Bordeaux-based Qucit Bike is a software tool dedicated to maximising the efficiency of shared micromobility operations.
Qucit’s software powers micromobility systems of all sizes, covering more than 100,000 bikes in more than 30 cities worldwide.
Boasting reputable partners like Smovengo, PBSC Urban Solutions and Bicycle Transit Systems, Qucit’s solution cuts rebalancing hours by 40% on average while increasing ridership for its clients by 20-50%
Bike share backed by data science
Qucit Bike is built from a team who are not only bike share veterans but who have a deep understanding of data too.
Having dedicated much of his life to data science with a PhD in Theoretical Physics, Qucit Founder and CEO Raphaël Cherrier sees bike share systems as problems that can be solved with objective and logical solutions.
“The way we model bike sharing systems is very close to the way you’d model a physical system – the goal is to define what the optimate state is for the system,” Raphaël tells Zag Daily.
“We make sure that the processes drive this system as quickly as possible towards its optimal state – that it’s relaxed towards an equilibrium point for bike share operations.”
By algorithmically predicting demand, the platform prioritises tasks for operators to optimise each element of their operations, from battery swapping and rebalancing bikes, to broken bike collection, maintenance, and charging stations.
The platform uses an extensive list of calculations. To inform a shared operator of the optimal number of bikes it should have at its stations, Qucit predicts the number of bikes that will arrive and depart from each station during the next 24 hours. Based on that prediction and a computing of the risk that a station will remain empty at any given time, the platform sets a target for the number of bikes an operator should make available at its stations to meet its goals.
The target is recomputed every hour and is based on the operator’s goals – be it maximising revenue, availability and accessibility, KPIs, or meeting Service Level Agreements.
“Our software translates our conversations with customers into numerical formulas and parameters to achieve the optimal point for their operations.”
Qucit isn’t designed to be merely a platform but rather a smart assistant that supports operators to respond proactively to operational circumstances of the day. Every time a driver completes a task set by Qucit, more optional tasks are presented to them to add further value to their operations.
“This flexibility and freedom means the driver can add dynamic intelligence to the proposals made by the software,” Raphaël says.
Case Study: Indego
Indego, a bike share player from Philadelphia, ‘soft launched’ with Qucit’s platform last year before committing to a full roll out in May 2024.
At last week’s NABSA Conference held in Philadelphia, Raphaël explained how Indego has been using Qucit to optimise its operations and reduce labour costs.
According to Indego’s General Manager Nate Bowman-Johnston, the operator’s biggest challenge used to be matching the labour demand required to grow its e-bike fleet – which today makes up 70% of Indego’s 2,500 fleet.
“Managing shared e-bikes was an added burdensome layer to our operational workflow,” Nate says. “The biggest pain point for our staff was figuring out which bikes needed their batteries changed, rebalancing the fleet, where to deploy our team and how to carry out these tasks in the most efficient way. We needed to make sure we had enough staff to be able to keep the customer experience high.”
With Qucit, Indego can prioritise its workflow based on customer demand, and the demand model is designed to keep customer experience at its core.
“Qucit allowed us to take something that was done in a manual way and automate it.”
The result was that Indego no longer needed a full-time Dispatch team. Since using Qucit, these employees have been restructured as field supervisors, and now spend 60% of their time carrying out operational tasks themselves.
This means more batteries are swapped and bikes rebalanced than ever before, and Indego has gained the equivalent of two extra full-time employees in direct field labour.
Qucit also supports Indego in optimising its two different pricing strategies – weekday and weekend. For the weekday strategy, Qucit’s platform prioritises tasks which ensure vehicle availability for Indego’s commuters who pay regular subscription fees. Optimising the weekend strategy involves maximising revenue by targeting stations which see high use from casual riders.
“The impact Qucit has had on our profitability is huge,” Nate says. “Every time we put new bikes on the ground we needed more labour, but using Qucit means we’ve been able to address those labour needs without the huge incremental costs.
“The cost is cheap compared with the cost of hiring extra staff, and that’s been key to our growth strategy as we ensure the accessibility and equity of bike share while maximising revenue.”
Tailored for a global reach
Having conducted projects in over 30 cities around the world, Qucit’s platform is designed to adapt to the unique specificities of each system.
“For example, we have a customer who didn’t want certain stations to be empty for more than 100 minutes,” says Raphaël. “So we evolved our software to accommodate this. Today, if a customer can’t have a station empty for a certain amount of time then we track every minute every station has been empty or full, and when we approach a certain limit we focus on this station.”
For Qucit, there’s an optimal state for every micromobility fleet and operational teams just need to know where to find the sweet spot.
“Bike share is made up of many problem solving puzzles and the team and I have spent hundreds of thousands of hours thinking about how to solve them.”
