Evaluate how much sorting errors cost your community or site. And get an estimate of how much you can save by using Lixo.

The simulator's data is based on national and local sources from ADEME (Modecom reports and Sinoe database), Citeo, and our partnerships. These elements guarantee accurate results tailored to your needs.
Analyze, optimize, save
By deploying Lixo technology, sorting errors are automatically detected in real time. You get a detailed analysis of the quality of your flows, so you can take corrective action.



_FAQ
By simulating the cost of sorting errors, you can appreciate the direct financial impact that sorting errors can have on waste management. This has several advantages.
1. Reduce the lack of visibility on actual management costs: local authorities increasingly need to understand and control the state of waste collection in their areas. Poor visibility of these costs prevents them from optimizing the budget, leading to decisions being taken without a full understanding of the financial impacts.
2. Justifying investments in calls for tender:public calls for tender are becoming increasingly competitive, with higher and higher demands being placed on collectors, making justifying investments crucial to winning contracts.
3. Be aware of the financial impact: sorting errors lead to higher management costs, weighing on local authority budgets. These additional costs are detrimental to the public perception of local authorities, whether in terms of their reputation or the purchasing power of users (with increased taxation).
4. Get a better understanding of blocking points:without accurate data, it's impossible to identify and effectively address problems linked to sorting quality. In short, simulating the cost of sorting errors provides a precise view of the financial impact of poor sorting practices, while offering a lever for improving waste management and encouraging more environmentally-friendly behavior.
All the data used in the Lixo simulator comes from public, national data published by ADEME, Citeo, Modecom and Sinoé. Feedback from our users (private and public collectors) has also helped us to shape the sorting error cost simulator.
To provide the most accurate estimate possible, Lixo has decided to take into account only certain types of stream: residual waste, recyclables and bio-waste. Other streams will be added in the near future for specific rounds.
The main data sources used include:
1. Sorting error rates: The simulator is based on sorting statistics, including observed error rates for different types of stream. These data come from research, field studies and feedback from local authorities and companies.
2. Incorrect waste treatment costs: The simulator takes into account the additional costs that can be generated by sorting errors, in particular the costs of sorting rejects and processing them in suitable channels.
3. Waste treatment revenues: The simulator includes buy-back rates for recoverable materials, as well as support for the packaging EPR sector.
4. Local data: The simulator adapts to local particularities according to the tonnages of the main flows observed in France (RMW, CS, bio-waste) as a function of the number of inhabitants.
Thanks to these different data, the simulator can produce a personalized and realistic assessment of the costs generated by sorting errors, while taking into account the specific features of local authorities.
When you run a simulation of the cost of sorting errors, you are provided with two types of results:
1. The precise cost of sorting errors: this amount represents an estimate of the costs associated with errors. It includes the additional costs of processing incorrectly sorted waste, and any loss of revenue. This figure gives you a concrete idea of the financial impact of your sorting errors to date.
2. A range of potential savings: In addition to the current cost, you'll receive an estimate of the savings you could make by reducing the refusal rate through the use of Lixo sensors and the implementation of targeted action. These sensors make it possible to better analyze and control sorting quality in real time, thus reducing the number of errors thanks to concrete actions.
The simulator not only provides you with an overview of the current costs of sorting errors, but also a projection of the savings you could achieve if you optimized your waste management with technologies such as Lixo sensors, by reducing the refusal rate. These results give you a better understanding of the financial benefits of improving your sorting practices and investing in technological solutions.
Reducing the costs associated with sorting errors depends on the specifics of your territory, the waste management practices in place, and the tools used. However, the key to optimizing these costs lies in the use of reliable and accurate data.
Here are some points to consider:
1. Adapt your practices to the local context: waste management systems vary from one territory to another, both in terms of waste deposits and the organization of collection or treatment . Understanding these specificities is essential for implementing actions to reduce sorting errors that are adapted to your situation.
2. Leverage data to better understand your sorting errors: one of the most powerful levers for reducing your costs is to analyze the sorting error data provided by Lixo. This enables you to identify the type of errors and precisely where and when they occur, and adjust your actions accordingly. Access to a data visualization platform is crucial for measuring progress and assessing potential savings.
3. Use automated tools for better real-time visibility: innovative solutions such as Lixo enable you to collect precise data on sorting quality directly at source. These sensors help identify errors in real time, enabling you to react quickly to improve sorting and ultimately reduce the costs associated with errors.
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Lixo - Sales Manager