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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  

Simplifying and Accelerating Micro-Mobility in 2019

In 2018, we took our business to a new level and put a foundation in place to continue our growth globally whilst utilising our technology to solve new challenges. It was also the most exciting and successful year Stage Intelligence has had to date. We executed our vision for AI-optimised mobility and our partners are seeing the results every day.

This year we met partners across the globe, had more productive conversations, and listened to a growing number of operators as they look to innovate their operations. At every event I attend, I’m reminded of how young, fresh and exciting the Micro-Mobility market is. Everyone is looking at ways to deliver for end users, improve and expand their operations across urban areas or with new modes of transport.

It really feels like 2018 was a landmark year for Micro-Mobility in terms of growth and recognition. The pace of change has been amazing, and the ups and downs throughout the year have shown how important it is to have simple and powerful solutions for managing an increasingly complex mobility landscape.

That’s where we are creating real long-term value for our partners no matter how their organisations evolve in the future. From start-up operators through to the largest Bike Share Schemes in the world, our platform is simplifying and accelerating how they operate.

I’m extremely proud of all that our team has achieved in 2018 and we saw what we are capable of. I know we can continue to build on our success and not only enable more partners to benefit from our platform, but also enable more users to experience the best Micro-Mobility service possible. I believe we can play a critical role in creating sustainable mobility options, businesses and urban environments and that is an exciting prospect in 2019 and beyond.

We’re Moving Fast

At the beginning of the year, our BICO AI optimisation platform was live in two Bike Share Schemes, and by December 2018 it had been deployed in 15 schemes across three continents. Our growth has been transformational for our business. We’re operating in a range of unique environments and have shown that we can scale to serve some of the world’s largest and most dynamic schemes. Smaller schemes that have adopted BICO have also seen the benefits of adopting AI within their schemes, making them more cost efficient enabling them to grow and scale efficiently. There really aren’t any limits on where we can deploy our platform and have positive impacts on operational performance.

In July, we announced our deployment in Helsinki with CityBike Finland OY from which it has grown to be our most successful scheme in terms of ridership. After deploying BICO, CityBike Finland saw ridership grow by five riders per bike per day. That means more citizens are using the available bikes and the scheme is growing its profitability, shown by another expansion planned for the coming season – It’s a win-win for the city, operator and the users.

In Latin America, we partnered with Tembici to deploy BICO in cities across Brazil including Rio de Janeiro, Sao Paulo, Recife, Salvador, Port Alegre and Vila Velha. Our phase two deployments include Santiago, Chile, and Buenos Aires, Argentina. This is a major leap forward for our presence in South America and a vote of confidence in our platform. Tembici believes in BICO and will utilise the platform to scale their operations across Latin America and beyond.

In Europe, we’re working with Smovengo and have deployed BICO across the Velib in Paris, France. We’re extremely proud to see BICO live in the largest Bike Share Scheme in the Western world, and increasing the usability of more than 21,000 bikes of which 7000 will be electric. It’s a major milestone for our business and really shows that no matter the size of scheme, season, vehicle type or weather, BICO can drive efficiencies for our partners.

Each of these BICO deployments shows the potential of our business to directly influence the future of Micro-Mobility globally, and enable the success and growth of more operators across the world. With every scheme we add we’re evolving, refining and improving our platform. Each scheme adds something new and drives our platforms features and functionalities forward.

Priorities in 2019

Since becoming CEO of Stage Intelligence in 2018, I’ve been focused on continually pushing our business forward and building on and adding to our successes. The biggest challenge in AI and Micro-Mobility is remaining focused on where we add value and not try to chase every opportunity. We have to stay aligned with our original purpose. We make solving complex challenges simple for our partners.

In 2019, we’re going to build on our core strengths and use all we’ve learned to expand into some new areas. I see 2019 as a year where we add some new dimensions to BICO and find some interesting ways to add value for our partners.

There are six areas that we are going to prioritise in the 2019:

  • Nurturing Our Core – We will continue to grow the number of Bike Share Schemes we’re deployed in and support more operators globally. There are more than 1,600 Bike Share Schemes globally and we know that we can help them to operate efficiently and deliver an optimised experience for users. I see huge potential in North America, and we’ll be making a big push in the market in 2019.
  • Adding New Capabilities – We’re expanding what our platform can do for our partners. We’re adding new support for managing broken bikes, electric bikes and optimised battery management. Operators need a more efficient way to deal with maintenance and we see an opportunity for BICO to help them solve these challenges.
  • Supporting Hybrid Models – We’re looking at ways to support Hybrid Bike Share models where docked and dockless systems are integrated. Depending on the exact model, bikes can be docked at physical docking stations, “virtual docking stations” or remain free-floating. It adds new complexity to scheme management but ultimately offers a flexible user experience. The challenge is to help operators manage their bikes and ensure they are available when and where they’re needed.
  • Deliver Micro-Mobility Through a Single Pane – As the number of modes of transport grow across a city, we’re developing ways to visualise the entire Micro-Mobility landscape in an urban area. Operators want to see and understand their entire operating environment through a simple, optimised dashboard. They want to gain insights from data and make faster decisions. Micro-Mobility will only grow in complexity and we’re finding ways to make it simpler to manage.
  • Growing Our Team – In 2019, we’re going to continue to grow our team and bring on board new skills and talent. We added Alex Churchill to the team at the end of 2018 to expand our AI expertise, and he brings new perspective and insights to our operation. Our AI platform is delivering amazing results and we want to continue to refine and optimise it. The tech team will grow as well as we expand our platform, while sales and marketing will also see new additions.
  • Continued Execution for Partners – The most important thing is that we continue to execute for partners and deliver the results we’re capable of. The numbers show precisely the kind of impact we can have on a scheme within months. Each scheme we work with sees cost-savings and new growth in their ridership. It is that simple. We just need to keep delivering for partners.

This Time Next Year

This time next year I think the Micro-Mobility market will have had another year of huge growth and disruption. Personally, we will have double digit growth in the number of schemes we’re deployed in and our platform will support more diverse needs of our partners.

There will be more modes of transport deployed in cities across the globe and the need for a simpler, faster and easier way to manage schemes will only grow. We’re going to work closely with partners to collaborate and co-create features or solutions that solve their challenges. If we keep listening to their needs, the potential in our business is limitless.

Part of this is about getting out in the market and to even more events. We’re going to be sharing our ideas, data and results. I want to evangelise AI in Micro-Mobility and share our partners’ success stories. I see an opportunity for us to offer consultancy to new partners and really act as a trusted advisor for new schemes that are launching, or existing schemes that want to go to a new level.

There has never been a more exciting time in our business and our industry and I’m looking forward to a huge 2019.

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

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

Five Bike Share Trends to Watch in 2018

When I talk to people at events, I see how business models have changed over the last year. Bike Share operators are constantly challenged to keep up with the rapidly changing industry and offer better rider experiences to its users.

 

A big opportunity for operators in 2018 is in how Bike Share Schemes are managed. It will not be enough to just supply the bikes, questions will be asked about how operators cater to the local market needs.

 

Intelligent operations will be at the heart of Bike Share Schemes in 2018 with operators focused on delivering the best experience to compete in the highly saturated market.

 

As Bike Share continues to grow across the globe, I see the following trends changing the marketplace:

 

  1. Rise in App-Based & Dockless Bike Share Models

App-based Bike Share Schemes are being deployed in more markets globally. In many urban cities, you now have access to free-floating bikes that can be picked up and dropped off virtually anywhere. In 2018, we will see an increase in cities adopting these schemes in an effort to reduce the strain on existing transport infrastructure and facilitate the move from personal vehicles.

 

  1. Growth of Multi-Operator Environments

Multi-operator environments are not new. We are already seeing many cities where more than one operator is running a scheme. Throughout 2018, this is likely to grow to more cities around the world and operators will be asked to deliver an optimised Bike Share Scheme to keep up with the competition. Cities will also need assuring that resources will be better managed to avoid bikes being damaged or left in unsuitable places.

 

  1. Optimised Redistribution with New Technology & Incentives

The growth in Bike Share Schemes and multi-operator environments will be the driving force for better redistribution. Operators will be challenged to offer schemes that work well and is not a nuisance to cities or its citizens. Fortunately, new technology such as geo-fencing and incentives including financial rewards will drive better rebalancing processes. From the events I’ve been to, it’s clear that operators are looking to do more to improve their redistribution efforts.

 

  1. Increased Bike Share Regulations

Bike Share operators have welcomed the prospect of more regulations. While some may hinder current operations, most regulations will help Bike Share Schemes to thrive. It will guide operators as to what is required and enable them to grow into new markets much easier.

 

  1. Driving Intelligent Bike Share Scheme Operations

In 2018, operators will look towards better ways to manage their schemes and to grow their ridership. We see growth in technology such as Artificial Intelligence (AI) simplifying the management process. It enables operators to sort through vast amounts of data to gain actionable insights that has a direct impact on their operation. That kind of information makes management of Bike Share Schemes simple and efficient.

 

In 2018, we will continue to see disruption in all parts of Bike Share and the wider transportation industry. It will impact how operators do business. How these schemes are managed will still be the main focus for many cities and its citizens.

 

Users expect transportation to be as simple and efficient as the other services they consume on a day-to-day basis. That puts the pressure on operators to deliver a well-run Bike Share Scheme.

 

An optimised scheme enables users to rely on its services and use it regularly. It reduces unnecessary costs and complications for operators while driving profits to their business.

 

Fortunately, I see new technology, incentives and processes enabling operators to transform their current business model.

 

At Stage Intelligence, we combine citywide data with AI technology to deliver real value to Bike Share Scheme operators. Our BICO platform makes it easy for operators to simplify their operations and deliver Bike Share Schemes that works for both cities and the users.

 

To find out more about how Stage Intelligence is transforming Bike Share Schemes around the world with AI technology, please contact  tom.nutley@stageintelligence.co.uk

 

2018: A Tipping Point for Artificial Intelligence in Transportation

2018 will be the tipping point for Artificial Intelligence (AI) in the transportation industry. It will be a year where AI becomes an essential tool with new understanding and recognition that it is critical to success. In our business and beyond, we’ve seen how influential this technology can be in changing business models and creating better transport solutions.

 

At Stage Intelligence, we’re seeing this become a reality. In 2017, we’ve seen tremendous momentum behind our business and growing demand for real AI solutions in transportation. We’re rolling out our AI-based Bike Share management solution in cities across the globe and changing the perception that Bike Share isn’t a viable, reliable transport option.

 

We are helping to accelerate transformation in transportation and utilising self-organising algorithms and elements of machine learning to simplify and empower Bike Share management.

 

2018: Challenges in AI

The future of transportation will be defined by AI. Research firm Gartner predicts that by 2020 almost every new software product will have AI technologies. In transportation, we are starting to see widespread application and development of AI technology that is being powered by the collection of data and use of algorithms.

 

That said, it is still a very young market with challenges ahead. I see three big challenges for AI in transportation:

 

  1. Not All “AI” is the Same – Many businesses that say they use AI don’t actually have it deployed. It is a buzzword and many businesses are doing data visualisations or pretty interfaces but when you look under the hood there’s nothing there. Operators eager to benefit from AI don’t get what they paid for and won’t see the best of it.

 

  1. Transportation Expertise and Focus – AI solutions need to address specific challenges. They need to be purpose built for transportation and developed by both experts in transportation and AI. Otherwise, you get generic solutions that solve generic problems rather than enabling real innovation and agility in transportation.

 

  1. Nurturing AI – AI isn’t just about building solutions. It is about training it and nurturing it to deliver the results you want. It requires people, time, effort and a lot of data to continuously maintain and develop the technology. You don’t just flip a switch. It requires an expert experienced in developing and growing successful solutions.

 

As we see more AI-based solutions adopted, there will be a move towards quality and performance. Solutions that are based more on buzzwords than results will fade away.

 

In 2018, more people will understand the basics of AI and make better decisions about the solutions they deploy. That’s good for transportation and will accelerate its growth.

 

Building Better Bike Share Schemes

We’ve seen tremendous growth in our business over the past year. In 2017, we deployed our solutions in new corners of the world.

 

Our business development team led by Tom Nutley was out and about at events and meetings almost on a monthly basis. We’ve been successful in sharing our belief in automated rebalancing and using self-organising algorithms to build better Bike Share Schemes and that has led to trials and deployments around the world.

 

Our flagship BICO Bike Share Scheme management platform has been adopted and is supporting ridership growth in unique markets in the Americas and Europe. In 2017, We added greater functionality to BICO including a successful internationalisation process that helped us to better serve our partners abroad and dynamic replenishment values for greater predictive management of a scheme. Both have made it easier for operators to deploy and benefit from our solution.

 

We are also proud to have partnered with industry bodies to accelerate transformation in Bike Share Schemes. We are a member of the platform for European Bicycle Sharing & Systems (PEBSS), created by European Cyclist’s Federation (ECF). Our work with ECF and PEBSS highlights our commitment to growing a healthier cycling market for all.

 

In November, our usability data was shared around the world and is influencing conversation about how to create Bike Share Schemes that give riders an optimised experience. We are sharing our data and analytics to show what is possible in Bike Share when you take a new approach.

 

This Time Next Year

Throughout 2018, we will develop our AI technology for the shared mobility market, innovate for Bike Share operators and continue to roll our solutions around the world. It is an exciting time for our industry and we are ready to help our partners benefit from our solution and encourage the continued growth of Bike Share.

 

As cities around the globe continue to push towards cleaner and more sustainable transportation, we will see increased demand for user-friendly Biker Share. How cities and operators manage their schemes and support riders will define their success.

 

The tipping point in Bike Share will be seen when automated rebalancing becomes a critical part of any Bike Share operator’s conversations about growth. AI will at least be considered when discussing a path forward for schemes looking to grow. That’s a big step forward in an industry that is constantly changing.

 

There are a few things that I believe will define the Bike Share in 2018:

 

  • Growing Bike Share Schemes

As more Bike Shares use AI-based management solutions, riders will get a better experience and schemes will grow. It will enable faster decision making for bike distribution, ensuring that riders get bikes and docks where and when they need them. That drives growth and creates new efficiencies.

 

  • Move Towards Electric

We will see a greater push in electric cars, bikes and scooters in an effort to reduce emissions and drive down costs. We will see more Bike Share offering e-bikes and even further introduction of e-scooter sharing in cities around the world. With greater range and a larger, more diverse user base, schemes will need better management solutions to drive efficiency.

 

  • Mobility as a Service

We will see mobile phones play a greater role in traditional transportation. Mobility as Service (MaaS) showed its potential in 2017 and now MaaS will begin being rolled out in cities around the globe. It will streamline how we travel and deliver even more data about how we commute.

 

  • The End of the Free-For-All in Free Floating

The free-for-all in Free Floating Bike Share has to come to an end. Healthy markets do not tolerate massive oversupply and as we’ve seen in some cities in China it leads to failing schemes. Free Floating Bike Share Schemes need to be managed and follow policies set out by local governments to be successful. In 2018, we hope to see less mistakes made and a lesson to be learned.

 

All of these things will drive demand for AI-based solutions and the evolution of Bike Share Scheme management. Bike Share operations should be simpler to manage with better experiences for riders. In 2018, we will solve some of the challenges in transportation and deliver solutions that benefit cities, citizens and the environment. I see tremendous potential in our business and our industry. 2018 will be a phenomenal year for AI in transportation.

 

Stage Intelligence’s Usability Data Reveals the Need for Better Bike Share Scheme Management

Insights from schemes in London, Paris, New York and Chicago show that data can be used to deliver optimised rider experiences and grow Bike Share Schemes

LONDON, 8 November 2017 – Stage Intelligence, the leading provider of Bike Share Scheme management solutions, has released its 2016 Q4 data on bicycle and docking station usability and availability across Bike Share Schemes in London, Paris, New York and Chicago. Usability is central to providing an exceptional rider experience and supporting the growth of Bike Share Schemes. It ensures bikes and docking stations are available when and where they are needed most.

The data reveals Chicago and London leading the group with an average usability figure for the quarter of 99.3% and 99.4% respectively. Chicago has been consistent in delivering a reliable Bike Share Scheme to its riders. London is also rated highly but this could indicate over servicing its market, which can create unnecessary costs and limit growth.

New York City ranks the lowest of the major cities with an average usability figure of 90.2% for the quarter. It means that on average 10% of riders at any given time cannot access the bikes or docking stations they want. Paris follows New York City with an average usability of 98.1% with usability dipping to lows of 76.7%. The inconsistency in the scheme means that it may be difficult for riders to depend on the scheme on a daily basis.

“Bike Share riders and cities benefit from Schemes that are easy and reliable to use,” said Tom Nutley, Head of Operations at Stage Intelligence. “Operators need to make sure that riders have access to bikes when and where they need them without over servicing the market. This is where the London scheme could be at most risk. The data is very positive for London but it could be using too much city resources to manage its operations especially when there is no need to.”

Stage’s usability measure compares all docking stations that are within easy walking/cycling distance in a published 500m radius from each other, which can be altered by the BICO platform. The platform takes into account each city’s SLAs when measuring the usability of a Bike Share Scheme. A docking station is usable if there are bikes and docking points available at the station itself or at one or more of its neighbours. The BICO platform can also set custom usability defined by a specific threshold or the SLAs of different cities.

“For Bike Share schemes to be seen as a real, public transport solution and a smart answer to urban mobility, they need to work as good or better than existing public transport services,” said Paul Stratta, Director, at Platform for European Bicycle Sharing & Systems (PEBSS), an initiative from the ECF. “Nowadays people go to bus and railway stations expecting the services to be there, and for it to operate on time. It should be the same with Bike Share schemes. Collecting and analysing data allows Bike Share operators, and their city clients, to get a big picture of operations and understand where bike share can improve and how exactly to do it.”

The neighbourhood approach goes beyond the usual cluster and geographic data collection method which may be a sub-optimal approach – especially in larger schemes. It can identify if Bike Share Schemes are managed well and if it is over or under servicing the cities and its riders. The BICO platform is dynamic to each city and considers each city’s user patterns and prioritisation as well as the SLAs they operate under to measure the usability of Bike Share Schemes and provide valuable data for operators.

“Our BICO platform allows us to take a deep dive into individual Bike Share Schemes in different cities and neighbourhoods around the world and find ways to improve usability within them,” said Toni Kendall-Troughton, CEO at Stage Intelligence. “We were particularly impressed with Chicago’s Bike Share scheme which was performing well without over servicing its neighbourhoods or the market. It was consistent throughout the quarter with high usability figures and over-performed on busy summer weekends to meet the rise in demand.”

 

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 bikeshare schemes. BICO enables precise and optimal decision making and has been purpose-built to remove the complexity from managing resources within a bikeshare scheme. Customers choose Stage Intelligence because our solutions increase their agility, adaptability and enable them to move beyond traditional manual processes. We collaborate with customers to solve complex problems and deliver solutions that have a lasting impact on their operations.

www.stageintelligence.co.uk