned. Flowlity offers regular monitoring (for example, monthly steering meetings) to verify the achievement of objectives, analyze indicators (stock reduction, improvement of the service rate, etc.), and process any new requests. In addition, as the solution evolves, we keep you informed of new features that could be useful to you. This methodology is led by an experienced Flowlity project manager, with the support of data and supply chain consultants. It is adapted according to your constraints: for example, if you prefer a big bang across the entire scope, this is possible (although we recommend gradual implementation). If you have periods of high activity (seasonal peaks) where you need to take a break, we take this into account in the planning. The idea is to work hand in hand with your teams, gradually transferring skills. At the end of the project, your users are autonomous on the tool, and our support teams take over for any future assistance. In summary, the implementation of Flowlity is a structured, collaborative, and results-oriented process, where each step aims to ensure that the tool integrates perfectly into your processes and that your teams adopt it enthusiastically. (Customer testimonials are available to illustrate our project approach and the successes achieved – do not hesitate to consult them or ask us for an introduction.)

Yes – it’s even one of Flowlity’s founding principles: providing AI that can be explained and understood by the humans who use it. We know that in the Supply Chain, planners and managers need to trust a tool’s recommendations, and this requires understanding the “why.” Flowlity was therefore designed not to be a black box, but rather an educational tool as well as a decision-making tool. Concretely, how does this manifest itself? In the Flowlity interface, each forecast and each recommendation is accompanied by explanatory elements. For example, if Flowlity recommends ordering 500 units of item X for next month, the user sees the breakdown of the expected demand: seasonality, trend, promotional effect, etc., depending on the case. The tool also displays a confidence interval around the forecast (for example: central forecast 500, with a low scenario at 450 and a high scenario at 560), which gives an idea of the uncertainty. This allows for the justification of calculated safety stocks. Furthermore, Flowlity provides alerts and justifications. For example: "Risk of shortage in 15 days on this product because recent demand exceeds forecasts by 20%." Or: "Inventory reduction proposed on this item, because its turnover rate has decreased over the last 3 months." Technically, Flowlity's AI uses machine learning models (including deep learning), but the complexity is hidden behind a simple interface. Ensemble learning techniques are also favored, which smooth out predictions and avoid aberrations. And above all, Flowlity sees itself as an assistant: the user always has the option to review a decision. If they don't agree with a recommendation, they can modify it (for example, order a little more or a little less), and the system will take this feedback into account to adjust in the future. It's a virtuous learning loop where the human retains final control. During training, we insist that users understand how the tool works. Without revealing all the algorithmic details, we explain the main principles (probabilistic forecasting, dynamic buffer calculation, etc.). Very quickly, planners see that the tool reacts as they would in many cases, but better because it reacts more quickly and integrates more data. For example, the tool can detect correlations between products that humans would not have seen – but it will display “30% increase in anticipated demand for product A because it is correlated with that of product B on promotion”. This kind of explanation makes AI tangible. Finally, on the question of technical transparency, Flowlity is open to discussing its approach: we publish white papers and articles on our approach (e.g., use of probabilistic vs. deterministic forecasts). Our goal is not to mystify the algorithm, but to make the supply chain smarter collectively. Flowlity users become better at their jobs because they learn from AI feedback. Many report that after a few months, they have a better understanding of their supply chain dynamics (seasonality, impact of promotions, supplier behavior) thanks to the visibility the tool provides. In short, Flowlity's AI is transparent, explainable, and human-friendly. It's a companion that informs your decisions instead of arbitrarily replacing them. This philosophy increases trust and adoption of the solution within Supply Chain teams. (If you'd like to see in practice how Flowlity presents its recommendations and what explanations are provided, we invite you to a demo where you can judge the tool's clarity for yourself.)

Yes, Flowlity is fully GDPR (General Data Protection Regulation) compliant and attaches paramount importance to the security and confidentiality of its customers' data. Here are the main aspects to consider: • Personal data and GDPR: In the context of a Flowlity project, the data handled is mainly supply chain data (products, stocks, sales history, etc.) which is rarely personal. However, if some indirect data contained personnel (e.g. supplier contact names, delivery addresses, etc.), Flowlity contractually commits to comply with the GDPR. Concretely, this means: consent and information on the data collected, data minimization (we do not process unnecessary data), right to be forgotten and return/destruction of data in the event of contract termination, etc. Flowlity can provide upon request a Data Processing Agreement (DPA) which details these commitments, including any subcontractors (cloud host for example) and storage locations. • Secure hosting: The Flowlity solution is hosted on secure cloud infrastructures such as AWS or Azure (depending on the case, and preferably on servers located in Europe to guarantee data sovereignty). These data centers offer guarantees of high availability, redundancy and physical security. Access to the servers is strictly controlled and monitored. In addition, Flowlity segments data by client: each client has its own isolated database, to avoid any mixing or leakage of information from one client to another. • Encryption: All communications between your system and Flowlity are encrypted (SSL/TLS) to prevent any interception (listening) of data in transit. Similarly, data stored in the Flowlity database is encrypted at rest to protect against any illegitimate access. For example, if backups are made, they are encrypted. • Access controls and authentication: Flowlity implements strict access controls. Your users access the platform via secure accounts (strong password authentication, with the possibility of SSO/SAML if you wish to integrate it with your corporate directory). Rights can be managed by roles to ensure that everyone only sees the data that concerns them. On the Flowlity side, only authorized people (for example, the project manager or the support team) can access your environment, and only for maintenance or assistance purposes, with your agreement. These accesses are tracked and limited. • Security protocols: Flowlity follows industry IT security standards. We regularly carry out security audits and intrusion tests via external firms to verify the robustness of our application. The development of new features requires code reviews, particularly on everything related to data access. Flowlity has implemented a vulnerability management policy (security monitoring, regular updates of third-party components, etc.). The company is aiming for relevant security certifications (e.g. ISO 27001) as it grows, and is already applying best practices in its internal organization. • Backup and continuity: Your data on Flowlity is backed up regularly, and the platform has disaster recovery mechanisms in case of a major incident. This ensures that even in the event of a failure, your data would not be lost and the service could quickly restart on a secondary infrastructure. These points are part of our SLA (Service Level Agreement) commitments. In terms of confidentiality, Flowlity undertakes to never share or use your data for purposes other than your project. The data you entrust to us remains your property. If you decide to leave the service, your data will be returned and then deleted from our systems after an agreed retention period. To summarize, security and compliance are pillars at Flowlity, because we work with sensitive clients (industry, distribution, sometimes defense like Thales mentioned in the press). Whether it's GDPR compliance, technical security, or contractual confidentiality, everything is in place to ensure your information is treated with the highest level of protection. (We can provide you with our complete security and GDPR compliance documentation during our discussions, and involve our security experts to answer any specific questions your CIO or DPO may have.)

The solution is available in French, English, Spanish and Russian (soon in German, Chinese and Japanese).

Flowlity's integration with your existing information system is designed to be simple and fast. Flowlity is ERP-agnostic, which means it can connect to any type of ERP or database, whether SAP, Odoo, Microsoft Dynamics 365 (AX/NAV), Sage, or even more specific systems.

Several integration modes are possible depending on your preferences and technical capabilities:

• Connectors and APIs: Flowlity has secure RESTful APIs that allow you to send and receive data. If your ERP can call web services or if you use an integration platform (middleware type), it is possible to synchronize data (orders, stocks, item references, etc.) via these APIs. For example, you can call the Flowlity API to push daily sales history, and in return retrieve replenishment suggestions to integrate into the ERP. This mechanism is robust and real-time.

• Flat files / Secure FTP: For contexts where you prefer to exchange via files, Flowlity supports the automated import/export of CSV or XML files. You can schedule file deposits (via secure SFTP) containing the necessary data, which Flowlity will ingest at a defined frequency (daily, hourly, etc.). Similarly, Flowlity can generate output files (for example, the list of orders to be placed) that your ERP will consume. This method, although less modern than the API, is often quick to implement because it does not require complex development on the ERP.

• Native connectors: For some common ERPs, Flowlity offers pre-developed connectors or ready-to-use scripts. For example, with SAP, we have standard extractors (via IDoc or queries on tables) to retrieve needs and stocks. This reduces integration time since many standard fields are already mapped. In terms of data exchanged, Flowlity generally requires as input: sales or consumption history, stock data, the item repository (with supplier lead times, MOQ, etc.), possibly customer orders in backlog and current supplier orders. And as output, Flowlity returns: demand forecasts, supply proposals (quantities per item/supplier/date), target stock levels (recommended safety stock, etc.), as well as indicators (stock coverage, alerts). The exchange can be adjusted according to your use cases.

The important thing to remember is that the integration effort is minimized with Flowlity. Many of our customers are operational very quickly because we reuse their existing extractions or standard connectors.

Flowlity supports your IT department during this phase and provides complete documentation of its APIs and formats. Furthermore, Flowlity's platform is highly available and designed to handle large volumes of data, ensuring that even file-based integrations of several thousand lines run smoothly. Finally, from an ERP perspective, Flowlity is non-intrusive: it acts as an overlay without requiring any major changes to your ERP processes. For example, if you use SAP, you can continue to create your purchase orders in SAP, simply because they will have been calculated by Flowlity upstream. This smooth integration philosophy facilitates acceptance by the IT department. During the pre-project phases, our technical experts will be able to assess with your team the best integration strategy for your environment to ensure a smooth transition.