By Benoit Leclerc and Jesse Cale

This brief is based on the second instalment to Criminology at the Edge book series, published by Routledge: Leclerc, B. and Cale, J. (Eds.) (2020). Big data. Routledge.

1. What problem does your research address? Why is this significant?

Whether in government agencies, corporate and non-corporate organisations, large firms, academia, politics and so on, the Internet has launched the world into an era into which enormous amount of data are generated every day through technologies with both positive and negative consequences. This often refers to Big Data. But what is Big Data, how is it relevant in general, and, more specifically, for criminology and criminal justice? Speculations on the implications of Big Data for the field have begun, but there is no solid consensus in the criminological literature about what exactly Big Data refers to, and how it will impact theory, research, and most importantly, practice. Big Data typically implies an abundance of data and new processes, such as data mining and data analytics, which provides virtually anyone using data with the opportunity to generate new discoveries or upscale an organisation’s capabilities. Most importantly, Big Data brings challenges to organisations and innovative embedded systematic solutions are much needed to overcome these challenges so that organisations can thrive and prosper in a safe environment. In this volume, we are using a business lens to identify challenges related to Big Data in criminology and criminal justice and providing roadmaps to help address these challenges.

2. How did you conduct the research?

Even if this volume sits in the discipline of criminology and criminal justice, we looked at what is known on Big Data, its challenges and potential solutions through the lens of the business literature. Mostly sourced from Harvard Business Review and McKinsey Quarterly, the literature led us to a much deeper understanding of the challenges associated with Big Data, but also provided important insights to make Big Data work for organisations across any industry. We realised that the business literature is arguably much more robust when it comes to understanding the potential challenges and benefits posed by Big Data compared to the social sciences, and more specifically, criminology and criminal justice – despite the high quality of data analytics utilised in much of criminology. Second, in a very inductive manner, we invited contributors to participate in this volume with the hope that important themes around Big Data would emerge organically across the volume and assist us to some extent in making sense of which steps organisations could take next for improving their practices. Third, it became obvious through reading the contributions of this volume that key challenges related to culture and data analytics processes are critical not only in the world outside of criminology and criminal justice but also in this field quite specifically, which we aimed to address by developing practical roadmaps.

3. What are the major findings?

The chapters included in this volume all looked at Big Data challenges in the field of criminology and criminal justice. The contributions of this volume cover a range of topics relevant to Big Data, which include Big Data challenges in criminology and criminal justice, epidemiology and criminal justice, environmental criminology, artificial intelligence, intelligence-led policing, cybercrime, and genetics and bioethics. Two challenges cut across these contributions, culture and analytics. First, in any organisation, culture is a dimension that has been examined in depth because of the benefits associated with ‘getting it right’ and the costs of ‘getting it wrong’. Any organisation should typically be seeking to align its mission with its people and culture and vice versa. Therefore, if the culture of one organisation is not receptive to Big Data, making the best of data for that organisation will be twice as challenging. Second, suffice it to say that having access to an enormous amount of data is meaningless for an organisation unless these data are of a certain quality, can be utilised effectively, and that the ‘entry point’ (i.e., formulating questions to address) and ‘exit point’ (i.e., interpretation and dissemination of findings) of the process of data analytics are completed with diligence.

Drawing from these contributions, the volume concludes by highlighting some of the key themes to emerge across these chapters, followed by a proposed framework moving forward to facilitate engagement with Big Data and data analytics in the fields of criminology and criminal justice. The purpose of this is to facilitate engagement with Big Data and data analytics in proactive ways, with an eye to understanding barriers and limitations, how to overcome them, while at the same time ensuring the integrity and ethics of the knowledge generated through these means. 

4. What does the research mean for policy and practice?

Big Data entails a major disruption in the ways we think about and do things, which certainly applies to most organisations including those operating in the criminology and criminal justice fields. It is fascinating to observe that despite the unique topics and contributions to the volume, the most prominent theme that emerged across several of the chapters was that of culture. As pointed out before, the absence of an organisational culture, whether in academic criminology or criminal justice, that is receptive to engaging with Big Data, or simply, data period, the utility of introducing and engaging with Big Data and data analytics may prove to be irrelevant, or perhaps at worst, a costly and counterproductive exercise for organisations.

Big Data is currently disrupting processes in most organisations – how different organisations collaborate with one another, how organisations develop products or services, how organisations can quickly scale up their business, how organisations can identify, recruit and evaluate talent, how organisations can compete with one another, how organisations can make better decisions based on empirical evidence rather than intuition, and how organisations can quickly implement any transformation plan, to name a few. All these processes are important to tap into, but two underlying processes are critical to establish a foundation that will permit organisations to flourish and thrive in the era of Big Data – creating a culture more receptive to Big Data and implementing a systematic data analytics-driven process within the organisation.  

Creating roadmaps on culture and the data analytics process emerged as critical after reading and making sense of the business literature on Big Data and compiling the work of the contributors of the current volume. There is one clear objective underlying these roadmaps: change management – guiding, and working with, organisations (criminal justice-related or not) to facilitate transitions into and management of Big Data. These roadmaps are applicable in practice, which could benefit any relevant and interested organisations. While Big Data may involve challenges which we are not currently aware of, creating a culture more receptive to Big Data is no doubt a priority and a critical starting point for any organisation. This volume also represents an invitation to all to engage with Big Data and analytics for generating positive outcomes.