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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  

Stage Intelligence Data Shows the Direct Impact AI Has on Growth and Sustainability in Bike Share Schemes

The BICO Artificial Intelligence optimization platform is enabling schemes across the globe to reduce CO2 emissions while increasing scheme ridership.

LONDON, 24 October 2018 – Stage Intelligence, the leading Artificial Intelligence (AI) platform provider for Mobility and Logistics, has released data showing how AI directly impacts Bike Share Scheme growth, efficiency and sustainability. Across Bike Share Schemes in Divvy Bikes (Chicago), City Bikes (Helsinki) and MIBICI (Guadalajara, Mexico), AI has been able to deliver positive outcomes for riders, scheme operators and the cities themselves.

One of the largest and most costly challenges in Bike Share Schemes is the redistribution of bikes across a city. The BICO AI optimization platform enables Bike Share Schemes to ensure bikes are available where they are needed, and docks are free when a rider ends their journey. A rider experience optimized with BICO’s AI drives repeat and regular use of the Bike Share Scheme resulting in increased riders and the reduction of redistribution trucks and staffing resources.

Ridership Growth Since Deploying Stage Intelligence’s BICO AI Platform:

 

  • Divvy Bikes, Chicago: Ridership increased by 0.75 Rides Per Day
  • MIBICI, Guadalajara: Ridership increased by5 Rides Per Day
  • City Bikes, Helsinki: Ridership increased by5 Rides Per Day

 

“When you see ridership growth increase, it means more riders are enjoying a reliable scheme and making it part of their daily routine while operators are increasing profitability. Each ride per day adds to a scheme’s bottom line and enables it to grow and scale effectively/efficiently,” said Tom Nutley, CEO at Stage Intelligence. “We are seeing AI create more liveable cities with sustainable transportation solutions, reducing traffic and improving air quality. That will have a lasting impact on how we experience urban environments.”

Over the last 12 months, the BICO AI optimization platform was able to reduce the number of miles driven by redistribution trucks by 10,000 miles with 100,000 less bikes being moved. With less redistribution trucks on the road, CO2 emissions caused by redistribution trucks were reduced by 10 metric tonnes, enabling schemes to reduce their carbon footprint while offering green transportation options moving one step closer to carbon neutral operations.

Divvy Bikes in Chicago is one example, they have seen a reduction of 4,000 hours of redistribution time which equates to 2.2 drivers per annum. This means there are less trucks on the road, new efficiencies in operations and an increase in ridership year on year. BICO enables them to optimize its resource management and ensure it is giving riders the best possible experience.

The BICO AI optimization platform enables users to collect, manage and visualise vast amounts of data and turn this data into actionable insights to drive growth within businesses. It enables users to automate processes to increase agility and adaptability whilst moving away from traditional reactive manual processes.

“The number of trips per bike has increased significantly in recent years, however we are continuing to work with the same resources as two years ago with the Government providing re-balancing vehicles for the scheme. Currently, during the week we register more than 12,000 trips per day, that is, about 6 trips per bicycle per day. This means that MIBICI represents an efficient transportation alternative for people and has had a very high level of acceptance,” said Mario Delgado, director of BKT bici pública Operator of MIBICI, a project from ‘Gobierno del Estado de Jalisco, Mexico’.

“In this context, the BICO platform has been an invaluable tool for the operation of the system, we have obtained greater performance of the vehicles and has been adapted to our additional strategies for the rebalancing,” Delgado added.

 

About Stage Intelligence 

Stage Intelligence specialises in developing Artificial Intelligence solutions for the transport and logistics industry. Its flagship solution, the BICO AI optimization platform, delivers real-time intelligence for the management of Bike Share Schemes and other forms of mobility.

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 enables 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

 

 

Stage Intelligence Appoints Tom Nutley as CEO to Drive Its Next Phase of Growth

The appointment comes as Stage Intelligence ramps up its development of new transportation solutions based on its BICO Artificial Intelligence platform

 

LONDON, 03 October 2018 – Stage Intelligence, the leading Artificial Intelligence (AI) platform provider for Mobility and Logistics, has appointed Tom Nutley to the role of Chief Executive Officer (CEO). The appointment marks the next phase of growth for Stage Intelligence as it uses its BICO Artificial Intelligence platform to solve an increasing number of challenges in Mobility and Logistics.

 

Nutley has a track record of success in business development and nurturing Bike Share Scheme customers across the globe. He has spent the last two years expanding Stage Intelligence’s presence in the Americas and Europe while enabling millions of riders to benefit from optimal Bike Share Scheme experiences. Nutley assumes the day-to-day leadership of the company and succeeds Toni Kendall-Troughton, who will maintain her role on the board of Stage Intelligence.

 

“It is a tremendous honour to serve as CEO for Stage Intelligence. I’ve seen so much accomplished over the last two years and I believe our BICO AI platform can do even more to optimise how people experience transportation and their urban environments. We’re already seeing more people using Bike Share Schemes globally thanks to our platform and as we deploy in new cities we’re helping schemes to expand and grow,” said Tom Nutley, CEO at Stage Intelligence. “I’m excited for our future and look forward to pushing our platform to new places and solving our customers’ challenges”.

 

Stage Intelligence has deployed its BICO AI platform in Bike Share Schemes in major cities like Paris, Helsinki, Chicago and Guadalajara, Mexico. It has success in creating new efficiencies in Bike Share Scheme management and enabling the optimised distribution of bikes across a scheme. The result is cost-savings for the scheme operators, growth in ridership and an enhanced rider experience.

 

“Tom is passionate about our business and is dedicated to our mission of solving some of the biggest challenges in Transportation and Logistics with AI. Over the last two years, he has been on the road telling our story and helping our customers to understand how AI can transform how they operate,” said Toni Kendall-Troughton, Board Member at Stage Intelligence. “Going forward, I see Tom driving our growth in new areas that can benefit from AI like dockless bikes, electric scooter schemes as well as taxis and other forms of transportation. It is an exciting time at Stage Intelligence and Tom is a great pick to lead the business into the future.”

 

The BICO AI platform enables users to collect, manage and visualise vast amounts of data and turn this data into actionable insights to drive growth within businesses. It enables users to automate processes to increase agility and adaptability whilst moving away from traditional reactive manual processes. Over the coming months, Stage Intelligence will be announcing new products and services that use the BICO AI platform to support the growth of a range of transportation types. It also has schemes coming online across North and South America in the coming months.

 

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

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

Delivering On-demand Team Management to Bike Share Operators

Bike Share operators around the world are looking for easier and better ways to manage its operations and operational staff. They need solutions that can make internal team management simple and reliable.

Today, Bike Share operators are struggling with outdated team creation and management processes that restrict how they carry out their day-to-day tasks. They are burdened with manual inputting, time implications and constant miscommunications internally.

When your operational staff are not working together efficiently, your whole scheme could be at risk. Your redistribution and internal operations are not optimised and that could have a negative impact for your riders.

It’s why team management has been a big priority for us. Operators are looking for easier ways for its distribution teams to work together, communicate and collaborate. In BICO version 15.1.0, we made it simple to create and manage multiple teams.

Operational staff can now set up teams in real-time without the need to do so in advance. They are free to start their day and update the app as they pick up new job requests. It saves valuable time and effort for staff and enables them to operate more efficiently when redistributing the bikes.

Bike Share operators really benefit from a dynamic management platform that can keep up with the changing industry. You’ll see better optimised internal processes that enable your teams to work together to better serve the market. That gives riders complete confidence in your scheme.

Riders can trust that your bikes and resources are available when and where they need them. They can rely on your scheme to get to their end location each and every time. That builds strong ridership and helps you grow locally and around the globe.

In BICO v15.1.0, we’ve worked closely with our partners to add new features including:

 

  • Simple Team Creation

Our BICO Android application lets users create teams with the app by selecting a User Name, Shift, Break Time, Vehicle, Depot and Team Name, which can be easily edited.

 

  • User Verification

The latest BICO update includes a simple user verification process that can be set up by entering the username and password. This is an optional feature and can be turned on or off.

 

  • Usability & Stability Improvements

BICO 15.1.0 also comes with a range of usability improvements, general bug fixes and stability improvements.

 

At Stage Intelligence, we’re continually updating our app to deliver a simpler, faster and better way to manage a Bike Share Scheme. We’re improving the usability, stability and performance of the app while adding new features to give partners around the globe a reliable Artificial Intelligence (AI) platform.

 

If you’d like to find out more about the latest BICO update and how that impacts Bike Share operators around the globe, please get in touch: 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

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

 

Introducing Version 10 of BICO Distribution Services

At Stage, we are continually updating and refining our BICO, logistics system for Bike Share Scheme operators. We listen to our customers and proactively develop the platform to better meet the needs of operators. It is important that the platform continues to evolve and change as we find new ways to use data and put Artificial Intelligence (AI) to work for our customers.

We developed a new version of BICO to simplify management and improve usability for operators. Version 10 delivers improvements focused on:

  • Console usability
  • Bug fixes
  • Android app stability

With Version 10, field operatives benefit from full access to BICO distribution services with the improved Android app. The BICO RESTful API v2.0 has been re-engineered to improve communication resilience and improve efficiency across high latency mobile networks.

The new version focuses on simplifying usage for operators with enhanced map views. Users can customise their default view from any one of the available options and declutter it through a custom Google map style. The view also shows ad-hoc jobs in a different colour to improve visibility for users.

In previous versions, stations with poor usability were all under the same red icon. To improve this, in the new version, we use multiple colours to represent the status of the stations and whether it is too full or too empty.

In our growing efforts to provide additional functionality and future extendibility of the system, we have implemented the New Service Point view to replace the old Docking Station View. The new view makes it possible to filter or search service points and pull up all the information that BICO holds about that specific point which may be amended by the user.

These key changes are implemented with the user in mind and how the system can deliver enhanced usability and a customised view to each individual user. Field operators gain better visibility of the entire Bike Share Scheme and makes managing this process simple with clear map views and warning indications. Simple management is the key to success and growth of Bike Share Schemes.

At Stage, we are always looking to use the latest technology to provide the best possible solutions in logistics in cycle sharing programs. This version update builds on our dedication to improve our services that impact both our customers and their end users.

To find out more about BICO Version 10, please contact tom.nutley@stageintelligence.co.uk