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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

Bike Sharing and Micro-Mobility Shifted Gears in 2018

2018 was the year where Bike Sharing and Micro-Mobility showed its potential to change urban spaces and the transportation industry as a whole. Docked or dockless Bikes, e-Bikes, scooters, e-scooters and a whole range of new mobility options have become the most exciting and innovative sector in transportation.

 

If we go back 15 years, there were just four Bike Sharing Schemes. In 2018, there were more than 1,600 globally, according to Bike Sharing consultancy MetroBike. These schemes account for 18.2 million public-use bikes available around the world, nearly double the number from four years ago.

 

Growth is expected to remain in double digits for the next eight years at least. Research and Markets expects global Bike-Sharing market to grow at a Compound Annual Growth Rate (CAGR) of 12.5% between 2018 and 2026.

 

At the same time, schemes are diversifying and going beyond traditional Bike Share models. In the spring of 2018, multiple US cities started facilitating electric scooter services, which lead to 3.6% of people claiming to use the sharing-scheme. An impressive statistic, considering the market was only made available to the public less than 12 months previously.

 

Inside a Populus report – The Micro-Mobility Revolution – they highlighted that 70% of their respondents viewed electric scooters as a positive addition to urban areas – predominantly as they’re more convenient for shorter journeys, compliment public transport and extend their choices of transport as a whole.

 

In April, we saw the beginning of convergence between mobility platforms with Uber’s acquisition of Jump Bikes in April. Uber signalled it would be adding additional ways to move around your city directly from the Uber app. It has recognised the value of micro-mobility to its future and is prepared to spend capital and resource to get in the game.

 

The market is changing fast and that’s exciting but it hasn’t all been good news.

 

In China, a dockless Bike Sharing system was launched that charged cyclists just pennies for a half-an-hour ride. However, the initiative out-grew its demand, meaning there were too many bikes and not enough riders. The bikes were dumped –  in the streets, sometimes in rivers – and that lead to them being laid to rest in ‘bike cemeteries”.

 

In May 2018, the city of San Francisco temporarily banned electric scooters after residents complained of congested streets and illegal parking. The city received 1,900 complaints about the new vehicles. In August, San Francisco Municipal Transportation Agency announced Scoot and Skip as the winners of its e-scooter pilot sweepstakes, bringing e-scooters back to the city.

 

Across the Micro-Mobility industry, growth is being matched with experimentation and a healthy skepticism from local authorities. As in any rapidly evolving market, we are going to see more successes and failures in the next 12 months with efficient and consistent scheme management being a common challenge. No matter what type of scheme is being operated, end users need an optimised experience and operators need an efficient way to manage them.

 

As the market grows in complexity, Stage Intelligence uses its BICO AI optimisation platform to solve these challenges and simplify how schemes are managed. As our industry goes to a new level, we’re taking scheme management to new places with Artificial Intelligence.

 

Please get in touch if you’d like to know more about how we can help you get the most out of your Bike Sharing Scheme:  info@stageintelligence.co.uk