I’d taken a break from the “You’re Live, Now What?!” series in favour of another initiative. This was one post that I’ve sat on for WAY too long. Finally getting around to posting it to the series. Enjoy!
Data is the heartbeat of many organizations today. Long gone are the days where we need to base decisions on what we “think” is happening. Instead we can, and should, lean on data to inform us on what’s really happening.
Over the past couple of years the first thing I do when I think about purchasing anything is read reviews of the product. The more reviews, the more confidence I have in the general sentiment of the reviewers. That is to say – the more information I have, the better informed I feelt.
This extends into our internal systems at work. Data is a critical aspect in our endeavor to understand how we’re doing as a company. As such, we must take steps to ensure that data has strong governance around it’s integrity. Why? Because if data is erroneous we run the risk of erroneous decisions.
Let’s be real – we are “busier” than ever. We manage multiple projects, sit in various meetings about different projects/initiatives, and have many conversations in a day. As a result, our attention to detail is compromised. It may be that we’re documenting something hours or even days after it took place, or we’re inputting data while thinking about the next three things we need to be focused on. The result? Errors.
They are inevitable. We can, and should, strive to prevent them from happening but we must accept that they will come up. With this in mind, it is essential that we have a plan to deal with data integrity challenges that may arise.
There are some tactics that can be implemented to help foster a culture of ‘clean data’.
Limit Hands in the Pot
Does everyone in the company need access to every part of the data management system? Perhaps we can identify methods to streamline process by having data flow through a data steward or be reviewed before it’s entered. Limiting the number of people that have edit permissions can decrease the potential for error. It reduces the number of people that need insight into the ‘how’ the data is entered/managed. That said, it’s important to note the value of having documentation to outline the data entry/management processes.
Data Clean-Up Efforts
Everyone is responsible for the data, so everyone should be responsible for auditing the system for data integrity. This can be done in various ways – perhaps a scheduled day each month where teammates perform random audits on records that were entered to look for completeness and/or errors. But don’t make this a ‘find the problems’ adventure – perhaps create a process whereby teammates are rewarded for excellence in data management practices.
Dashboards / Reports
Use tools like this to look for common data integrity issues. For example, set-up dashboards or reports that show records that are missing key data entries. The name of the game is to develop things that shouldn’t have any results – for example, Accounts with no Address or Country data. If results show up on the list, they need attention. If all records have been entered cleanly, the result of this dashboard/report will be zero, so, no effort needed. Of course you should look to ensure critical data is set to required where possible to avoid mistakes in the first place, but this isn’t always possible.
Training
Training is not a one-and-done exercise. It needs on-going attention. You can use tools like the dashboard/report exercise to hone in on areas that need extra attention (example: notice that you find records from user X always missing the same important information? Schedule a time to discuss with them – use it as a training opportunity but also dig into why they might be missing it as perhaps there is a system change that can be made to make things more efficient).
It’s a Team Effort
Not to be overlooked is the simple act of talking about the importance of data integrity. Bring it up in your weekly/monthly calls with the team. Talk about why paying close attention to data is important and how it pays dividends to the company as a whole. When users understand the ‘why’ behind it, they are going to be more diligent in their attention to detail when entering and managing data.
These are just a few tips. There are others ideas out there. Have some of your own? I’d love to hear them! Drop them in the comments section or engage in the social post promoting this entry.
We’re all learning! Why not learn together?
Cover Photo: Photo by Franki Chamaki on Unsplash
The Nerdy Admin 