Big Data Analytics & Placemaking
In this age of incredible innovation and technological advances it is becoming increasingly difficult for urban practitioners and local authorities to continue using traditional regeneration and economic development methodologies alone to achieve sustainable results. One innovation is the application of big data analytics to the urban realm to help provide detailed insights into how places are performing.
The modern world has become an incredibly well connected place providing significant opportunities to derive in-depth and accurate insights from the constant streams of data being generated. In fact, according to IBM “90% of the data in the world today has been created in the last two years alone”.
These insights include, but are not limited to: detailed movement patterns, dwell times, spend data, property market analysis and customer and visitor sentiments.
The effective deployment of big data analytics has the potential to redefine how urban practitioners make decisions related to places. Big data analytics allows to combine and analyse vast amounts of data collected over time in sectors such as planning, transport, licensing and regeneration providing in-depth insights on the development of places over time. These existing data sets can be further enhanced using newer and more detailed data available through technologies such as: cellular data, wi-fi, and card payment transactions. These newer data sets allow real-time analysis of places and provide the opportunity to measure impact assessments of developments.
Key urban management fields that big data analytics can support include: economic development strategies, masterplanning, regeneration, transport planning, public realm, properties and housing, and commercial space curation among others.
Data Analytics & Metrics
Big data analytics is driven by the application of various metrics to support the decision making progress of stakeholders. These metrics help urban practitioners to make informed, accurate and sustainable decisions. Smart Urban Management (SUM) data sets include:
- Cellular
- Social Media
- Open source - public
- Travel data
- Card transactions
Depending on the focus and outputs of the projects, SUM is able to collect and process extensive information and granular details on the following metrics:
Movement
Mobility patterns – directional footfall numbers, desired paths etc.
- Origin and destination area of visitors
- Transport modes (public, private, cycling, walking etc.)
- Distance and time travelled
- Dwell time
- Patterns around ‘points of interest’
- Congestion and bottlenecks
- Hotspots of activity
- Under-used areas and times
- Key transit places
- Catchment areas – (origin of visitors)
Behaviour
Socio-demographics (ethnic origin, social status etc.)
- Discussion topics – around events, incidents, points of interest etc.
- Sentiments analysis
- Sematic links – identify competing places
- Security perceptions
Economics
Transaction Volume
- Commercial diversity (sector break up etc.)
- Business hours
- Commercial real estate rents
- Commercial capacity – bench-marking sentiments against transaction volumes
- Spend satisfaction
These metrics do not include those that can be measured using existing data sets urban practitioners may already possess such as those related to licensing, planning, enforcement, crime etc. New data can be analysed together with existing data to identify bespoke places and the relationship patterns occurring within the urban realm.
SUM is pioneering the application of big data analytics to place making. For further information please get in touch using the get in touch tab at the top or the email address below.