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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

Big Data Innovation in Bike Share Schemes

Big data is changing how we experience cities and enabling us to live healthier, happier and more productive lives. As cities become smarter, big data is being used to reimagine transportation and how we get from A to B.

Every city is producing vast amounts of data every hour and every day. Increasingly this data is being captured and put to work creating new solutions, processes and experiences that improve how a city functions and is enjoyed by citizens.

Data can be used to improve, urban planning, health care, sustainability, transportation and just about every aspect of a city. The “smart” in Smart Cities is about taking this data and rapidly turning it into actionable insights.

According to IBM, a Smart City “makes optimal use of all the interconnected information available today to better understand and control its operations and optimise the use of limited resources”. It makes cities better places to live and enables the best use of what a city’s budgets, space, people and technologies.

By 2021, open and shared data has the potential to add $2.83 billion (10.4 Billion AED) to Dubai’s economy every year, according to a report produced by KPMG. That is a lasting and long-term impact on the city of Dubai and results from using data in a Smart City environment.

While Smart City deployments continue to grow, transportation is an area where we are already seeing the direct impact of data on how citizens live day-to-day. In modern cities, Bike Share Schemes have emerged as a healthy and efficient means of commuting and navigating a city.

These schemes are taking the Smart City concept and applying it to local challenges and succeeding in growing ridership and providing more citizens with healthy and efficient transportation.

It’s this citywide data that is at the heart of the three pillars of smarter public bike sharing system as set out in the Policy Framework for Smart Public-Use Bike Share by the Platform for European Bicycle Sharing & Systems (PEBSS). Data influences how rider priorities are met and how cities offer suitable conditions with sustainable technologies and innovation. Smart Cities support Bike Share Schemes by considering the people, infrastructure and technology elements.

To make data work for Bike Share Scheme operators, it needs to be collected, managed and analysed effectively. This is where Artificial Intelligence (AI) plays a crucial role. AI-based platform manages all available data to deliver valuable insights to operators. The illustration below highlights this.