The school which was too small

The current INFORMS blogging challenge/theme is about "O.R. and politics". It reminded me of a student project a great many years ago. It was never suitable for a research paper write-up, but a blog is an appropriate place to recount what happened.

The city had expanded, and a large housing estate had been built. Part of the development was a new primary school. However, before the estate was complete, the school became overcrowded. It was too small. Not much could be done to provide more space. The local politicians were embarrassed and the local media were not slow to blame them. The student (B) and I were asked to help the council officers make better decisions in the future.

So we interviewed people, read literature, and did our best to become familiar with aspects of planning. We quickly realised that the whole mess was multi-criteria, and many criteria were non-numerical. One of the attributes of O.R. should be the ability to cut through messes. For simplicity, here, we reduced the problem to a two way table. One dimension was the forecast demand, reduced to “Low”, “Medium”, “High” and the size of school “None”, “Small”, “Medium”, “Large”. In each of the twelve cells we wrote down aspects of the consequence of the two dimensions, and then iterated through meetings in which stake-holders could contribute their ideas. So the table of twelve cells became a tool for thinking with for planners and decision-makers. It could be – and was – used in other new developments in the city and region. Nothing high-tech, but we had helped to make the mess less messy. B went on to a career in O.R. and other messy problems.

Among the gems that we learnt along the way were the following:
(1) It takes about five years from initial ideas to opening a school, so the children who will use the school are being born at about the time of those initial ideas;
(2) Families with pre-school children are much more mobile than others, so it is not possible to forecast demand by local surveys of families;
(3) The forecasts made in the past had gone awry because of world-wide economic upheaval;