Data-driven decision-making is becoming increasingly important in Rwanda. Very large datasets are generated in real-time across the economy: each time you transact using mobile money, or purchase a bus ticket – to name but a few examples – data is generated. If public and private decision-makers can effectively draw on this data, they can begin to make increasingly impactful evidence-based decisions. We saw the positive effect in the health sector when COVID-19 illustrated the importance of using data to make contextually relevant and timely decisions. The same potential exists for many other sectors.

Transport is a case in point. A well-functioning transport system is instrumental to improving the living standards of Rwandans, as moving from point A to B without undue delay or cost is key to effective economic participation. Cognisant of this, Rwandan policymakers made increasing the ease of mobility and the developing an efficient transport system two of the key pillars of Vision 2050. Yet, while significant progress has been made in developing a sustainable and inclusive bus transport network in Kigali, there is evidence to suggest that the bus network is not aligned with the transport needs of citizens.

Initial analysis of bus transport tap-in data conducted by Cenfri and 71point4 as part of the ongoing Rwanda Economy Digitalisation Programme shows that more than 60% of bus passengers use the bus fewer than six times in a month, roughly just once a week. Passengers were also more likely to purchase tickets during the middle of the day, outside traditional peak commuting hours. Recent consumer research reveals that long waiting times and queues, as well as unpredictable bus schedules frustrate citizens, prompting many to use motos even if they are more expensive than buses.

How can policymakers foster the development of an effective and widely used public transport system?

Data can help. There are a number of new data sources that, if effectively leveraged, can allow insight into parts of the transport system that were previously difficult to understand. Utilising the full potential of such data sources can enable decision-makers to develop the transport system in a way that aligns with commuter needs and transit patterns.

The first source is ticketing data. Many modern public transport systems now use digital systems to administer passenger tickets, and Kigali is no exception. With the support of digital services providers like AC Group and Centrika, bus operators have implemented a card-tap system that generates data each time a passenger taps in to ride the bus. This smartcard data provides a host of valuable information, including ridership, the time that the ticket was purchased, the route it was purchased for, and the ticket price. Tap-in systems can also utilise GPS technology that provides coordinates for points or stops where customers tap in.

GPS functionality on the bus fleet also has the potential to show the precise location and speed of transport vehicles as they move through the city. GPS data generated on other modes of transport like motos and taxis can also be used to understand usage of alternative means of transport. This could assist in determining how best to integrate complementary transit modes and to gain a more systemic view of mobility patterns.

Exploiting the full potential of such datasets can help on three fronts:

i. Bus capacity planning: The government of Rwanda’s plans to acquire 300 buses to address public transport shortages in Kigali would be a welcome investment. Smartcard and moto data can identify the primary pressure points in a network and can be used to direct the new busses to where they are needed most.

ii. Bus route planning: Planning bus routes optimally requires a global view of the utilisation of the transport network. With the use of smartcard data, it is possible to assess whether key arteries are performing as expected, and if smaller routes are being utilised at all. Route planning can be optimised by integrating GPS data from buses and motos to create a view of total mobility demands.

iii. Priority lane planning: Priority lanes are key to the success of public bus transport in many cities internationally. However, their design and implementation require significant investment. Given limited resources, this investment must be targeted towards meeting the transport needs of as many passengers as possible. Smartcard data enables officials to identify the most in-demand routes, and by tracking how quickly or slowly buses move through these areas, GPS data can help to identify the routes that most warrant investment in priority lanes.

Indonesia’s capital Jakarta provides a powerful example of the effective use of GPS and tap-in data. As part of the Jakarta Smart City venture, real-time data on the TransJakarta bus system is used to enhance bus service planning and delivery. The project uses GPS data to study bus speeds, the number of operating buses and bottleneck ratios in twelve corridors dedicated to TransJakarta buses. With this information, Jakarta Smart City identified problematic routes and locations across the city, enabling them to reduce traffic bottlenecks and detect anomalies on affected bus routes. The project also analysed tap-in data to understand passenger behaviour, weekly commuter patterns and origin statistics. In this way, it could pinpoint the number of hours between consecutive trips, times of peak demand for bus services and the most utilised routes. Tap-in data combined with fleet GPS data was also used to determine which stations experienced the longest waiting times.

Likewise, for Kigali, tapping into the powerful sets of data we generate daily holds immense potential for the optimisation of bus system planning.

This is not to say that data analysis using these emerging sources is a silver bullet. While e-ticket or GPS datasets are able to show how people use particular routes or modes of transport for their daily mobility needs, it does not offer insight into their underlying motivations. The continued use of passenger surveys, user interviews and regular consultation with key supply-side role players are essential to give context to the data trends identified. Drawing on this variety of complementary information sources allows for the development of a holistic, commuter-focused view of the transport sector that will evolve as the City of Kigali does.

James Scott is a research analyst at 71point4, Lebogang Mashego is a research analyst at Cenfri, Vera Neugebauer is an associate at Cenfri, and Morongwa Marutha is a research intern at Cenfri.