The Challenge

The Household Budget Survey (HBS) is among the largest and most important of the data collection programmes which the Central Statistics Office in Ireland carries out.  Every five years a random sample of 10,000 households are polled about their expenditure patterns.  The aim is to determine in detail the pattern of household expenditure in order to update the Consumer Price Index.

Inpute was tasked with devising a system which would automate and streamline the processing of 100,000 pieces of highly varied, unformatted data and deliver substantial cost and resource savings.

“A solution which could deal with the unstructured nature of the till receipts seemed highly unlikely,” says John O’Reilly. “They proposed the introduction of software with advanced character recognition capabilities, designed to transform information from unstructured documents, such as receipts, into machine readable data.”

“It does however add another layer of complexity to the data processing operation,” says O’Reilly.

Information from the expenditure diaries was already being captured by Teleform, a form recognition software solution which Inpute had implemented some years earlier.  In the context of structured templates like the diaries, it worked perfectly. As the system stood however, it was not a viable option to automatically capture data from till receipts. Prior to HBS 2015 receipts data was manually keyed in by a team of data entry operators over a period of months.

Variety is the issue here. Till receipts vary hugely from store to store. Totals, discounts, dates and numbering sequences appear in different places on different parts of the receipt. Identical products are described in different ways, while many receipts also carry marketing messages unrelated to the underlying price data.  In short, no two till receipts are the same, while the paper itself is invariably of poor quality which fades quickly and creases easily.