Research showed that posting water schedules online did not improve the ability of most users to understand their intermittent water supply system
An interdisciplinary case study from researchers at the Department of Civil & Mineral Engineering (CivMin) and the Department of Geography & Planning demonstrates the challenges that can arise when governments adopt a ‘smart cities’ strategy — and points the way toward possible solutions.
The study revolved around the city of Coimbatore in India’s Tamil Nadu state. Municipal water there is supplied via an intermittent system, which is turned on and off for each neighbourhood at various times throughout the week or month.
“More than a billion people around the world get their water intermittently,” says Professor David Meyer (CivMin), who studies these types of systems, including how to effectively model them.
“For many cities, upgrading to a 24/7 water supply is just not feasible. But one thing they can do as a stop-gap measure is to post the schedule online, so their users can at least plan around the times when they will receive water.”
This was the case for Coimbatore: in line with the Smart Cities initiative launched by India’s national Ministry of Housing and Urban affairs, the city decided to post its water schedules online.
“When they started posting the data online in April 2022, it gave us an opportunity to study the impact that open data and digital transparency can have on municipal services,” says Professor Nidhi Subramanyam from the Department of Geography & Planning, co-author along with Meyer of the new study, which is published in Environmental Research: Infrastructure and Sustainability. The research was funded by a Catalyst Grant from U of T’s Data Sciences Institute.
“As our study shows, it turned out to be a pretty laborious task, and it just couldn’t be sustained. They stopped posting after just a few months.”
Meyer says one of the key challenges was the format in which the data was provided, as well as its sheer volume.
“Each day, city staff would post a 50-page PDF document, a digitized version of the internal paper documents they used to determine the water schedule,” he says.
“But as a user, you don’t care about most of that: you only want to know when your taps are going to be turned on. To find that, you have to scan through hundreds of rows of text, looking for your street name. And it might be in a different place each time — or it might not be there at all, which would mean that you’re not getting any water that day.”
Meyer uses the analogy of a rainstorm in a desert to describe the switch.
“Before this, there was no data at all, like a dry desert with no rain,” he says.
“And then all of a sudden, you have a torrent of data, like a flood. But that doesn’t make things better; instead, it creates a whole new set of challenges.”
In the paper, the team outlines simple changes that could have made the data much more useful. For example, posting the data in the form of a machine-readable spreadsheet instead of a PDF would have enabled third-party developers to create an app that automatically sends users a text message when their water is coming on.
“Why didn’t they do that? To be empathetic to the city workers who we interviewed, a lot of it comes down to resources,” says Subramanyam.
“The utility didn’t hire anyone to be in charge of the new system, or to think through the best way to do it. Instead, they just added it to the list of tasks that current workers had to do, without increasing their pay or providing incentives. So it’s no surprise that they did it in a way that would be easy, rather than useful.”
“There’s also an element of ‘silent resistance.’ If you are asked to take on a new project that significantly adds to your workload, but you are not compensated for it, you have a good reason to want the project to fail. And in the end, that’s what happened here.”
Meyer says that while implementation was not effective in this case, the strategies of digital transparency and open data still have the potential to improve how cities work. He hopes that the team’s work can point the way toward best practices that might enable these tools to better live up to their promise.
“Right now, there’s no standard for how to do this effectively, so everyone is just kind of making it up as they go along,” he says.
“What we’re hoping is that by highlighting what didn’t work in this case study, and by suggesting what might have worked better, we can set the stage for a more successful implementation.
“If more places provide open data that is accurate, timely and accessible, it will do a lot to reduce the uncertainties and stress resulting from inadequate water supply.”
By Tyler Irving