Appeals

I set out previously some work I’ve been doing on the quality (defendability) of planning decisions, and published it as a table. I then turned it into a picture broken out by region. In showing it to a few people it’s clear that there is something interesting going on here, and not necessarily what you might think. And, in a final flourish, I mash the data with another public dataset and ask “does having a plan mean you make better decisions ?”

The East of England

This post takes things a little further and turns this mash-up of public data into pictures using my favourite plotting tool ggplot2.

Benchmarking – improving planning services

(this article is reproduced with the permission of the journal of the TCPA)

The Planning Advisory Service (PAS) is a government-funded programme of improvement for local authorities. Eighteen months ago we began a project for managers of planning services. This is the story of one authority, Hastings Borough Council, who were in our very first benchmarking group of six coastal authorities in the South East.

The most common performance measure published by planning authorities is National Indicator 157 (NI157), on speed of determining planning applications. Hastings’ performance against NI157 (centre top in the chart above) showed a slight decline over the last four years compared with that of its peers. Our work with this group was designed to get underneath and behind this sort of statistic to help unpick what was really going on and so help them to understand the implications for costs, time and performance.

Super planning authorities

A little while ago, I was presenting some of my geeky stats to a room full of people. We were reviewing how variable the workload coming into a planning department is – much more than you’d imagine. My argument is that simple performance measures (we will validate 90% of applications on the same day) are pointless and act to demotivate people. Anyway. As it happened, a couple of authorities in the room were planning to combine their back offices. They asked a really basic question – “Would combining our workloads smooth out the peaks and troughs, or make them worse ?”. It’s an important question. At the time, we eyeballed it and reckoned that the answer was “no, it would probably make things worse”.

What with the formation of “super” authorities in the news recently, when another person asked me a similar question recently I thought I’d try to answer it properly. Like many simple-sounding questions it actually is quite tricky to pin down. This is my attempt, and given that I’m not a professional statto your comments and criticism is welcome. Let’s find out whether there is an economy of scale to planning applications.

MEPS tools part 2 – “the factory gate”

After a fairly heavy set-up, this is a more relaxed look at some of the visualisations possible when you have benchmarked your data. This, if you like, is the pay-off for the hassle of aligning your data with the standards. Our first one is nicknamed “the factory gate”, and treats the application system as if it were a manufacturing plant.

MEPs tools part 1 – installing R, ggplot2 and sample data

To ease the burden of supporting our benchmarking project “managing excellent planning services” (aka MEPS) we have been experimenting with some stats toys. While this started out as a “howto” in excel, the idea of being welded to a mouse for the next few weeks did not appeal. This is the technical set-up, where I describe in some detail the tools and code used to make the graphs that benchmark performance. Following on from this I go through the five sets of visualisations that support MEPS. If you want to know how we made it, or if you are living in a local authority trying to find ways of tracking performance, this might just be useful.