Today’s business environment creates challenges for most 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. I intend to outline the key factors affecting a business’ poor data management and the steps organisations can take to create a culture of data integrity to ensure businesses better manage their data. I’ll also explain how data quality can contribute to overall business strategy in terms of performance.
Factors affecting poor data management
Based on my experience in this arena I believe there are five key factors that lead to poor contact data quality management. The first is that even where contact management technology is in place, it is not necessarily deployed across all an organisation’s customer and prospect touchpoints.
The second problem with contact management technology comes when staff are not using it effectively. If they haven’t been sufficiently trained to use the software or new staff are not trained, then chances are they won’t easily come to grips with it or may even stop using it all together.
The third factor is the pressure on people’s time to keep the data fuelling the system up–to–date. A contact management solution may work perfectly well on day one, but its performance can gradually decline if the data updates are neglected.
We need to remind ourselves of the statistics. How many people die each year? How many people move each year? How many people change their name each year?
The fourth factor affecting poor contact data quality management is the human factor. The process of capturing people’s addresses, particularly over the phone, is prone to human error. Most mistakes are being made at data entry point.
Finally, no matter how good the solution for verifying new customer and prospect data, there is still likely to be legacy data within the system that has not been verified to the same extent. Whatever solution you have to cope with new data that you capture, you also need something to bring the older data up-to-date.
A culture of data management
Good contact management needs the right approach. Technology on its own will not suffice. The solution must be built into an organisation’s business processes. Companies these days have so many different touchpoints with consumers that their business processes must be able to account for the different ways customer and prospect data is captured. And of course, it’s people who make business processes work, so it falls to the organisation to provide the necessary training, encouragement and incentives to ensure that everyone in the organisation understands the importance of data quality.
In order to establish a culture of data integrity, it is my belief that it must enjoy board level sponsorship and be owned by the users not the keepers. Otherwise, the commitment and the funds needed to improve data quality just don’t materialise.
The final point to consider is that there is more to contact data management and data quality than the accuracy of the address itself. While businesses have largely embraced address management in its purest form, the market has evolved. Today, data quality embraces not just contact data management, but data cleansing, suppression, enrichment and de-duplication.
In summary, address and data quality is all about people, processes and technology. It is about creating a culture in which data quality is taken seriously by everyone in the organisation, where there is buy-in from the CEO to the most junior member of staff. The results of an accurate database are invaluable to all areas of a business.