 Shrinkage Figures and Data Corruption: Lies, Damned Lies and Statistics?Vicky Turbin ()
Chapter Chapter 2 in Crime at Work, 1998, pp 25-33 from Palgrave Macmillan Abstract: Abstract Effective security requires accurate data about losses. In retailing, estimates of loss known as ‘shrinkage’ are commonly used to indicate problems within a store. However, shrinkage not only includes theft by staff and customers but also some degree of unidentified ‘clerical’ error. Understanding how data is created and corrupted, is a vital part of understanding estimates of risk. By reducing data corruption, more reliable loss figures are produced on which to base security decisions. This is a vital component of any security strategy designed to increase the risk for offenders. This paper presents results from a twelve-month study of data corruption within a medium-sized jeans and casual clothing retailer. Using both hypothetical examples and case studies of real stock figures, the paper demonstrates how data is corrupted and how corruption impacts on stocktakes, loss figures, merchandising and sales. Keywords: Data Error; Loss Figure; Shrinkage Figure; Computer Record; Stock Data (search for similar items in EconPapers) There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:pal:palchp:978-0-230-37783-7_2 Ordering information: This item can be ordered from Access Statistics for this chapter More chapters in Palgrave Macmillan Books from Palgrave Macmillan |
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