A roadmap for a data-first city
In 2017, The Economist declared that data “is the new oil.” This statement rings true today; without data, cities are unable to tell if policies and programs designed for the betterment of the city are working or not. The adage of “you can’t improve on what you can’t measure” bears out. City planning is no longer a case of merely lining up roads, locations and utilities. We must design systems that yield measurable outcomes and contain analogue signals that can be detected by sensors and captured as digital information on data platforms designed for multiple users.
On the plus side, digital applications are well-suited for data collection as this task can be tedious and laborious. Digital tools can furthermore provide performance insights on demand in the form of real-time data for constant monitoring or the simulation of future infrastructure scenarios to plan and adjust for optimal city outcomes.
At the same time, however, city governments are treading warily in pursuing digital pathways. Not least, there are institutional barriers to digital adoption as individual departments and agencies tend to collect data for their own purposes, resulting in silos and barriers to the pooling of knowledge.
Breaking down these walls is difficult, and it requires tenacity and strong leadership to shift public organizations into new paradigms. Unsurprisingly, public investments in technology have mixed results: different data collection systems that don’t talk to one another; systems that are either designed wrongly or become obsolete in a short space of time; and, in the end, the usefulness of data to help make public decisions is questionable.
To avoid these pitfalls, cities are urged to be mindful in both uncovering the right kind of data and using that data in the right way.
Measure the right data. Collecting data for the sake of collecting data serves little purpose if the right data is not being measured. Quality rather than quantity should be the approach taken. This requires a level of systems thinking to connect seemingly unrelated sources to causal relationships. For example, measuring air quality should be linked to public health indicators to establish a meaningful relationship between transport planning and traffic reduction. There is a need to involve key stakeholders as they are often the users as well as holders of critical city data. User research is vital to make sure that the right data is being measured.
Know what the data is telling you. The scale and complexity of data can often be overwhelming and confusing if the outcomes are not properly identified and analyzed. Hence, interpretation of data is crucial. For instance, the usage of particular facilities gives us an idea of emerging user behavior patterns, demographic changes or new business trends. Conversely, occurrences of high impact incidents like storms and heatwaves tell us of impending events. In both cases, we should use the data to plan and realign our public systems. This form of predictive logic is becoming increasingly commonplace but again this relies on the accuracy of the data and what signals the latter is giving.
Put the data to work. If the reported data suggests something is amiss, then corrective action should be immediate and visible. Take for instance, leakage detection in drainage pipes. Data collection on the location, height, attribute, and other information of the drainage pipe network, as well as data on the river water level elevation, groundwater level elevation, sewage treatment plant and pumping station operation status, can assist operation scheduling, maintenance management, and rapid response. This means managers can quickly grasp the actual situation of the pipe network and correctly deploy appropriate measures in emergency situations.
Make sure everyone benefits. Clearly, the capture of data for city management must yield benefits for inhabitants whether it is for purposes of security, efficiency or convenience. Feedback from users is an effective way of finding out if public systems are working or not. Equally imperative, people from minority classes should also benefit and not be excluded from the advantages of digital enablement. This means that the systems should be able to assimilate data from different stakeholders according to specific needs.
Communication of the benefits must be obvious. Other than economic benefits, the social and environmental benefits must be translated into an understandable and obvious manner to stakeholders. The use of mapping and spatial data allows a powerful multi-dimensional visual display of how planning and infrastructure has or will affect the city environment and the communities living there.
Avoid the “trust me” trap. Or rather, avoid raising mistrust and suspicion on the part of the public. Obtaining personal data as part of data collection always poses ethical problems on respecting privacy and individual rights. We have to move carefully when introducing systems, which are designed to collect personal data and demonstrate that the latter will only be used for city management purposes to assure stakeholders.
Be open and honest. Inevitably we will make mistakes as unprecedented events such as the coronavirus strike us. But in being transparent and accepting that there is a learning curve to be transcended, we can establish the right collaboration and cooperation amongst different stakeholders to make the city future ready.