Don’t the industry surveys show what causes of shrink or shrinkage are?

The retail sector is not short of surveys trying to ascertain the scale and nature of the shrinkage problem it faces. In the US there is the longstanding National Retail Security Survey, while more globally there has been various sweeps of the Global Retail Theft Barometer, covering a varying number of countries. In addition, many surveys have been undertaken over the years covering particular retail sectors and a range of different countries. Virtually all of these surveys rely upon respondents providing a ‘shrinkage’ figure with varying degrees of explanation about what should be included and excluded from this number. For instance, in the past the National Retail Security Survey (NRSS) asked for: ‘your firms fiscal inventory shrinkage (excluding damages and spoilage)’, while the 2008 version of the Global Retail Theft Barometer asked for the ‘Corporation’s shrinkage or stockloss for 2007-2008 financial year (or most recent year) as a percentage of turnover)’. It then goes on to ask a further question about whether wastage/or spoilage was included in this figure and if it was to provide this, presumably as a percentage of turnover (although it is not clear). Both surveys then request that the respondent provide a best guess or estimate of the likely causes of this unknown loss using the typical four buckets of shrinkage outlined above, although for the NRSS, the category of ‘Administrative and paperwork error’ obviously now excludes damages and spoilage, and there is also an option for respondents to choose ‘unknown loss’ as an explanation of their unknown loss!

As detailed above, given that most definitions of shrinkage are based upon data derived from variance in expected and actual stock holding, the data is almost always a measure of unknown loss. From these estimates the surveys then calculate the apparent causes of loss, with some carefully tracking and micro analyzing annual changes and differences between countries and retails sectors based upon this data. Some authors have been highly critical of this approach. One said: Attributing known losses to these [loss] classifications is fairly straightforward. The problem arises with the inclination of business and academia to apportion a value for total shrinkage, i.e. known and unknown shrinkage, to these categories. Instead of an honest answer along the lines of: Retailing is a complex business, there are many mechanisms through which shrinkage can occur and we don’t know which ones apply in this instance, there is a tendency to use judgement/estimation/guess work to apportion unknown shrinkage to each category. Despite the fundamental weakness, this erratic approach is the default mechanism all too often used to inform management thinking and direct investments in loss prevention solutions when faced by a lack of hard data.

Others have highlighted similar problems: [the data] can only been seen as a measurement of how respondents currently feel about each of the factors they are requested to make estimations about – they are socially constructed and more than likely a distorted picture of the problem based upon personal prejudice.

Without doubt, some of these surveys have played an important role in helping the loss prevention industry understand how it is thinking about the problem of loss. Other parts of these surveys, which for instance, focus upon the extent of the use of various approaches to managing loss, have been important in providing benchmark data. But the rapidly changing retail landscape, together with the way in which retailing is not only experiencing a broader range of losses, but is also growing its capacity to collect and analyze data on them, would suggest that a new approach to benchmarking retail losses may well now be required.

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