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Effective data quality strategies

Data quality is still a global issue but many organisations are still not taking basic steps to care for their customers’ data. Failure to invest in a data strategy will not only waste money but also isolate customers and put businesses on the wrong side of the law.

Creating a culture of contact data excellence where responsibility for data quality is given at board level is the only way businesses can ensure that employees believe in its importance. Inaccurate data can damage both brand value and bottom line profits.

Consider the cost inaccurate data has on organisations worldwide. The report Contact data: the profit maker or the neglected asset? commissioned by Experian QAS found that the overall approach to data quality and integrity in organisations around the world is what can be described as at best half-hearted, at worst, cavalier. The study revealed there have been some improvements in the last two years but there is still a lot more to do worldwide.

Less than half (46 percent) of organisations worldwide have a documented data quality strategy in place, with only North America and France citing more than 50 percent of their organisations as taking such action. In a similar picture, 49 percent do not have any targets around how accurate, up-to-date and complete their customer records are. Unbelievably, a further 34 percent of organisations do not validate any of the information they collect on their customers and prospects, whether that be name and address, contact number, email address or bank account information. Despite these unacceptably low figures, organisations are beginning to take data more seriously as only 27 percent told us they had a formal data strategy two years ago. And although you would agree that this is a step in the right direction, there are still a significant number of organisations lagging behind.

Risky business
So what is the impact of this cavalier approach to contact data management? What organisations most definitely are aware of is the damaging effect bad data has on their profits. More than 90 percent of respondents believe that inaccurate and incomplete customer or prospect data costs their business in terms of wasted resources, lost productivity or ineffective marketing and communications spend. This is a significant increase from our study in 2005, when only 73 percent of respondents recognised its impact. Digging deeper into the impact on the bottom line, respondents now estimate that the amount of budget (or funding) wasted due to inaccurate data could be as much as 19 percent, much higher than the six per cent previously cited.

Wrong side of the law
However, financial hazards are not the only risk here. Inaccurate data is also leaving many organisations dangerously vulnerable to breaches of national and international data regulation. Only 27 percent of organisations worldwide say they are 100 percent compliant with database-related regulations, down 10 percentage points from 2005. UK organisations are ahead of their global counterparts and, on average, 87 percent claim to be compliant with database regulations, perhaps due to the structured and mature regulatory environment. That said, in the UK, very little action has been taken by the Information Commissioner’s Office against firms that do not abide by the Preference Service laws. This could change with the new focus on the protection of personal data and organisations may have to brush up their act. The Netherlands holds the lowest average compliance level at 73 percent.

Whose responsibility?
To get a measure of where many companies are failing worldwide, it is important to look at where responsibility lies for ensuring high data quality standards across an organisation. Businesses as a whole appear unable to decide who should own and champion data quality, often making it the burden of middle management. Only three job functions: head of marketing, head of IT and “a dedicated database manager,” scored double figures, with the highest, head of IT, only reaching 15 percent. With these levels of inconsistency, it’s perhaps not surprising that the level of employee buy-in to the importance of data quality is low. On average, organisations say that only 52 percent of their employees believe in its importance, ranging from 54 percent in North America and Singapore to an average of 46 percent in Australia. What is perhaps more worrying is that certain regions had many organisations actually claim not to know how bought into data quality their employees are, with 32 percent of Singaporean organisations and 27 percent of UK organisations falling into this category.

How to fix it
This lack of cohesion and lethargy towards data needs to be tackled at boardroom level if previously mentioned revenue losses are to be reduced. Members of senior management need to have responsibility for pushing data quality targets, yet only half of organisations have somebody at board level championing data integrity. Meanwhile, this very data that organisations are neglecting is in many cases (23 percent) used on a daily basis for strategic analysis and decision-making. Directions that the board and management are driving the business in are influenced by data, whether that be financial reporting, customer analysis or marketing strategy. So that data, which paints a picture of the customers, needs to be right.

I believe that organisations worldwide are presented with a simple choice. They can commit themselves to improving data quality with a documented data quality strategy that is supported and enforced from the top. Alternatively, they can continue to ignore the issues and allow current problems to persist, leaving them further and further behind organisations who have proactively tried to overcome their data hurdles. Choosing to ignore contact data leads to unnecessary risks: wasting money, losing customers, breaking the law and damaging their brand reputation.

Make it a priority

Data quality needs to be a priority for organisations globally, not just because it saves needless aggravation but because wider business opportunities are more plausible when such strategies are in place.

Today’s business environment creates challenges for organisations when processing vast amounts of incoming data. Because customers can provide information at multiple entry points, such as the phone, web or point of sale terminals, the number of duplicate records in businesses’ databases has increased. Combined with the constantly changing nature of data, many companies struggle to accurately and quickly match information from each channel.

Data quality can seem like a daunting task, but it’s really all about having the right people, processes and technology in place. These simple steps will help you focus your efforts and build an action plan of how to approach this massive challenge.


How to improve data quality

Build a business case
Measure the current impact of data quality within your organisation. What type of data do you collect? What is it used for? Look at the financial implications. If data quality improved by just one percent, what impact would that have on your customer acquisition and retention, marketing campaigns and customer satisfaction?

Devise a data quality strategy
Look at the type of data that you want to collect and measure going forward. For example, if you operate in the B2B space, wouldn’t it make sense to append employee numbers/turnover to your data so you know the scale of the organisation you are working with? Tie in your objectives with the strategic objectives of your organisation so you’re all working to the same end gain. Set SMART targets around how complete, accurate and up-to-date your contact information is so that you can use them to monitor your effectiveness.

Secure buy-in
Many data quality projects fail because they don’t have support from all the necessary stakeholders. Typical stakeholders include the Board, senior management and IT. Education is vital to get everyone on board and explain what’s in it for them. You should discuss the options available to improve existing processes and manage control. Having a well communicated, formal data strategy will also help ingrain data quality into your organisational culture.

Make the technology work for you

Effective finance, CRM, HR and business intelligence systems rely on good data. If you put poor data in, you can expect poor data out which can have a serious impact on decision-making. Using software tools to control the data entering these systems, and manage data quality within, ensures that you get the most from your technology.

Don’t do it alone
Technology alone is not sufficient. Merging data from multiple sources, for example, can be a risky process. Pitfalls can appear along the way if the project is not managed correctly, so try not to tackle it alone. There are many organisations that can provide professional expertise to ensure that the project runs smoothly.

-Paul Vescovi is managing director Australia and New Zealand of Experian (www.experian.com.au).

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Paul Vescovi

Paul Vescovi

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