Big data is now high on the agenda for corporations, governments, researchers and others. However, a team in the USA suggests in the International Journal of Auditing Technology that we now need to look at “thick data” to enhance big data and improve the validity of the information that can be extracted from it.
Michael Alles and Miklos Vasarhelyi of Rutgers Business School in Newark, New Jersey, explain that big data is one of the most important developments in business and as such auditors themselves are being pushed to use it in their own work. However, the team suggests that they need to see big data as a means towards an end and not as an end in itself. They describe thick data as a new ethnographic approach that “uncovers the meaning behind big data visualization and analysis”. In other words, when applied to big data, thick data provides the context needed to more completely interpret the big data itself.
There is enormous growth in big data, with Forbes predicting it to have more than $16 billion in revenues for 2014 and expanding six times faster than the overall information technology market. As such corporate auditors must match pace with these developments and Alles and Vasarhelyi suggest that their thick data approach might be readily and transparently incorporated into current auditing practice. They must, however, be cautious of the fact that big data may well have reached “peak hype”, the peak of inflated expectations that usually accompanies any technological development. They must address the big data issue without being overwhelmed by hyperbole and grandiose claims for what big data can do beyond its actual capabilities.
The team points out that, “Auditors, whether internal or external, are certainly closer in their business objectives and practices to ‘traditional US businesses’ who are their typical clients than to companies ‘born into a big data world’.” Seeing big data as a means to an end means that auditors will be able to more accurately assess management practices and financial statements.
Alles, M. and Vasarhelyi, M.A. (2014) ‘Thick data: adding context to big data to enhance auditability’, Int. J. Auditing Technology, Vol. 2, No. 2, pp.95–108.