The cost of bad data
What is the true cost of a bad data? Some scenarios impact revenue or savings, while other scenarios impede operational efficiencies, customer satisfaction and people’s lives. The real cost of bad data was illustrated in October 2020 with failure by the UK Governments Track and Trace system.
Revelations in October 2020 that the badly thought-out use of Microsoft’s Excel software was the reason nearly 16,000 coronavirus cases went unreported. This mistake had substantial human cost never mind the financial cost of the 2nd lockdown.
Erroneous decisions made from bad data are not only inconvenient but also extremely costly. According to Gartner research, “the average financial impact of poor data quality on organizations is $9.7 million per year.” IBM also recently discovered that in the US alone, businesses lose $3.1 trillion annually due to poor data quality.
In 2013 two Harvard economists admitted a faulty spreadsheet calculation caused errors in a study used by numerous politicians to support their austerity policies. Simply by releasing his index finger from the left clicky button of his mouse to soon!
The impact of bad data
The more complex the data needs of an organisation, the more difficult it becomes to keep all data sets clean. There is also a greater threat to the organisation and the cost of bad data can be substantial.
Bad data in action:
- Wrongly using contact data for deceased contacts or gone away contacts. This can damage your brand and waste resources.
- Holding on to personal data longer than is necessary for the purpose it was processed. This can result in an organisation falling foul of GDPR legislation.
- Collecting multiple duplicate data sets. This can skew decision-making, corrupting the customer insight even wasting resources.
According to Dun & Bradstreet, 42% of companies said they struggled with inaccurate data. In the same report 43% had seen ‘some’ data-led projects fail. These findings seem to suggest that companies with bad data are more likely to experience project failure.
What a Difference Clean Data Can Make!
The cost of bad data impacts not only financially. Often times leadership and management teams do not just want savings – they want direct correlation in terms of revenue as well.
The business benefits of clean data
Clean data is vital for businesses of all sizes. Any organisation with complex data requirements stands to gain the most from clean data. This benefit can be realised through the combination of more effective marketing campaigns, more efficient spend, lowered compliance risks and associated brand damage. Some other examples include.
Marketing: A direct marketing campaign using high quality data reaches the right target contact with relevant offers. This drives up sales leads and campaign return on investment.
Sales: A sales representative can reliably contact current customers. With access to complete and accurate data, they can ensure no-one is forgotten or missed.
Compliance: Avoidance of penalties and the related brand damage. Complying with the GDPR and other global data protection regulations require companies to maintain clean data.
Better insights and decisions: Accurate data will deliver more accurate insights and enable better decision making.
Protect your brand: Applying data quality best practice will help to protect your organisation from brand and reputational damage. For example, it will stop you from contacting deceased individuals.
ProAptivity are an independent CRM solution provider. We focus on the implementation, training, and support of highly customised CRM software solutions. Our CRM software provides the customers with the tools needed to manage their data. We help organisations embed sales best practice throughout their organisation.
Contact us today on 028 9099 6388 or via email@example.com. We can help you assess if your business is CRM ready.