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The growing requirement for objective data in public financing applications is not a free administrative constraint. It responds to a logic of responsibility in the use of public funds and efficiency in the allocation of resources.
Funders — whether they are ADEME, regions, departmental councils or the State via the AVELO or CRTE programs — must justify their choices to supervisory authorities, courts of auditors and citizens. Financing a bicycle development that will be used very little is difficult to defend. Conversely, financing a project that meets a proven need and that generates a measurable impact is a robust political and budgetary decision.
Attendance data allows instructors to answer three key questions: Does this project meet a real need? Is the proposed infrastructure properly sized? Will the community be able to measure the impact of the project once completed?
A case that cannot answer these questions with factual data is in a weak position compared to competing files that can. In a context where budgetary envelopes are limited and competition between territories is strong, this difference can be decisive.
Several public funding schemes have explicit or implicit requirements for attendance data.
The AVELO program, deployed by ADEME and local authorities, finances cycling facilities provided that project leaders can demonstrate the expected use and measure the impact after completion. The best rated files are those that rely on existing counts to justify the design and that provide for a post-work measurement system.
Ecological Recovery and Transition Contracts (CRTE) regularly include active mobility components. The instructors of these programs expect numerical indicators: number of cyclists per day on an existing route, growth observed in previous years, projection of use after development. These items should be in the file.
Regional programs to support greenways, cycle routes or structuring cycle paths often require N+1 or N+2 usage assessments after commissioning. These balance sheets can only be produced if a counting system has been put in place.
ADEME calls for projects on active mobility, active mobility funds or even European ERDF programmes systematically include impact assessment criteria. A project that does not include an attendance measure will be penalized during the scoring.
Even when counting data is not explicitly required in the specifications, it is a major differentiating factor between folders. Instructors know how to recognize a serious case from an approximate one.
Before even submitting a financing application, it is strategic to have attendance data on existing routes that will be impacted by the project, or on comparable axes.
This data makes it possible to answer the question: “How many people use this axis today or are likely to use the future layout? ” This information is used both to justify the relevance of the project and to calibrate its dimensions.
For example, if you want to create a greenway between two municipalities, measuring traffic on a pilot section or on a comparable route makes it possible to estimate the number of expected users. If you have an average of 150 cyclists per day on an undeveloped temporary road, you can project an increase of 50 to 100% after development, which gives a credible range of 225 to 300 cyclists per day.
This data should be presented in the file in a structured manner:
The absence of pre-draft data makes it necessary to rely on national estimates or benchmarks, which is always less convincing than a local measure.
The measurement after the completion of the project is just as important as the initial diagnosis. It makes it possible to demonstrate that the development has produced the expected effects, which reinforces the credibility of the community for future cases and justifies the use of public funds with funders.
Post-project data should make it possible to compare the situation before and after development. For this, it is essential to have installed sensors permanently, or at least to carry out equivalent measurement campaigns before and after (same periods of the year, same durations, same locations).
The metrics expected by funders are generally simple:
Some programs impose a deadline for producing the impact assessment: 6 months, 1 year or 2 years after commissioning. It is therefore necessary to anticipate this obligation as soon as the initial file is prepared, by providing the budget and logistics necessary for post-work counting.
Communities that systematically produce quantified impact assessments build a reputation for seriousness from funders, making it easier to obtain grants for the following projects.
A grant application package should include metrics that are clear, easy to interpret, and directly related to the objectives of the funding program.
Basic metrics:
Projected impact metrics:
Context metrics:
These metrics must be presented visually: graphs, curves, summary tables. Instructors have limited time to assess each file. A clear and structured presentation of data facilitates their work and reinforces the impression of professionalism.
To make concrete what it means to “produce usable data for a funding case”, here are examples of metrics that are actually used in files that have obtained grants.
AVELO file for the creation of an urban cycle path:“The measurement on the current axis (shared path) indicates an average attendance of 180 cyclists per day during the week, with a growth of 12% per year over the last 3 years. We project an increase of 60% after the development of the separate bike path, or around 290 cyclists per day.”
CRTE file for an interurban greenway:“The pilot section opened in 2022 recorded an average of 420 crossings per day over the summer season (April-October), 65% of which were cyclists and 35% pedestrians. This attendance places the greenway in the top 20% of French greenways of comparable size.”
Regional file for the extension of a bicycle network:“The three bicycle routes put into service between 2020 and 2023 record an average growth of 18% per year in their use. The proposed new axis connects two employment areas that are currently poorly connected, and should capture an estimated flow of 250 home-to-work trips per day.”
These examples show that metrics don't need to be sophisticated. They must be factual, contextualized and directly linked to the objectives of the project. A well-chosen number is better than a long, rough speech.
The before-and-after structure is the reference format for evaluating the impact of a development financed by public funds. It makes it possible to compare a reference situation (before work) to a target situation (after work) based on comparable data.
Phase 1: Reference measurement before workInstall sensors on the current axis or on a comparable axis for at least 3 months, ideally 6 to 12 months to capture seasonal variations. This measure is the baseline, i.e. the starting point from which the impact will be measured.
Phase 2: Realization of the projectDuring the work, counting may be interrupted or continued depending on the case. If the layout significantly changes the layout, it may be necessary to reposition the sensors.
Phase 3: Post-work measurementReinstall the sensors on the new layout as soon as it is put into service, and collect the data for a period equivalent to phase 1 (at least 3 months). This measure makes it possible to calculate the evolution of attendance.
Phase 4: Comparative analysis and balance sheet productionCompare the two data sets by neutralizing seasonal effects (compare April before work with April after work, for example). Calculate the change in percentage and in absolute value. Identify changes in user profiles if relevant.
This methodological structure should be presented in the grant application file, specifying when and how the measures will be carried out, and when the impact assessment will be sent to the funder. This transparency on the methodology reinforces the credibility of the case.
To maximize the chances of success of an application for a bicycle or mobility grant, here are the elements relating to attendance data that should be included in the file.
✓ Item 1: Diagnostic Data
✓ Element 2: Measurement Methodology
✓ Element 3: Impact projection
✓ Element 4: Post-work evaluation system
✓ Element 5: Visual presentation of data
A file that respects this checklist is immediately distinguishable from files based on fuzzy estimates or unsupported hypotheses. It shows that the community has a serious, methodical and results-oriented approach — exactly what funders are looking for.
If you are carrying out a greenway, cycle path or development project in favor of active mobility and want to structure your financing file with robust counting data, Kiomda can assist you in defining the measurement system and in producing the metrics expected by funders.
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