I was recently asked this question whilst on a property panel discussing how to use data to guide investments decisions in property.
I was recently asked this question whilst on a property panel discussing how to use data to guide investments decisions in property.
This is a great question to ask anyone who offers an ‘all in one place’ solution because part of the value these services offer is inherently based on bringing together datasets.
This couldn’t be more true for off-market property sourcing platforms. Here’s what I went for.
At the time, I said planning application data. My answer is still the same today but I have now included the need for this information to be searchable.
For many of us, the ROI is made on a successful planning application. This is where much of the risk lies and also the reward.
In England, since the start of 2021, 25% of applications for residential properties have been refused (Source: SearchLand Planninng Data).
A small percentage of these will go on to be overturned at appeal or resubmission but the cost of a refusal can still be detrimental to your work.
This is why one of the key questions we should be asking ourselves when on the hunt for development opportunities is ‘will this site get planning’. Another way of phrasing this question is ‘will there be development here in the next 5 years?’.
If the answer to the above is yes then it’s your job to get that site on your portfolio, rather than someone else’s.
Back to the value of the all in one place solution. This is the understanding that the data is more valuable when combined than when fragmented, say, hed by different organisations on different websites.
An example of this would be to assess the extent of flood zone coverage over the boundaries of a plot of land you’re assessing for development.
This is easy enough. head to Land Registry, find the title you’re after and pick up the title plan for £3. Next, generate a flood map and now you’ve got yourself some usable information.
However, data is a means to an end. What is that end? Well, for most this is the planning application approval I mention above. So we then need to assess how these planning constraints will affect this desired outcome.
It takes many many more pieces of data to assess a plot of land so at this point it’s a matter of rinse and repeat.
This is why SearchLand has over 35 spatial layers that we link to every title. So that example of checking flood zones against the title boundary can be done in one click.
The answer is a bit of a cheat, and that’s why I like it.
Why do we care about the extent of the flood zone, or whether our site is in the conservation area, near a listed building or within the Green Belt?
These are all planning constraints that’s why and will affect your decision and the level of risk associated with a site.
So if I had one dataset, it would always be planning application data. These data points provide a litmus test for how the council views different types of applications, how they assess constraints and how they assess housing need.
Not using this data is like preparing for an exam without taking any practice papers.
There is a catch. A big, hairy, ugly catch. In order to get planning application data, you have to go through planning portals.
These portals are about as exciting as a coffee stain.
That said, SearchLand has done a good job of turning these portals into our most useful datasets. We’ve done this because we see planning applications as data just like property sales data.
And there is a lot of it.
There are 324 local planning authorities in England, which in SearchLand amounts to just under 20 million planning applications.
Each of these applications has lots of data attached to it which we can then search. This includes:
That’s right, you can search by case officer! This isn’t a name and shame feature but a due-dillegence feature. Just been allocated an officer or going for an appeal? Find all the applications your officer has submitted and see what makes them tick.
Planning is a people business too.
Don’t take my word for it, as an ex-planner I am biased and primed.
Leave a comment for what data set you’d choose!
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