Powered by BICO: Increased Demand

The impact of COVID-19 on bikesharing operations has initially been mixed with the longer term outlook looking relatively positive.

While the face of bikeshare systems will likely look the same, operations will undoubtably look very different as we enter the ‘new normal’, further proof that the past is not a good indicator of the future.

In systems across the world users are now utilising bikeshare as one of their primary modes of transport more than ever before, will system usage surpassing even pre-COVID levels. This is due in-part to city policy, free-pass offerings, less congested roads or new infrastructure changes, however also due to the plethora of benefits that bikeshare provides against its shared mobility counterparts.

So, as cities de-confinement accelerates, and with it the usage of bikeshare systems, how can bikeshare operators adapt to ensure bike and parking availability as ridership booms?

Working with bikeshare operators across the industry has given us a unique insight into overcoming not only the daily challenges of bikeshare operations but also the new challenge of returning from lock-down. One of these challenges is change is the significant increase in system usage, otherwise known as ridership.

With lockdowns beginning to ease, there has been a considerable increase in bikeshare usage all over the world.

In China, the original epicentre of the virus, there has been over a 150% increase in bikeshare usage, in Paris a record breaking 191,000 rides have been made in a single day along with numerous other reports of shared bike demand has surging across the world.

This isn’t the first time that cycling and bike share have proven to be crisis resilient. Events such as the 2005 New York City transit-worker strike or recent public-transit strikes in Paris bike ridership providing evidence of this. In fact, not only did usage increase during these events, but remained significantly higher than pre-crisis levels, indicating that the levels observed currently will likely become the ‘new normal’.

Therefore, is essential that operators take these positive usage changes into consideration, as increased usage can create decreased availability due to the reduction in the number of bikes to rebalance meaning reduced customer satisfaction and overall system performance.

Now more than ever optimisation of resource (bikes, stations, trucks and field teams) is more critical to system success.

So, What Does This Mean?

In the face of the COVID-19 pandemic, the bike is emerging as the top transportation choice around the world. Operators must be aware and act accordingly to the long-term impacts and cities must transform to accommodate the cycling boom.

The incidence of increased ridership is likely to continue to correlate with the increased freedom that lockdown relaxation is providing, and will not relent based upon previous history.

Increased ridership is music to bikeshare operators of all shapes and sizes, as it not only increases financial revenues but also continues to prove to cities and policy makes the advocacy for these systems.

However, it does also present its own headache. With more bikes in use, resource (bikes) become limited for rebalancing vehicles to redistribute to meet demand causing a potential drop in system availability (bikes & spaces available). With availability have a direct impact on ridership, it is almost a recipe for the perfect storm that will negatively impact bikeshare system usage in the long term as users struggle to find bikes and spaces therefore reverting back to other shared transport — or worse the single occupancy vehicle.

Systems utilising our BICO system have not had to focus on these changes, as BICO automatically assess the resource at its disposal, from bikes, stations, docking points, trucks, truck capacity and much more to optimise what is available to proactively meet real-time demand & conditions.

For example, one of the largest mixed fleets (mechanical & electric shared bikes) dock based operations, who utilises the BICO system, were enabled to manage an unprecedented influx of demand, of over 20% of ‘normal’ levels, without any change to their (already reduced) operational resource to maintain their required KPI performance.

With BICO forming an integral part of their team, it allowed the operator to have full confidence that riders would be able to have access to bikes and docking points (parking) when are where they required it — even if a truck left the depot late, a member of the field team was unavailable or for any other reasons that the planned operational resource can be reduced.

Which is why it is critical, based upon the operational, financial and usage impacts caused by the pandemic that bikeshare operators need to decide:

“What does good look like?”

Rides per bike per day and daily ridership have long been the chosen indicator of a ‘good’ or well performing system, however if this comes at the expense of rider satisfaction due to a reduction in availability is it truly a quality all-round indicator of performance?

Availability must remain high, even with increased usage to ensure overall system performance. This is why operators must assess what good truly looks like and how do they meet requirements.

By understanding the impact of what increased ridership means, such as a data-driven understanding of the required fleet size, vehicle capacity and resource availability, operators can make better decisions for their rebalancing strategies ensuring each piece of the larger operational puzzle is used optimally to maximise system performance.

Using a data-driven approach to scale both bike and operations resource accordingly is crucial, especially as seasons change, having systems that optimise what operators have at their disposal, autonomously, based upon real-time conditions could be the catalyst to ensure that the ridership bar remains raised.

Read Part-1 of the Powered by BICO Series: Workforce

Read Part-2 of the Powered by BICO Series: Changing Patterns

BICO AI provides an AI Operations Platform that assesses various environmental, resource, performance and usage data to optimise available resources (teams, bikes, batteries etc.) to ensure asset availability (location, usable, charged) across the entire network when and where it is required.