A data model for forecasting what it costs to care for parks and open spaces across Aotearoa New Zealand in 2022.
Parks, sports fields and waterfronts are where communities gather, and someone has to mow, clean and repair them. For years, deciding how often and at what cost came down to an experienced manager's judgment. Our brief was to turn that art of maintenance planning into a science: a model that estimates the right service programme for each open space and forecasts its cost by location.
This was conducted for a property company in New Zealand. Our interdisciplinary mainly PhD team mapped every factor that changes how long a site takes to maintain:
The site. Location, size and the secondary assets on it, like seating, bollards and rubbish bins.
The land. Flat, undulating or steep, and urban, rural or coastal.
The climate. Grass and weeds grow at very different rates in subtropical Auckland than in Christchurch, in the lee of the Southern Alps.
The crew. Which equipment is used, how it is used, and the travel time between sites, since time is cost.
The calendar. Summer cricket and winter rugby, public events, and hours when a site can't be mowed at all, like during school.
We compared modeling approaches, ran a gap analysis of the data available inside and outside the organization, and assessed the risks of relying on each source.
The team delivered a recommended modeling framework, a data gap analysis, a risk assessment and a final report with recommendations. It was my first look at a question that runs through all my work since: how to measure the everyday care that keeps shared places alive.