Theory v data embracing digital planning reform

The Savills Blog

Theory v data: embracing digital planning reform

There is a line in Arthur Conan Doyle’s A Scandal in Bohemia whereby the famous Sherlock Holmes declares:

“It is a capital mistake to theorise before one has data…”.

This line refers to the common human trait of conjuring conclusions based solely on theory, or biases. Holmes’ musings continue, explaining that without evaluating data: 

“Insensibly one begins to twist facts to suit theories, instead of theories to suit facts”.

Holmes, being a genius detective, knows that scientific reasoning relies on facts rather than assumptions or beliefs.

As a practitioner in urban design and spatial planning, I often wonder if we rely too heavily on theoretical thinking, rather than data. With the huge advancement of IT systems in recent years, should data play a more central role, dictating how we analyse, make decisions and develop consensus? If the answer to this question is yes, then it raises another question: 

Is the onus on human nature to adapt to data systems, or should data systems adapt to human nature? 

For data systems to be effective, they must be digestible and easy to sift through, otherwise the value will continue to wither, particularly when competing against theoretical thinking. 

Practical issues continue to impede the ability to draw benefits from data. To fully understand the impact practical issues are causing, we should reflect on how human nature might respond; that way we might be able to figure out how to fix it. 

At a fundamental level, the main practical issues for data incorporation include: 

  • The break-up of data
    • Built environment data is typically dispersed across multiple platforms, industry sectors and local authorities. Even when the data is open source, it takes experience to know where to search. 
    • Our understanding of human nature tells us that when something is too difficult to find, we will eventually stop looking.
  • The inconsistency of data
    • Data is derived from many different sources; however, a lack of standardisation means that it can be difficult to decipher or match-up with other datasets. This is key to informing built environment initiatives, as often numerous data insights will be used to help frame an initiative. Without standards, it becomes difficult to trust data. 
    • Our understanding of human nature tells us that when we don’t trust something, we tend not to rely on it, so it is disregarded.
  • The accessibility of data
    • Not all data sets are open source, meaning that some require payment to access, or are not publicly available at all. This provides a barrier to entry for those looking to proactively engage, but can’t, as they don’t have the resource or means to benefit from data driven analysis. 
    • Our understanding of human nature tells us that once barriers to entry exist, we become disenfranchised, which in turn leads to increased scepticism and an unwillingness to take part. 
  • The quality of data
    • For data to be effective, data must be accurate, relatively up to date and legible. If the quality of data is poor, it could lead to flawed analysis, ill-informed proposals, and poor allocation of resource. 
    • Our understanding of human nature tells us that trust is a key factor in nearly every key decision we make. We need to know that what we propose or decide is based on a reliable source, so to ensure the desired outcomes are realised.

Other issues exist, such as the lack of skills and resources relating to data insights, cultural habits, and data privacy. However, these issues are likely to lessen over time once the fundamental barriers to entry are addressed. Further, advancements in Artificial Intelligence (AI) create real potential to overcome some of the user frustration when sifting through or handling data. Experience has shown us that true innovation tends to occur when industry needs and technological advancements coincide, so perhaps the time is ripe for digital planning reform.

 

Digital transformation

The digital and data teams within the UK’s Ministry of Housing, Communities and Local Government (MHCLG Digital) appear to understand the benefits data solutions can bring when it comes to streamlining planning processes, reducing subjectivity, and formulating impactful planning policies. Admirably, MHCLG Digital is seeking to empower planners, designers, development stakeholders and communities through the creation of more innovative digital tools that incorporate data. Overall, the objective is to make the planning process more efficient, inclusive, and reactive to broader socio-economic challenges.

Of course, there will be challenges to creating the level of transformation required. For one, as planning and urban design practitioners, we may need to re-evaluate some of our working practices. In some respects, time-spend on routine tasks is likely to reduce; however, the demand for knowledge and insight is likely to grow. Given that nothing is black and white when it comes to the built environment, theoretical insight is still required. To make better planning and design decisions for the common good, we will need insight beyond what data alone can cover.  

The backdrop to the Sherlock Holmes’ remark referred to at the start of this piece was a puzzle Holmes was trying to solve. In practice, I’ve always viewed the urban design role as solving a problem. If it were as simple as looking at the data, is Holmes underplaying the value his own personal insight will bring to solving the problem? 

Data can help decode the challenges faced and simplify the context, so we should embrace its advancements. However, it won’t solve the puzzle for us. For that, we’ll always need problem solvers.

 

Further information

Contact Barry Gaffney

 

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