Challenge LDN: a data science challenge

The GLA delivers an Infrastructure Coordination Service (ICS) with the overall purpose to help plan and coordinate infrastructure delivery. This challenge focusses on developing the planning for growth service line of the ICS. We wish to better understand the certainty of local authorities’ growth projections to support utilities to better plan infrastructure in line with projections of demand.

While data on planning permissions are publicly available through the Planning London Datahub, it is still challenging to estimate the likelihood of planning applications making their way through the planning process. This is due to a range of challenges:

• There is often a lengthy process between application and commencement dates, approx. 2/3 years, and sometimes longer if further approvals are sought, which can make it difficult to predict when growth will happen. 
• Not every application will eventually proceed to development as it may not get approval or may be withdrawn. 
• There is uncertainty around non-standard coding conventions between London boroughs and missing data such as commencement and completion dates. 

These challenges impact the ability of utilities to plan their capacity around projected future growth. This affects Londoners as it can cause:

• Delays to development when sites are allocated without utility context, which ultimately causes delays to delivery of new housing 
• Disruptive retrofitting of new developments, which impacts their costs, economic efficiency and delays delivery
• Utility resilience is eroded as they are ‘sweated’ to meet unforeseen demand 

Improving this process will lead to reduced disruption, increase the likelihood of achieving sustainable housing targets, and help maximise the value of existing utility assets. The GLA Infrastructure team have identified a strong need for utilities to better understand projected growth so they can plan infrastructure accordingly and justify investment decisions.

We were looking for applicants to propose creative and innovative ways to develop a methodology for calculating certainty of development using PLD data and/or new publicly available datasets or approaches that may not have considered yet.