Data Edits vs Data Audits: It takes the whole team to keep your data clean!

Contributed by Stacey Ho, Marketing Analyst at WSP, USA.

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I was chatting with another marketing data gal pal this week and was lamenting how many data edits I’m doing right now for our CRM database. My role as a CRM data coordinator and marketing analyst – plus the current, rapidly changing market – is keeping me very busy with pipeline edits right now. Editing is a good sign, of course. It means your system is being used and data is getting scrubbed. I’ve always said, “data entry is not a dirty word” and I’ll stand by that motto—editing is never a bad thing. Ultimately though, the job of a coordinator or administrator of a CRM (even if this is not their full-time role) should lean more towards data auditing rather than data editing. 

Let me just stop here and add that my own firm has a terrific culture of pushing clean data in our opportunity database. This culture of system use is number one for keeping any system in place and I couldn’t ask for better support. But there is a never-ending cycle of input-update-complete for any database and that means there are often multiple, overlapping steps that need to happen regularly for every system to stay useful. It also means that all too often those of us who fall into the coordinator role begin to feel behind in one area or another. As a data coordinator and marketing analyst myself, I’m going to get on my soap box here and ask everyone out there to help stress the difference between data editing and data auditing to your entire firm.

Data Editing

Data editing consists of making specific changes to individual records. These updates are often made after talking with a client, during a marketing meeting, or when an opportunity stage or milestone is hit (such as when an RFP is released, a proposal submitted, or after reviewing a regular report). The edits are specific to a certain opportunity and are not universal audits. Possibly the biggest distinction for those of us in coordinator roles though, is that data editing can be performed by anyone with CRM access. For this reason, routine updating should be done by all users at the time the data needs to be updated. I want to encourage everyone to note that the editing is everyone’s responsibility—not just your data coordinator. Remember, a regular user generally cannot do anything to break the system (we just don’t give you that kind of power), so don’t save up your edits for your coordinator—get in there and make those edits every day! Coordinators, you’re not off the hook: train, train, train. Make sure your users can help you help them.

Data Auditing

Data audits are those regular reports, filters, workflows, or custom lists that are created to check all of your data. Data auditing can often only be performed by data coordinators or those with specific report or workflow access. They are there to make sure that new entries and updates conform to a general set of rules you set that help you to keep your data accurate. Unlike data editing, auditing should be done at regular intervals or should be done in advance of specific reports or analysis that are enhanced by having quality and clean data. For example, if I’m doing opportunity forecasting, I make sure to audit decision or start dates a few days before running my forecasting reports. If I’m looking at our pipeline volume by project type, I’ll audit the project type field for blanks or the use of “other” a few days before I regularly run that report as well. Workflow type audits are especially helpful because they often involve some form of system automation that reduces the work for everyone!

As you can see, data auditing can be helpful in scrubbing and checking many records at the same time. Of course, auditing often leads to more editing, and once I’ve audited data, I often have a pile of edits or questions for opportunity owners. So really, data auditing and data editing need to go hand-in-hand. Just remember to encourage everyone to play a role in helping to maintain data. As we know, the better the data, the better the ability to make business decisions, which is the ultimate goal of any opportunity database. 

Title photo by Lukas Blazek on Unsplash

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