nationally and regionally as well as additional open source data when it was available. Through the mobility data, we could investigate connectivity between hot spot areas and the rest of the UK. As cycling became more prominent in how people might travel, we linked total mobility estimates with other modal data to derive cycling estimates. This later became a new daily cycling series, which had not previously been created. And by bringing in more ONS census data we could move into predictive analytics, looking at key workers and shopping habits to estimate expected levels of mobility under key policies. Up to 32 different analytical products were being produced at peak, over four main areas, some of which are listed in the panel.
As cycling became more prominent in how people might travel, we linked total mobility estimates with other modal data to derive cycling estimates
A COMPLETELY NEW WAY OF WORKING
To enable rapid working against the intensely demanding timescales of the pandemic crisis, the team developed new ways of working on top of the already challenging move to remote working. Each time new analysis, data series or products were developed the team were quick to automate these and continued to improve them throughout. Enabled by shared software, we were able to ensure resilience by alternating who worked on
each task and through regular updates. Normally the Analytics Unit’s shortest projects last weeks to months, so this represented a completely new way of working for many in the team.
This work has produced evidence to support monitoring and decisions as the crisis has unfolded
FAR-REACHING IMPACT
This work has produced evidence to support monitoring and decisions as the crisis has unfolded. But in addition, while meeting the mobility information needs of the crisis, the team has ensured that the benefits of improved insight into mobility will be sustainable, meeting the longer-term needs of Government and
A WIDE RANGE OF ANALYTICAL PRODUCTS
The tempo of working, repeated needs from central government, and the department’s access to anonymised, aggregated insight from mobile telecoms data meant that at peak periods, the team were producing up to 32 different analytical products daily and weekly for different purposes, highlighting the range of possibilities that this sort of data presented. Products included:
Daily mobility updates
Looking at big trends in national mobility to answer questions on how mobility is changing as a result of lockdown, and throughout restart, as well as more focussed analysis on geographic areas and times of day.
Predictive Analytics
These products answered questions on what effect on total mobility should be expected due to the lockdown, so that this can then be compared to insights coming from the daily updates, and areas or times which were different than estimated can be identified.
Local lockdown connectedness
We also provided analysis for planners, identifying potential areas for future outbreaks and looking at how people are moving at different times of day.
Cycling
Data on trips by bicycle in near real time has not previously been available on a regular basis, but by combining the mobility data with other available sources the team derived a measure for the change in usage.
IMPACT | AUTUMN 2021
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