Big data needs a people focus, not just tech

Julian Francis
01 November 2016

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With data becoming integral to the functioning of future cities, Julian Francis looks at how it can be utilised to meet the urban challenges of the future.

I was recently part of an industry discussion looking at how the cities of the future would be able to use technology and data to meet the challenges they will face in this century. While preparing, it occurred to me that in all the discussions we are having about big data we seem to be more focused on technology than people and that this may be the Achilles heel of the whole debate. 

I have, therefore, decided to set out what I see as the challenges that big data poses to people and how we can meet these challenges so that the advantages of new technology can be achieved. 

I see three main barriers to the use of data and technology in both the public and private sector and these are:

• Data-free decision making,
• Data duplication
• Data discomfort

Let me deal with each of these in turn. 

Firstly, data-free decision making. Despite all the new technology that is transforming our lives, it is still the case that choices about policy, strategy, or other actions are made without critical examination of evidence of problems. Decisions made without close examination of relevant data can lead to working on problems that don’t exist, or working on problems that do exist but won’t be solved through the proposed solutions. 

When data is made widely available in a useful format, there is greater opportunity for everyone to use data when making decisions. We can, and should, use data before a programme begins: to identify what the problem is, the extent of that problem, who or what is most impacted by it, and then devise a data-driven strategy for addressing the problem.

Secondly, critical data is stored and edited by different actors who are not transparent about methodologies and do not share the data leading to duplication. Data duplication stems from a lack of transparency around the methodology for data production, maintenance, and storage. As time progresses, the differing methodologies lead to significant discrepancies in the quality and contents of data and natural human bias leads each to strongly believe their own methods are the best. 

The same information, transparently displayed and described, combined with an opportunity for everyone to weigh in on methodology, vet the data, and utilise it, can benefit the entire community. With one trusted source, each silo can spend less time creating and maintaining data, and more time utilising it to make change.

This leads on to the final issue of data discomfort. Data can be intimidating and overwhelming to the average person and can act as a significant barrier to use. Many staff members of policy makers lack data literacy skills which prevents the engagement with the subject. A critical element of increasing transparency and accessibility to encourage shared ownership, accountability, and data-driven decision-making, is training. Data can be overwhelming, confusing, or even boring to many people.  

This means that organisations may be hoarding data without analysing it because IT and decision makers find themselves in a situation where neither is able to communicate to the other. PwC has highlighted this problem by pointing out that decision makers and IT always have had difficulties talking to each other. 

Traditionally, organisations create requirements and IT executes them. In the world of exploring data, that doesn't work so well anymore. The knee-jerk reaction of IT is, "we're going to collect data and manage it and you guys figure out what to do with that". The problem is that, due to a lack of literacy, a sophisticated analysis required to glean meaning from data is often beyond decision makers. New organisational approaches are need to combat this trend. 

All three issues are connected and one cannot be solved without consideration of the other two. Decision makers will not be inclined to use data in the examination of issues if they do not understand what the data is telling them or if they have to struggle with different departments or organisations storing data in different ways. 

We must invest in the human element as much as we do in the technological element if we are to truly realise the benefit that big data promises us.  

Julian Francis is the director of policy and external affairs at the Association for Consultancy and Engineering.