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Stage Intelligence Data Reveals the Power of Artificial Intelligence to Increase Efficiency and Profitability in Micro-Mobility Schemes

The BICO AI Optimization platform moved 40,000 bikes per day in 2018 and delivered an average of 98% usability while reducing distribution hours by 20%

London, 18th June 2019 – Stage Intelligence, the leading Artificial Intelligence (AI) platform provider for Mobility and Logistics, has launched its BICO Performance Report 2019, showing the direct impact of AI on Micro-Mobility schemes across the globe. The report reveals that AI can be a driver for both enhanced user experience as well as increased operational efficiency. AI can solve operators challenges around revenue growth while also reducing costs.

The report uses captured from Stage’s BICO AI Optimization platform, which enables operators to visualise, automate and optimise their Micro-Mobility schemes. 

BICO is live across three continents, seven countries and 12 cities handling 40,000 bikes a day of which 15,000 are electric.

In 2018, BICO platform has reduced distribution hours and miles covered by distribution trucks by 20% leading to a 20-tonne reduction in carbon dioxide emissions. Schemes were able to deliver a 98% availability and increase rides per bike per day by two enabling them to maximise the potential of their scheme.

Schemes that have deployed BICO on average have seen:

  • 98% usability
  • 94.5% availability
  • 30% reduction of bikes moved
  • 20% reduction of redistribution trucks required
  • 25% reduction of rebalancing jobs

“Micro-Mobility schemes can be complex to manage, costly to operate and difficult to grow. That puts limits on the impact Micro-Mobility can have for citizens and cities. When an operator deploys an AI-based solution, they transform their operations and increase the health and sustainability of their schemes,” said Tom Nutley, CEO at Stage Intelligence. “Our data shows the impact that AI is having in the real world. It is solving the most pressing challenges operators face while making it easier for users to make micro-mobility part of their daily routine.”

BICO enables micro-mobility scheme operators to remove complexity from their operations and reduce costs and in the past 12 months the platform has improved KPI performance for operators by 8%. With historic visibility into scheme performance, BICO enables operators to increase ridership, reduce costs and automate operations allowing them to grow and add new capabilities.

“Operators need an intelligent foundation for delivering the next-generation of Micro-Mobility and offering new users experiences. The ones that will be successful will be armed with new intelligence, data visualisation, real-time decision-making, optimized resources and have the freedom to grow and innovate,” added Nutley.

5 Ways Automating Processes will Change Your Scheme

Across all kinds of industries, businesses are automating their operations and finding new ways to create efficiencies with artificial intelligence (AI). Micro-mobility is no different, especially bike sharing.

The challenge for many operators is to understand the value of automation and how it can influence the future of their operations. The immediate response to AI-based automation is that it will simply replace humans and it will be a driver for job losses.

In fact, Gartner reports that automation related to AI will lead to 1.8 million in job losses but it will create 2.3 million new jobs. AI will drive a net gain of 500,000 new jobs, according to the research firm. Automation isn’t as simple as a swapping out humans for software.     

In micro-mobility automation is about creating new efficiency, scalability and speed. Here are five ways automating processes will change your Bike Share Scheme:

  • Reduced Costs – Data has shown that despite tripling the size of the scheme, one Bike Share operator reduced the required rebalancing fleet by 50% whilst achieving their SLA of 97% usability through automating their processes. Automating the decision making within a Bike Share Scheme enables operators to scale back on the need for trucks, drivers, and management staff. While resources are reduced, the management platform will continue to achieve the desired outcomes set out by the scheme.
  • Increased Profitability – Automation supported with AI enables precise redistribution of fleets across a cityscape in real-time. That means users can get the bikes they want where they want them. Planning and decision making can be made as situations change in a city and that will have a direct impact on the experience for users. When users have an optimised experience, they are more likely to use a scheme and ridership increases. That drives long-term profitability and creates loyal users. 
  • Gain New Scalability – When you automate processes, your scheme can grow seamlessly. You don’t need to add new team members or look at increasing fleet size. You can simply replicate the same processes in new locations and manage resources efficiently across a larger area. It makes it easy to grow efficiently. You are able to make data-driven decisions furthering the automation and optimisation of your current fleet to reduce wasted journeys. At the same time, if you’re looking at adding new vehicles to your scheme like e-bikes, scooters or e-scooters, they’re simple to add to the existing platform.
  • Deliver Consistency and Reliability – Automation removes the risk of human error and enables schemes to move faster. With any manual processes that requires human intervention, there’s a risk that something can go wrong. When a scheme removes the manual processes, they gain consistency and reliability that translates into a predictable cost base and a stable user experience. 
  • Benefit from Transparency and Data Mining – Automationenables data to be capture end-to-end across a scheme and processed immediately. That means meeting SLAs and KPIs becomes simpler and services can be tracked for performance. The more online and connected a scheme is, the easier it is to gain insights and make long-term decisions about investments and opportunities. There’s less reliance on a human’s gut instinct and more on intelligence gathered across a scheme.      

Bike Share Schemes that automate their processes move away from a reactive model and increase their agility and adaptability. The benefits cascade across an organisation and enable it to grow efficiently.

We’re experts in automating micro-mobility schemes and if you’d like to learn more about how a your scheme can benefit from automation, get in touch: info@stageintelligence.co.uk

Artificial Intelligence Makes Greener Bike Share Schemes

Since the first coin operated Bike Share Scheme was introduced in Copenhagen in 1995, the health and environmental benefits of Bike Sharing have been widely recognised. If people choose to ride a bike, they aren’t driving a car, riding in a taxi or using mass transit systems. They’re exercising and reducing congestion across a city.

 

That’s all true but we’re seeing that Artificial Intelligence (AI) is able to maximise the positive environmental impact of Bike Share Schemes and make them even more sustainable. Bike Share Schemes that implement an AI platform can push their schemes towards carbon neutrality and demonstrate that they are taking climate change seriously.

 

We have seen it in the schemes that our BICO AI optimisation platform is deployed in. The data shows that AI can directly impact how a Bike Share functions within a city and optimise its operations, reducing CO2 emissions.

 

The biggest impact AI can have is simply getting more people to use a scheme. As mentioned, that means they aren’t using another mode of transport and a city and its citizens are healthier. BICO ensures that users can get the bikes they want where they want them and docks are available at the end of their journey. That makes it convenient to use a Bike Share Scheme and incorporate it into their daily routine.

 

We’ve seen ridership growth across these schemes after they’ve deployed BICO:

 

  • Divvy Bikes, Chicago: Ridership increased by 0.75 Rides Per Day
  • MIBICI, Guadalajara: Ridership increased by 1.5 Rides Per Day
  • City Bikes, Helsinki: Ridership increased by 5 Rides Per Day

 

These numbers are per bike, per day. That’s a huge jump in places like Helsinki, which has a big impact on the benefit the scheme is delivering. This is also combined with more efficient redistribution of bikes across a scheme that translates into a reduced carbon footprint for the schemes operations.

 

Our platform enables the redistribution of bikes to be optimised so that fewer trucks take fewer trips to achieve the best possible results for users.  Over the last year, Bike Share Schemes that use BICO have reduced the amount of time redistribution trucks spend on the road while also cutting the distance they travel by 10,000 miles. That means less CO2 generated by the trucks and a lower carbon footprint for the scheme.

 

BICO is also responsible for 100,000 less bikes needing to be moved, due to the precise and optimal decision making of AI. By streamlining the processes of multiple Bike Share Schemes, we have seen the reduction of up to 10 metric tonnes of CO2 emissions as a direct result of less redistribution trucks being on the road. This has enabled these Bike Share Schemes to take one step closer to their goal of delivering a carbon neutral operation.

 

It all adds up to a clean mode of transport being even cleaner with the use of AI.

 

Let us know if you’d like to learn more about how we support Bike Share Schemes with AI: info@stageintelligence.co.uk

The Positive and Powerful Story Building Around AI

Over the last 12 months or so, questions or concerns about Artificial Intelligence (AI) have largely faded away. It isn’t that the general public has got all the answers they need about AI but more that AI is becoming a reality in more and more of our homes and places of work.

 

In our business, we’ve seen skepticism turn to excitement when we talk about the potential of AI to optimise how they operate. There’s a comfort level that is growing and we believe acceptance of AI will only accelerate over the next 12 months.

 

AI is often in action behind-the-scenes making user experiences more enjoyable and easing the workload for businesses. We’ve seen it implemented in our homes in smart home-hubs or news stories about AI helping to identify cancer or potential heart attacks. AI has a positive story and real-world applications that are putting fears to rest.

 

At the same time, research firm Gartner has confirmed that AI is creating more jobs, rather than taking them. By 2025, the amount of jobs generated by AI will have reached 2 million, according to the firm. That’s a big change from the common idea that AI kills jobs and makes people redundant.

 

Gartner shares our view that AI frees workers to focus on other tasks and enables them to go beyond routine tasks. Instead of seeing AI as a competitor, workers can see AI as a companion and a way to excel at a given task. AI becomes a critical tool in problem solving not a substitute for a human.

 

Gartner notes that in 2021, AI augmentation will generate $2.9 trillion in business value and recover 6.2 billion hours of worker productivity. We see this directly in the Bike Share Schemes that have deployed our BICO AI optimisation platform. They augment their operations with AI, which in turn drives revenue growth through increased ridership while maximising the potential of the workforce.

 

As worries about AI fade, businesses across different industries are starting to realise that AI can be extremely beneficial to them if applied correctly. Global technology research company ISG, discovered that although at present only 16% of businesses utilise AI, in 2019 that figure will rise to 51%.

 

There are a lot of different drivers for that but part of it is that the potential of AI is becoming widely understood and it is delivering real competitive advantages. Businesses that don’t explore the potential in AI potentially will miss out or see their competitors move faster and with more precision than them.

 

In the increasingly competitive micro-mobility market, we believe AI will be a clear differentiator and be a driver for user and revenue growth. AI isn’t an idea anymore, it is having a direct impact on how citizens enjoy and move across a city. The skepticism is gone and now adoption is only going to accelerate.

 

Get in touch if you’d like to learn more about how we’re using AI to optimise micro-mobility: info@stageintelligence.co.uk  

Using Autonomous Vehicles To Manage Bike Share Schemes of the Future

While fully autonomous cars are still years away from being a mode of transportation that we can use day-to-day. We think it could have a positive impact on Bike Share Scheme management in the future.

 

With 68% of the world population projected to live in urban areas by 2050, we believe the future of mobility lies in simpler, cleaner and space saving modes of transportation like walking or cycling. Autonomous cars could play a big part in this.

 

In Bike Share Schemes, driverless cars could open up new opportunities in optimising management to deliver a better scheme to its riders. It can make the redistribution of bikes in the future much easier and more cost-efficient for the operator. Data, Artificial Intelligence (AI) and autonomous technology can all interlink to carry out traditional operational processes.

 

Currently, operators have to rely on manual processes for redistribution with trucks and vehicles being led by operational staff. That requires a significant amount of internal planning on where the drivers need to be, at what time and taking into account shift breaks and patterns.

 

Fortunately, Bike Share operators now have a lot of tools and technology at their fingertips that can help optimise and manage this. AI-based management platforms are helping operators with a lot of the heavy lifting and giving operators the most optimum way to manage operational staff.

 

In a future where driverless cars are commonplace, we can see Bike Share Scheme management moving towards the use of this technology. It has the potential to directly connect with management platforms to optimise how the redistribution trucks move, where they go and how often they go there. That can all be done with minimal human interaction.

 

For Bike Share Scheme operators this can remove the limits on rebalancing its bikes and offer a better and more reliable scheme to its riders. When Bike Share Schemes are better managed, operators can reduce costs and accelerate rider experience.

 

You are able to accurately serve the local market and ensure bikes are available when and where it’s needed. That supports the move towards shared integrated transportation and gets more people cycling.

 

Autonomous cars have a lot of potential for Bike Share Schemes and wider transportation in general, but it is still very far away from reality. At Stage, we’re always looking at the future and seeing how complex challenges of today could be solved by the technologies of tomorrow.

 

We’re excited to see what new technology will bring to the growing shared mobility market and how we can best incorporate it to deliver smarter processes to the wider industry.

 

Please get in touch if you’d like to know more about how we support Bike Share operators with a simplified management processes: tom.nutley(@)stageintelligence.co.uk

 

 

Helsinki AI

Stage Intelligence Deploys Its Artificial Intelligence Platform in Helsinki to Support Bike Share Scheme Growth

Moventia and CityBike Finland OY go live with Artificial Intelligence technology that is simplifying and optimising Helsinki’s Bike Share Scheme.

 

LONDON, 10 July 2018 – Stage Intelligence, the leading provider of Bike Share Scheme management solutions, has partnered with Moventia, a widely recognised urban transport operator, and CityBike Finland OY, the Bike Share operator for Helsinki, to deploy its BICO Artificial Intelligence (AI) platform in Helsinki’s Bike Share Scheme. Helsinki CityBike has gone live with Stage’s AI management platform and is supporting over 600,000 residents with their new season of Bike Sharing.

The BICO solution is actively collecting citywide data and optimising Bike Share operations in Helsinki. The partnership with Stage Intelligence enables CityBike to use its BICO AI platform to drive usability of its more than 2,000 bikes and increase ridership for the new season of Bike Sharing as the CityBike scheme continues to expand into the city of Espoo.

Stage specialises in developing, training and deploying AI technology to optimise the management and operations of Bike Share Schemes globally. Its flagship BICO solution has been helping multiple Bike Share operators around the world deliver a better optimised scheme while reducing operational costs.

“Helsinki is in one of the top ten most livable cities in the world with strong cycling infrastructure and public transportation links. We are excited to go live with CityBike and its partners to transform how over 600,000 Helsinki residents experience Bike Sharing every day. Over 96% of its residents have a positive attitude towards cycling and we’re proud to be using city data and AI to get even more people cycling through optimised and efficient Bike Share Scheme management,” said Tom Nutley, Head of Operations at Stage Intelligence.

BICO is being used to optimise Helsinki’s Bike Share Scheme and get more of its citizens cycling and using public modes of transport. Helsinki is one of the top cities internationally for cycling with around six journeys a day made by bike, according to the City of Helsinki’s Bicycle Account 2017 report. By 2020, it’s aiming to increase the number of journeys taken by bicycle from 10% to 15%.

“Cycling is quite often the fastest and most comfortable way to travel in Helsinki and the city has built quite a strong culture around it. The residents love cycling, and we want to get more people on two wheels and using the city’s extensive public transport methods,” said Jordi Cabañas, GM of the Bikesharing Division at Moventia. We chose Stage Intelligence because they understand the city and have strong processes that can help us achieve our ambitious goals in making Bike Sharing more accessible and attractive to all citizens of Helsinki.”

With population figures expected to reach 860,000 people by 2050, city officials and planners are focused on getting more of its residents cycling. Helsinki City Bikes have been at the heart of promoting the city’s cycling efforts.

“Public transportation is a big part of Helsinki with over 50% of the population relying on it for its daily commuting and Bike Sharing plays a very special role in this. Over 60% of users combine CityBike with public transportation and use it to get around the city as the Bicycle Account report states. It’s why we’ve gone live with Stage Intelligence to deliver a more efficient Bike Share Scheme and help more people in Helsinki see bikes and public transportation as a viable mode of travel,” said Juha Pitkänen, Service Manager at CityBike Finland Oy.

Stage’s BICO solution is currently deployed in numerous Bike Share Schemes around the globe including Divvy Bikes in Chicago, MIBICI in Guadalajara and Helsinki CityBike with several more deployments in the near future. It has been crucial in reducing operational costs for operators and enabling the rapid roll out of new features for its riders. Stage Intelligence has supported the Divvy Bike Share Scheme achieve over 15 million trips in Chicago.

 

About Stage Intelligence

Stage Intelligence specialises in developing Artificial Intelligence solutions for the transport and logistics industry. Its flagship solution, the BICO recommendation engine, delivers real-time intelligence for the management of Bike Share Schemes.

BICO enables precise and optimal decision making and has been purpose-built to remove the complexity from managing resources within a Bike Share Scheme. Partners choose Stage Intelligence because its solutions increase their agility, adaptability and enable them to move beyond traditional manual processes.

Since its inception in 2011, Stage has collaborated with leading Bike Share operators from around the world to solve complex problems and deliver solutions that have a lasting impact on their operations.

www.stageintelligence.co.uk

 

About Moventia

Moventia is a public transport group since 1923, with a clear international vocation. Moventis is specialized in all type of mobility services (regular, urban, interurban and special) and moves around 110 million passengers per year with 1.300 buses, 41 tramways, special services and 26.000 bicycles, both traditional and electric with 1.700 stations. Regarding the automotive industry – 65 years this year – Movento sells about 27.000 new and used vehicles of the 17 brands it represents. Moventia, with 4.000 employees, is defined as a socially responsible group committed with the society, people, institutions and the environment.

www.moventia.com

 

About CityBike Finland OY

CityBike Finland is a subsidiary of Smoove and Moventia. The consortium is responsible for producing and operating the Helsinki Bike Share System. It was awarded a ten-year bicycle contract for the city of Helsinki, which was signed in December 2015 between HKL and the Moventia-Smoove consortium. CityBike Finland has also won an eight-year contract for the Finnish city of Espoo.

The Helsinki Bike Sharing service offers a turnkey solution aimed at providing the citizens of Helsinki with the most advanced public bicycle service in the world via a service with 1,500 bikes and 150 stations.

www.citybikefinland.fi

 

4 Reasons Why Scheduled Bike Share Redistribution Doesn’t Work

The biggest challenge in Bike Share Schemes is to provide an optimised service each and every time. Operators that choose schedule-based distribution are often limited in their rebalancing efforts and are not efficiently serving the local rider demand. That impacts ridership and rider experience as a whole.

It’s up to the operators to ensure they have a simple and optimised management process that’s tailored to the cities and the riders. It enables them to offer better services, build stronger ridership and reduce operational costs. Yet many operators still choose to carry out schedule-based redistribution.

Schedule-based distribution means drivers have pre-set information or a schedule of how many bikes to pick-up and drop-off and at what locations. The schedule is created irrespective of the city it’s operating in or its specific needs. This can often mean that by the time the first job is completed the whole schedule could be wrong.

Poor rebalancing and management processes can also add to the growing situation of bikes being left as a nuisance to cities and its citizens. Singapore has seen first-hand the impact of poorly managed resources that have a huge effect on the day-to-day lives of its residents.

To combat indiscriminate bike parking, The Land Transport Authority (LTA) in Singapore passed a legislation earlier this year aimed at tackling this issue for over 100,000 bikes in the area. Since then it has introduced several new measures including reduced fleet size and Bike Share licences to ensure operators are better managing their schemes.

It is now more important than ever to have a smart management process that takes the guess work away from Bike Share redistribution.

Here’s four reasons why schedule-based redistribution doesn’t work for modern Bike Share Schemes:

 

  1. Dynamic Nature of the City

Cities globally are different from one another. They all have different population, city topography, transport hubs and many other factors that make each and every city unique. A schedule that works well in one city could completely fail in another.

  1. Each Day is Different

The day itself plays a huge role in Bike Share ridership. When you combine the changing weather, major city events, transport strikes and a number of other things, the demand for Bike Share Schemes are likely to fluctuate on a daily basis.

  1. Evolving Rider Behaviour

Some riders may take a bike out every morning and every evening to commute between work and home. That makes it predictable and easy to manage. In reality, for many riders their behaviour is constantly changing. Increase in tourists or a rise in public transportation services could affect the demand for bikes in different areas.

  1. Inefficient Use of Staff

What we see every day with schedule-based distribution is that drivers are going from one location to another with no real insights. They often go to a docking station that is expected to be empty and find that it is full. This is huge waste of time, money and resources.

For modern Bike Share Schemes, scheduled-based redistribution doesn’t work. There are too many variables that make schedule-based redistribution time-consuming and inefficient. Operators instead need simpler and smarter processes that can predict demand and manage resources with accuracy.

At Stage Intelligence, we use four weeks of prior ridership data to track rider behaviour and mange redistribution effectively. We predict replenishment values up to 12 hours in advance to enable operators to make quick decision and move quickly to win new riders.

Please get in touch if you’d like to find out how we use data and AI to transform Bike Share redistribution: tom.nutley(@)stageintelligence.co.uk

Are Bike Share Scheme Operators Ready for the GDPR Regulation?

The EU’s General Data Protection Regulation (GDPR) is a European privacy law that was approved by the European Commission in 2016. It will apply to all EU member states from 25th May 2018 and replace the current Data Protection Act 1998.

 

Among other things, the GDPR considers how organisations collect, use, store and manage personal data of EU citizens. Data collectors will be required to process personal data lawfully, transparently and for a specific purpose.

 

For Bike Share Schemes, this will have a significant impact on their operations across Europe. Its business model relies on collecting and using vast amounts of personal data such as names, addresses and credit card details to offer bike sharing services to its users.

 

Many believe it’s the data mining aspect of Bike Sharing that has attracted billions in investment. During 2017, market leaders Mobike and ofo announced that it secured $600 million and $700 million in funding respectively.

 

As GDPR is implemented across the EU, it is likely to impact both the operators and the investors as well. It will limit what organisations are able to do with the data whilst pushing operators to better align their data collection and handling processes.

 

Here’s some of the main principles of GDPR that we see impacting Bike Share operators:

 

  • Wider Scope of the regulation

GDPR applies to all organisations that operate in the EU or handle personal data of EU citizens no matter where the organisation operates. It also has a broader scope of the definition for personal data and now includes data such as IP addresses, behavioural data, location data, and financial information.

 

  • Increased Individual Rights

Individuals have new rights under the GDPR including the right to access the data, right to rectify incorrect information, right to restrict processing, right to portability and right to object certain uses of data.

 

  • Stricter Consent

Consent is one of the main aspects of GDPR. It is important to obtain explicit consent from individuals for distinct purposes with a proof of record stating when and how consent was given. GDPR does allow for ‘soft’ opt-in which enables organisation to send marketing messages for similar products or services as long as individuals are given the opportunity to opt-out at any time.

 

  • Transparent Processing

Individuals can request how their information is processed. Operators need to clarify the purpose in which the data was collected and should ensure that the purpose is limited and the data collected is as minimised as possible.

 

Bike Share operators across the EU will need to ensure they comply with the new GDPR. We recommend reviewing the current consent and data management process in terms of how operators seek, record and manage consent and whether it meets the GDPR standard.

 

Operators should also consider appointing individuals to take responsibility for data protection compliances. In some cases, it may be necessary to have a Data Protection Officer (DPO) under the GDPR.

 

It is also important that all organisations that work on an operator’s behalf follows the stricter regulations. The GDPR applies to data processors as well as the data controllers when handling personal data.

 

At Stage Intelligence, we are experienced in handling personal data and ensuring that it meets the local and regional directives. Our partners around the world rely on us to manage information with the strictest confidence. We store and use data securely and our processes are optimised to support the growth of our partners.

 

To ensure all existing and new processes within your Bike Share operation meet the GDPR standard, we recommend consulting with GDPR lawyers and professionals.

 

To find out more about how Stage Intelligence can support your Bike Share Scheme with streamlined data management processes, please contact tom.nutley(@)stageintelligence.co.uk

Bike Share: The Foundation for Mobility as a Service

Bike Share Schemes can be the foundation for developing Mobility as a Service (MaaS) in an urban city. It has a proven model that supports the deployment of MaaS across many different areas.

 

MaaS integrates various forms of transport services into a single mobility solution. It combines a range of services from trains and buses to taxis and bike sharing to offer a tailor-made transport solution that connects you door-to-door.

 

Bike Share Schemes make it easier to facilitate the move towards MaaS. MaaS operators can take advantage of its large user base and learn from its management approach to drive efficiency beyond Bike Share.

 

We believe a well-run Bike Share Scheme is the foundation for MaaS models. It supports the move away from personally owned vehicles to modes of transportation that are just as effective and cost-efficient whilst better connecting existing transportation.

 

Research by DTimes and ofo has found that shared bikes have the ability to seamlessly interlink existing transport infrastructure. Bike Share Schemes make it easy for users to access other transport links as well get to their final destination.

 

When residents can rely on transportation services to fully connect them to where they need to go, they are likely to use the services again and on a regular basis. That can facilitate the move towards MaaS initiatives in the future.

 

We are seeing the growth of MaaS apps such as Whim in Helsinki that could soon be the norm for modern transport around the world. It provides the convenience of private vehicle travel without the need of ownership particularly when on average cars are parked for over 95% of the time.

 

For cities looking to adopt MaaS models and transform the culture of personal vehicles, simplifying and optimising Bike Share Schemes should be the first step. It makes the financial and convenience case for using public and private means of transport over own personal vehicles.

 

With MaaS, operators and city officials gain complete visibility across a cityscape. It provides a clear picture of its users and their transportation needs. Visibility can be matched with technology such as AI to optimise all journeys in the urban city.

 

At Stage Intelligence, we are leaders in Bike Share Scheme management and hold a track record of simplifying operations around the world using our AI technology. We combine data and AI to deliver actionable insights that makes the management of Bike Share simple and efficient for operators.

 

To find out more about how Stage Intelligence can optimise your Bike Share Schemes with its AI platform, please contact tom.nutley(@)stageintelligence.co.uk

E-bike Sharing

Delivering New Growth for Bike Share Schemes with E-Bikes

Electric bikes (e-bikes) have huge potential for Bike Share Schemes but it brings a new level of management challenges for operators. Over its manual counterpart, e-bikes need to be fully charged for each rider, every time and that requires efficient distribution.

 

E-bike is a pedal bicycle with an electric motor. It assists the rider with additional electric power whilst offering many of the same characteristics as traditional bicycles. Many e-bikes are legally classified as bicycles and subject to the same local laws.

 

E-bikes can be a great way to travel. It can reduce door-to-door time of commutes with a lot less effort and makes transport more accessible to the new or less-experienced cyclists. For operators, it delivers new opportunities to compete in the industry and win new riders.

 

In the recent CES 2018 event, we saw many operators reveal their plans to incorporate e-bikes. Limebike, Spin, Ford GoBikes and Social Bikes all announced the introduction of e-bikes within their operations. It marks the shift in the industry that caters to the end users and their Bike Sharing experience.

 

E-bikes are a convenient way to get from A to B but it is faced with challenges in the market that limit its growth. The perception of e-bikes as ‘cheating’, the added weight of the battery pack to cycles and the cost of purchasing and repairing one all affect e-bike adoption with the public.

 

Manual pedal bikes are also much cheaper and easier to purchase, build and maintain for operators. It makes it simple for operators to grow fast and grow far. It’s one of the reasons why we are seeing thousands of pedal bikes being launched globally and at such a rapid pace.

 

For operators, the key is to deliver a service that people will want to use regularly and e-bikes offer a solution that removes the limit on how and when riders can use the schemes.

 

One major concern I see is in how operators manage their e-bike schemes. The demand for e-bikes is likely to be higher than the current pedal Bike Sharing schemes. It will put pressure on operators to deliver each and every time.

 

E-bikes will also need to be charged at the end of the trip and ready to be used by the next rider. That requires seamless management of resources and expert understanding of the local market.

 

Bike Share operators will need to have a strong management process in place to not only handle the challenges of e-bike sharing but to also take full advantage of the many opportunities it looks to bring for operators. Operators will be required to match local demand with efficient redistribution to succeed in the market.

 

At Stage Intelligence, we are using our expertise in Bike Share management to address the challenges of e-bike sharing. We are incorporating new e-bike technology within the artificial intelligence platform. Our processes enable us to add new features and functionality to cater to the dynamic Bike Share market.

 

To find out more about how Stage Intelligence can support and simplify your Bike Share Scheme operations, please contact tom.nutley(@)stageintelligence.co.uk