This is a guest blogpost by Jim Conning, Managing Director of Royal Mail Data Services (RMDS).
The forthcoming 25 May implementation date for the General Data Protection Regulation (GDPR) is focusing businesses on the whole topic of customer data. How can they ensure that they are compliant and avoid potential fines of up to 4% of global turnover? Research into customer data management from my organisation, Royal Mail Data Services highlights the pressure that companies are under – and how collaboration between IT and marketing is necessary for effective customer data management strategies.
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GDPR – varying confidence levels
In a recent survey carried out by Royal Mail Data Services among key decision makers, we found that compliance with the GDPR was the number-one concern for survey respondents, with 29% citing it as their biggest worry.
Focusing on specific areas, the study asked how confident respondents were that their internally held and third-party customer data was GDPR compliant. The positive news is that 78% were either “very” or “reasonably” confident that their internally held customer data complied – although 11% were not confident, including 2% who even more worryingly didn’t know if they were compliant or not.
However, when it comes to third-party data, confidence levels drop dramatically. Just 43% of respondents were “very” or “reasonably” confident when it came to compliance, which demonstrates the difficulty of gathering evidence that the right permissions are in place when data has come from other sources. Only 9% of brands said they were very confident in their data compliance, which shows that there is plenty of work to do ahead of 25 May 2018.
Collaboration is the key
When it comes to data strategy, companies are adopting a range of approaches. Just over half (51%) of marketing teams set data strategies, while other groups such as central data management (26%) and the board (25%) were also involved. Legal and compliance teams were naturally heavily involved in privacy and permissions decisions, taking lead responsibility within 38% of organisations. Forty-four per cent of marketing departments led in this area, compared to 20% of IT/IS teams.
Responsibility for actually managing customer data is also split between different departments. IT/IS was in charge in 30% of cases, behind marketing (37%) and central data management teams (also 37%).
This demonstrates the need for departments to work closely together – each has different skills and approaches that together provide the complete solution for a business and help it to achieve its overall objectives.
Data quality is still an issue
Poor-quality data hits the bottom line, and survey respondents recognise this – they estimated the average cost to the business of poor-quality customer data to be around 6% of annual revenue. For major brands this is measured in millions of pounds – and this excludes any potential GDPR fines.
So what leads to poor-quality data? Respondents saw basic errors as the main culprits, specifically out-of-date information and incomplete data. Increasing automation around validation helps overcome this – but a significant minority (19%) of survey respondents said they didn’t validate website data, and 16% didn’t check data coming into internal systems at all. A similar gap is visible when it comes to data cleansing. While 22% of companies undertake this daily or continuously, one-third (33%) still have no formal processes in place to clean customer contact data. Overall, many businesses are putting themselves at risk of data-quality issues – and potential GDPR investigations over non-compliance.
The Royal Mail Data Services research demonstrates that GDPR is acting as a wake-up call to organisations, providing an opportunity to focus on how they collect, manage and store customer data. Successfully achieving compliance and getting the best out of customer data therefore requires IT and other departments to work together, now and in the future.
You can download a full copy of the research report, “The use and management of customer data”, here.