Dirty data. It sounds insidious - and it is.
Also called rogue data, dirty data refers to inaccurate, incomplete or inconsistent data – and it can be a huge problem for organizations utilizing CRM. Dirty data can emasculate even the mightiest Dynamics CRM implementations by rendering the information virtually useless and undermining all the processes associated with the data.
While gathering some dirty data is inevitable, it is imperative that organizations ascertain the entry point of the poor data and determine how and why the information is failing.
While dirty data can generate from any number of sources, the number one culprit as you can imagine, is user error. Misspelling of names and other identifying information is a common mistake and one that puts the kibosh on your Dynamics CRM process objectives. Mis-transposing a street address by even a single digit can render an entire profile useless.
I was once speaking with a sporting goods store representative and we were trying to find my account in their CRM system. We checked using my first name, my last name, my phone number and my street address. Nothing hit. Finally, we did one last pass with my email address and there I was. Turns out, whoever initially entered my data misspelled my first name, misspelled my last name and mis-transcribed both my street address and my phone number. While I had been a “valued customer” for years, not once were they able to reach out me. The representative was shocked and embarrassed. Imagine how corporate management felt.
Now multiply my experience exponentially.
User error can be a real problem and one of the hardest to combat. The key here is accountability, oversight and training. I also recommend leveraging third-party data services that can be easily connected to your CRM to scrub your data for inaccuracies.
Incomplete data is probably the most common dirty data. Those immersed in CRM see incomplete records or missing values more often than they would like. While leaving a few fields empty might not seem like a big deal, it is actually a huge deal.
For example, without entering a city or state into a record, an organization would be unable to segment or direct that record or lead to the correct sales territory. The fact is, incomplete data can thwart your processes in innumerable ways.
One simple way to counter the effects of incomplete data is to make key fields mandatory and thus disabling the ability to close a record or continue without adding the needed information.
Duplicate records are another form of dirty data that plague virtually all CRM systems. Dynamics CRM has duplicate detection capabilities, but not everyone utilizes them.
While duplicate customer records might be considered slightly less problematic than other forms of rogue data – as the target is still being reached – redundant development and outreach can be costly due to duplicating materials and other hard costs.
The best defense in combating duplicate data is consistency and perhaps the implementation of automated data entry designed to detect and negate duplicate data.
KEEP YOUR DATA CLEAN
The most effective way to avoid dirty data is to establish processes throughout your enterprise. While this approach can take many forms, the key is to create and commit to a culture that embraces and values quality data.
- Emphasize and prioritize to your entire staff the importance of clean, high-quality data throughout your organization.
- Implement and enforce quality data policies and best practices.
- Take the time and effort to scrub your current data. Third-party services make this a relatively painless process.
- Identify dirty data entry points and address individually.
- Create processes that tag or isolate incomplete, inaccurate or duplicate records
- Automate data entry to negate the impact of human errors.
Your data is an invaluable asset to your business. Make sure you treat it as such. If you are having sustained issues with dirty data, consider engaging a Dynamics CRM expert able to consult with you on the processes, policies and training that can elevate your data to where it should be.
By Christopher Smith, Founder & CEO of