Staring at a Swiss clock mechanism, it is difficult not to marvel at the design process that created such a masterpiece of accuracy and reliability. So why, in the same world, do people still wait for hours for buses that never turn up?

For the most part, transit agencies design their fixed bus routes on the basis of imprecise historical data, anecdotal evidence, or even gut feeling. What’s more, routes are rarely altered to suit changes in demand as cities grow and populations move around.

But in today’s rapidly changing mobility landscape, riders expect ever more convenient and reliable options. In response, some cities are proactively building the future of transit based on innovative shared-mobility solutions. This includes microtransit, which blends the convenience of ride-hailing with the efficiency and sustainability of public buses.

At Spare, we strongly argue for using microtransit to flip transit on its head, because poor transit planning results in transit deserts that disproportionately affect vulnerable communities. This has been dramatically brought to the fore by the COVID-19 crisis.

In other words, ‘business as usual’ is no longer an option for transit agencies. They must adapt to suit their riders’ needs, and fast.

That means improving right from the very start: at the planning stage.

The point of planning

Without rigorously simulating transit demand using real-world data, transit agencies risk designing transportation systems that work for nobody. Oversights include introducing a new service in the wrong part of a city, running it with not enough vehicles, or creating impractical timetables.

Ultimately, any miscalculation can have important cost implications for the agency and may affect the usability of the service for those who rely on it to get around.

Spotting an opportunity in the market, Spare stepped in to bridge the gap between antiquated planning practices and modern on-demand software platforms. We developed Spare Realize, a sophisticated network simulation tool, to run rapid and informative simulations during the planning and operational stages of transportation services.

We have deployed Spare Realize to advise on the design and implementation of microtransit all over the world: the United States, Japan, Norway, Spain… Our goal has been to inject a heavy dose of science into a field that often sees itself as a bit of an art.

So what makes Realize so powerful?

Stop guessing, start planning

For a microtransit service to be successful, special thought should be given to when and where it should operate, whom it is likely to serve and therefore impact, the service model it should follow, and its potential costs and returns.

Spare designed a four-step process to break this down into manageable chunks:

Spare’s four-step process for simulating microtransit systems.
  1. Estimate the total volume of demand for microtransit in the area of interest
  2. Distribute that demand realistically by trip type, origin, destination and time
  3. Run simulations in Spare Realize to generate performance and cost metrics
  4. Perform in-depth analysis of the results, and make recommendations

Each of the four steps is rigorously data-driven, to ensure the simulations are as realistic as possible, and the insights are actionable for Spare’s clients. We draw on a wide variety of datasets, from average passenger count (APC) data and travel surveys provided by transit agencies, to open-source census and land-use data.

Spare’s past experiences in simulating and running microtransit also help to validate our models and benchmark the results. So Realize gets better and better over time.

Some of the data sources used to power Spare Realize.

Pulling the levers of microtransit

By stacking appropriate data layers together, it is possible to predict where and when different trip types will start and end. For example, we build ‘transit dependency’ maps that combine income, vehicle ownership and education data to identify demand hotspots in residential neighborhoods. We also create ‘recreation services’ maps that predict demand for shopping and entertainment using location data from open mapping APIs.

Stacking data layers to predict where and when trips will occur in a city.

Each Spare Realize project is fully customized to suit an agency’s needs. For instance, we created an independent data layer that simulates demand for healthcare, to help guide our partners planning new microtransit zones in response to COVID-19.

The interactive map below shows the trips simulated by Spare Realize in Oslo, assuming people mainly travel to healthcare, grocery stores and green space in times of COVID-19.

Kepler.gl embedded map

Moreover, to empower agencies to make the best decision to achieve their goals within budget, we simulate a variety of demand scenarios and service levels. This gives agencies a much clearer understanding of the tradeoffs between a cheaper, more efficient service and a pricer, more rider-centric service.

Simulation = insight

Spare Realize simulations have brought crucial insights to our partners, including:

  • Discovering potential for microtransit: It is exceptionally difficult to pinpoint where microtransit makes the most sense across a city. Realize highlights hotspots of ‘microtransit potential’ to help transit agencies craft the layout of their service zones. For example, Spare helped a Norwegian agency identify transit deserts specifically relating to seniors, to fill the gaps with microtransit.
  • Predicting performance: Once potential microtransit zones are identified, Realize reports on a host of key performance indicators (KPIs) to assess the return on investment in each zone. This capability helped one of our partners in Quebec to focus on the best-value zones from a shortlist of ten neighborhoods.
  • Designing ideal operational models: A microtransit zone has to work for the people to use it. In Realize, it is possible to simulate a variety of operational models (e.g. door-to-door, or stop-to-stop), and their impacts on riders. We demonstrated to a partner in Michigan that a stop-to-stop service might be more beneficial to their service in the long run, even though they had initially envisaged a strictly door-to-door service.
  • Right-sizing transit fleets: Realize estimates the maximum vehicle occupancy that can be expected in a service – and therefore the vehicle size required. Right-sizing can substantially lower costs because smaller vehicles cost less to purchase, run, and maintain than traditionally sized transit buses.
  • Optimizing each revenue hour: By indicating the most optimal time windows for services to be run, Realize reveals the value of running an additional vehicle or duty hour. This feature helped our partners in Texas and Quebec to better grasp the cost tradeoffs of different operational scenarios.

For data-driven planning to be most successful, transit agencies should build it into their decision-making processes from the very start. By correctly identifying and configuring microtransit zones, choosing the optimal operational model and right-sizing their vehicle fleets, transit agencies can see savings of up to 70% compared to business-as-usual.

Spare Realize provides a guiding hand every step of the way.


As the COVID-19 crisis profoundly shifts mobility patterns around the world, transit agencies must not only respond to dropping ridership today, but also prepare for the future. Once the effects of the pandemic wane, public transit has the opportunity to propel itself into a new era. By adopting data-driven planning and harnessing the power of multimodality, agencies can recast this crisis as an accelerant of innovation.

Staying humble

Although Spare Realize has transformed microtransit planning around the world, we stay humble about its limitations. Models rely on a lot of assumptions and simplifications to represent complex patterns: traffic congestion can be difficult to account for, and human behaviour is notoriously unpredictable.

Our solution to this problem is to constantly engage with those who understand the reality on the ground: stakeholders. Only by setting up feedback loops with planners, transit officials and riders can we ensure that our data-driven insights bring true value. Or, as the British statistician George Box once noted:

‘All models are wrong. But some are useful!’

While data-driven planning is a key part of any transit solution, we also help our partners implement our recommendations. Whether it's launching an entirely new vehicle fleet, tweaking microtransit zones in real time, or marketing a new service, our expertise ensures we reach our full potential together.


Spare is all too aware of the impacts the COVID-19 crisis has had on transit agencies around the world. We have specialized resources on our website, including a guide to help agencies design safer public transit during the pandemic.

If you need rapid response support, we would be glad to provide help. Feel free to reach out directly to our CEO Kristoffer: k@sparelabs.com. We’re here to help you.