Singapore Firms at Risk of Losing Millions of Dollars From Unreliable Data

A new survey highlights the importance businesses in Singapore attach to the accuracy of their contact data. The survey, conducted by Experian, also emphasizes the challenges companies face in ensuring data quality and the impact data inaccuracies can have on their bottom line.


Experian’s survey revealed that despite 88% of businesses implementing a documented data quality strategy, 94% do not trust the accuracy of their contact data.


Reasons cited by respondents for the lack of trust include human error (75%), lack of relevant technology and/or inadequacies in current technology (54%) and inadequate data quality strategy (34%).


“While it is encouraging to see that companies recognize the importance of high data quality and have strategies in place to ensure data accuracy, the lack of trust highlights that these are often not followed through,” says Graeme Beardsell, Chief Customer Development and Marketing Officer, Experian Asia Pacific.


“As business data continues to decay by approximately 37% each year, it is imperative that organisations re-evaluate strategies to stay on top of the data quality issue. It’s equally critical to have a way of measuring the accuracy of their data over time, in order to be successful and maximize every dollar spent on customer engagement.”


Organisations also believe that about 24% of their data were inaccurate, directly impacting on their bottom lines. The data showed that an average of 14% of departmental budgets is wasted due to contact data inaccuracies.


Companies also reported that they had lost potential customers due to inaccurate data input (39%) and lack of complete data (28%).


Other issues cited included sending emails to the wrong address (41%), duplicate mailings (37%) and misspelled names and address details (40%) negatively impacting the customers’ perception of an organisation’s brand.


From an industry perspective, respondents in the financial services industry were more likely to experience challenges linked to data inaccuracies, compared with businesses in other industries including manufacturing and automotive, retail and distribution, utilities and telecoms and other public sector and non-profit organisations.









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