Improve Data Quality Management Today

Forbes Magazine has a really important maxim about data quality management (DQM). They state that it takes only $1 to verify a new CRM record that someone has input in your database, $10 to clean it up after the fact and $100 in lost revenue of you just leave it uncleaned on your system. Also, they stated that the average sales representative of a company loses about 27 percent of their sales time every year due to poor CRM data for sales prospects. The integrity of data is a very important topic to your bottom line. This article will address some steps you can take this week in order to get the ball rolling on improving the integrity of your data.

What is Data Quality

According to, there are two key factors to consider in data quality:

  • Does the data represent what is happening in the real world?
  • Can the data be used in order to perform whatever task you have envisioned for it?

As to the latter question, for example, if you are maintaining a database in order to determine trends in customer buying habits, can you get that accurate analytical information from the data? Or, can your data help you determine a better way to organize your website in order to help customers get what they come for every time without headaches or hiccups?

How Can I Improve Data Quality Management Today? –

One thing to realize is that DQM is a process that will be ongoing. But, there are things you can begin this very week that will get the ball rolling to improve your data and the analytics that you can harvest from that data.

Steps to Improve DQM Today:

Make the buck stop somewhere: According to Information Week, there needs to be an employee that has skills in business, IT and database management that needs to be the person in charge and responsible for the quality of data you are harvesting for your business. Also, you need to assemble a group of employees from each department that will become evangelists of data and will provide input on how data is used in each of their departments. This is essential to begin a process by which data is available in a useful form for every department in their analytics and other business uses.

Think of ways to triangulate the data: Information Week also explained that any good data-gathering initiative needs to ensure that the data gathered is accurate. One highly effective means of ensuring accurate data is to gather it from a few different sources in order to ensure its cleanliness and accuracy.

Forbes suggests that business owners not ask customers online to provide sensitive information too soon in the sales process because customers are likely to lie in order to maintain their privacy if they are not yet convinced they will be buying from you.

Decide what data is really needed: Forbes suggests that once the data team is in place, have them work together to determine what data that is being gathered is needed by each department and what data is unnecessary. Eliminate gathering that data as soon as possible and remove it from your database.

Automate database cleaning: Forbes suggests software that cleanses your database because such database cleansing can be performed regularly, is more cost effective that enlisting employees and is less prone to error.

Update the data in real time: Forbes suggests that you update your data when you interact with your customers. They stated that 70 percent of business-to-business data changes yearly. Lost contacts are lost repeat business. Also, mailers sent to wrong addresses are expensive and can be frustrating for customers.

There is quite a bit more to improving the quality of data that your business is gathering and maintaining an organizational focus on the importance of this issue. The guidelines above are just a few that you can begin working on this week. With a data team that has representation from all of your departments, a renewed focus on the accuracy and cleanliness of the data and an audit of what data is necessary and what is wasting customer and employee time, you can begin the process of removing dirty data that may be hampering your company’s profitability.