But findings from “The data revolution – liberating lost budget” report identify that companies which do invest in improving data accuracy believe they generate an average of close to £1m in additional profit.
According to the research, nearly 90% of companies admitted to wasting departmental budget – through duplicated mailings, lost contacts and missed sales opportunities – because of inaccurate data.
Departments such as marketing, sales, operations and customer services report wasting 15% of their budget on average – and in IT and data management this rises to 18%.
The price paid by companies for poor data quality is particularly high in customer-oriented areas of operation.
More than 80% of the companies surveyed operate customer loyalty programmes. Two thirds of these report that inaccurate data has had a negative impact on these programmes through, for example, lost custom.
Companies that do invest in high quality data, however, can earn rich rewards, Experian claims. Of the companies surveyed, 55% cited revenue generation as a driver for better data quality and other findings support the wisdom of this view.
Three quarters of UK companies have invested in upgrading data management systems in the past two years.
On average across the whole survey, large companies invested more than £500,000, medium sized companies £248,441 and smaller companies £141,795. Average investment for all companies was £285,349. Nine out of 10 companies that have invested have seen an associated increase in profits, with the average global figure coming in at £943,106 – representing a 300% return on average investment.
Experian QAS managing director Joel Curry said: “There is a growing body of evidence showing that accurate data is the key to competitive advantage. Companies that are able to rely on their data can use it to better understand their customers and target campaigns. It’s a fact that UK businesses are increasingly aware of, but as today’s research shows, this awareness needs to be translated into action and investment.”
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