Misconception n°1: « I need a lot of data for a successful optimization. »

Unlike Big Data, Machine Learning, and other predictive approaches based on historical data, optimization is part of prescriptive analytics and requires only a small amount of data: just the strictly necessary data to solve the problem, which must be precise and of good quality.

To optimize your operations planning, we only need a list of tasks to be completed (for example, making a delivery for Routing, loading a container for Packing, preparing an order for Picking) and the resources available to accomplish them (for example, respectively vehicles, containers, pickers). The constraints and objectives of the problem are modeled and configured in the software module. The solver will then produce an optimal planning of allocation of tasks to resources; in other words: “who does what, when, and in what order.”

Misconception n°2: « I already have a Management System (TMS, WMS, OMS, APS), so I don’t need optimization software. »

Management Systems (TMS, WMS, OMS, APS, ERP…) and other business software are valuable tools for managing, collaborating, and tracking the flow of goods and services. They provide data digitization and visibility. However, these tools often lack decision-support and automation features for operations planning. They typically don’t natively offer advanced optimization features that ensure the best decision-making among an overwhelming number of possible options.

Highly complementary to these business software, optimization solvers enhance these systems with plug-and-play modules via API, with a best-of-breed approach. They significantly improve decision-making and operational efficiency while ensuring a seamless user experience through native integration.

Already integrated with Management Systems (Acteos, Klareo, Savoye, Urbantz…), we observe significant gains among our users: 30% reduction in operational costs and planning time reduced by 5.

Misconception n°3: « I outsource my transportation operations, so I don’t need optimization software. »

Optimization solvers are powerful decision-support algorithms capable of generating the best transportation plan configuration within seconds, thanks to decision-making AI. These tools tackle even the most complex constraints (tariff grid, threshold effects, carrier equity, cabotage, etc.).

They are especially relevant if you outsource your transport, as they not only help reduce the overall cost of operations but also enable better control over environmental impact. This is achieved through better decision-making on challenges like consolidating shipments, planning optimal routes, preparing carrier tenders, and optimizing the 3D loading of trucks.

Misconception n°4: « I can’t configure the software or modify my solution. »

Far from restricting human control, optimization software enhances the planner’s capabilities by automating the tedious trial-and-error work to find a solution that is not only feasible but also as cost-effective as possible. They also aim to challenge arbitrary choices, often based on habits or common practices.

They actually offer total control, on the one hand through the configuration and direction of the solver’s behavior via the input data set, and on the other hand through partial re-optimizations, by setting part of the solution to accommodate the system’s dynamics. Finally, very short computing times (a few seconds) allow for multiple simulations and a detailed evaluation of the impact of each scenario by comparing the KPIs of each solution.

Misconception n°5: « My problem is too specific to be solved by business software, which cannot take into account all my field constraints. »

Clearly, the expert planner, who has been in the profession for many years, has acquired the know-how to often produce very relevant solutions. The goal is to capitalize on this experience and empower the human with intelligent engines to further refine decision-making. Optimization software also have the advantage of permanence (no holidays or sick days) and accessibility (by simply submitting a data set, you get an optimal solution). Not to mention that manual planning presents numerous pitfalls due to a lack of a global vision of the system, which no human can grasp.

A software solution like Atoptima’s is based on a library of very generic modules, offering the possibility to model any type of constraint, even the most complex and specific, with great reactivity. The solution’s scalability allows for the addition of new constraints over time, without having to start from scratch.

Misconception n°6: « Optimization solvers are for developers; they require extensive software development to solve a specific business issue. ».

Optimization solvers are indeed powerful, sophisticated software engines with advanced algorithmic capabilities. However, the modular nature of the software and the ergonomics of Atoptima’s visualization interfaces make them directly accessible to the user.

In this sense, Atoptima’s solutions bridge the gap between ad hoc tools based on generalist solvers and off-the-shelf tools, combining tailored, responsive and accessible solutions for very complex operational planning problems.

Optimization software are essential components for maximizing operational performance and empowering your teams’ decision-making.

Do you have any question about optimization software and how it works?