The growing power of the data analytics industry

The growing power of the data analytics industry

David Beer (University of York)

Following the England cricket team’s recent elimination from the world cup, Peter Moores, the England coach, caused something of a stir by suggesting that ‘we shall have to look at the data’. The response in the media was one of consternation – as was the public response based on the 953 comments that the Guardian article alone has already received. Both Moores’ statement and the media response reveal something of the politics of data. Moores’ desire to return to the numbers is suggestive of how embedded and routine data analytics already are in the production and consumption of culture. Data are seen to provide the objective means by which people can be judged or pushed to compete in lots of different ways.

As the philosopher Alain Badiou has noted, the things that are valued are those things that can be measured. Yet the media response and the reader comments show how the value of data is questioned when it inadvertently challenges the powers of independent thought, critical reasoning and human agency. This example from cricket is just one single instance of something that is far more widespread. Data and data analytics are now commonly used in multifarious ways to make decisions about us and to produce outcomes that directly affect our lives. What is often overlooked is the power of those providing data analytics in this order of things.

It would seem that not everyone would share Peter Moores’ ‘trust in numbers’ (to use Theodor Porter’s phrase). Yet despite this type of reservation, what is interesting is the emergent and growing power of data analytics in the production and performance of everyday life. What I’d like to suggest in this short article is that there is now a good deal of power in the hands of the data analytics industry. When organisations are confronted with what we now know are masses of data about us and with vast swathes of data accumulating at baffling rates, the problem is to find patterns, to render these data usable and to find out what the data can reveal about people. The scale of the data that are now produced is so vast that it is hard to know what to do with it all and the problem becomes one of turning numbers into knowledge. Also, alongside this, the data produced are not always created with particular purposes in mind. As a result there are attempts to repurpose the data so that it might be used in some productive way – they see what data they have and then try to work out how to use it. The data analytics industry is growing in response to this apparent need to make the data manageable and comprehensible. In some instances analytics experts are incorporated into organisations to achieve this. In other instances data analytics and data solutions companies provide outsourced data analytics packages for organisations to use.

I have recently conducted a small-scale study to look at the data assemblage in professional football. I found that this case study could be used to reveal some broader issues about the role of data and metrics in the production and consumption of culture and in the ordering of society. In general, I found that there are two ways that we can look at the growing power of this industry of data analytics. Both of these approaches force us to consider the way that data about us comes to act upon our lives, to cajole us in certain directions or to shape the chances, options and choices we make.

First, we need to think about the way that the data about us produces material outcomes in our lives. This would be to think about how decisions are made based upon the data analytics that are produced – such as visualisations, tables, proposed outcomes from recommendations systems, performance indicators, and so on. We might think here about how decisions in the workplace, in our schools, colleges, universities and so on are made based upon new types of data and analysis – then of course you have the data analytics performed by states and organisations, in consumer profiling or even in the apps we use to measure our lives. This is to think of data analytics as producing outcomes as well as simply reporting on what is happening. Decisions are made based upon the data analytics, which lead directly to outcomes and consequences for people. Similarly, we start to adapt our behaviours to suit the way that we are measured and to suit the analysis of the data about us.

By way of illustration, in the case of football we can see that decisions about player transfers, for example, can be data led. In these instances, players are recruited based upon the data about them. One player is chosen over another because of their stats and performance indicators. Here data analytics lead to financial decisions that have implications for the flow of capital but which also shape the lives of individual players and the production of the game of football itself. Similarly, the players themselves are guided by the stats that are produced when they play. Judgments are made about performance standards based upon those stats. From ball possession, successful dribbles, to final third penetration and pass completion rates. It has been suggested, for instance, that players will make decisions about what pass to hit based upon the need to complete as many passes as possible. The result is that the way the game is played, how the players conduct themselves and the coaching of players is shaped by data and its analysis.

We can imagine that this is not just about football, but that it might be about the social game that we are all a part of. We can perhaps think of ways that this is comparable in our own lives, about how the data about us encourage us to do certain things or to prioritise certain actions or activities over others. The analysis of data, in lots of different spheres, alters the performance of social life. It is not the raw data alone that have implications, it is the interpretation of those raw data that makes certain things visible or which illuminates certain actions or behaviours over others. In the case of football, most of the top-ranked clubs have sophisticated data analytics departments handling the management of the data they produce. In some instances even smaller lower league football clubs have data analysts on their staff in some capacity. And if you don’t play for one of those teams, and you are not a professional footballer, you can always become your own analyst and either play with the data produced by football matches, get yourself a pair of trackable football boots or even use the detailed stats databases on a football management game on your games console (which are now integrated with real world football statistics anyway). Beyond these in-house analytics, at football clubs, there are also a number of providers of various types of data analytic solutions – acting to help clubs with transfers and providing data insights for journalists, broadcasters, betting companies or individual sports fans.

Alongside this vast production and analysis of data, the power of the data analytics industry can be understood in a second way: by thinking about how the power of data analytics is imagined, presented and marketed by this industry. Data are not just material things they also have imagined powers. Data is often seen to have hidden values that are yet to be realised. They have the potential, we are told, to change the way we see things. Part of the way that data can produce outcomes is through the power that we imagine them to have. It is in the stories about the power of data analytics, the promises we are told that data hold, that we find a rhetoric that is hard to resist. The imagined power of big data is seductive.

Part of understanding the data analytics industry is to reflect on how it presents the promises of data and the power of its solutions and insights. This is not just about the actual material infrastructures that enable data to accumulate as we go about our everyday lives, it is also important to think about the way that the power of data analytics is imagined. It is in thinking about these imagined powers that we can understand how data analysis spreads across different social sectors and how it comes to be an increasingly prominent presence in various parts of our lives. In this regard, what we find in the case of football is a language and terminology that is also to be found in lots of other places. This is a language based on a profound faith in numbers, as embodied by an interest in increased objectivity in decision making, in the discovery of hidden value or concealed patterns, in the possibilities of fine-grained detail and ultra-accuracy, in the increase of efficiency and performativity, and so on. Data analytics are presented as being powerful in shedding new light on the social world. Although we might question, doubt or make sceptical comments about these promises they are now a part of how the increasingly data-led social world is understood and performed. So, data analytics operate directly on our lives whilst also being part of how our future is imagined.

We cannot understand the role of data in our lives or the broader politics of data without thinking about the role of the imagined power of data and data analytics. It is through such visions of the imagination that data led approaches to social organisation are justified and embedded in our lives. It is important to think about how we are measured today, but it is also important to think about how we are told that we might come to be measured in the future.

Overall then – given their scope, volume and density – the power and politics of data is in how they are interpreted. The way that data are analysed and the way that their power is imagined are a central part of this interpretation. The imagined power of data makes these analytics hard to resist or to question. When organisations, taking a similar line to Peter Moores, show a desire to ‘go back to the data’, they are actually going back to the outputs of the analytics whilst being informed by the imagined power of what those analytics might offer. Without us even realising it would seem that the data analytics industry is having, and will continue to have, a role in shaping our lives.

Data analysis is already shaping the culture we consume – the sports, the news, the TV shows, the games, the music and so on. Beyond this though there are many known and unknown ways in which we are measured and captured in data; at work, in our leisure time, in terms of our health, our consumption, our movements and locations, and the like. Data are a productive presence, with the data produced about us flowing-back into our lives in different ways. The expert input of the data analyst ensures that these data circulations operate smoothly. They envision the world through data, they make ‘big data’ comprehensible and manageable, they find ways of using data so that it can inform decisions and shape our lives.

The industry of data analytics is not just shaping the world through the application of data it is also imagining our social world in new ways in its depiction and promotion of the power of data. To understand the broader politics of data we need to see the data analytics industry as central to smoothing the passage of data circulations, but we also need to think about how the power of data is imagined and promoted in their hands. The social world, we are told, is being transformed by new forms of ‘big data’, but really the power of these data led transformations are in the hands of those analysts who provide the insights and who decide what it is that these data reveal.

 

David Beer is Reader in Sociology at the University of York. You can read more about the issues covered in this article in ‘Productive Measures: Culture and Measurement in the Context of Everyday Neoliberalism’, which was recently published open access in the journal Big Data & Society. You can also read more about the background to this work in the book Popular Culture & New Media: The Politics of Circulation. Dave is currently working on a book called Metric Power and editing the Theory, Culture & Society open access site.

1 Comment responses

  1. Avatar
    November 06, 2017

    Sure this is true, i love this article, but what i have discovered is that data analyst are some times neglected and some companies see them as more expenses.

    Reply

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