Most of you will have a set of Data Quality metrics similar to the below on your OneView page. Normally hidden at the bottom and not looked at nearly enough as they aren’t part of the “standard” metrics you check on a daily basis.

Bad data

Even though these metrics may seem a bit boring, they can actually be really useful. They not only point out where consultants may have been entering bad data but also show potential gaps in knowledge. 

For example, if there are a large number of Interviews With No Contacts, do your consultants not know how to follow the Interview Process properly in your CRM? Are they selecting Interview when they should be selecting Prescreen/Internal Interview? 

There are a few easy things you can do with these metrics… 

Tip 1: Use Slice & Dice to reveal your data quality offenders

The most obvious is clicking into the data and taking this into Slice & Dice to see who is contributing to this “bad” data.  In this case, Charlie might need to be taken through how to log Interviews on the CRM again.

Data quality

Tip 2: Report and monitor your metrics with OnPoint

Additionally, you can create an OnPoint report with these Data Quality metrics to continue monitoring this going forward. 

You could set something up like this and monitor it on an ongoing basis – just make sure to use a dynamic timeframe. 

Bad data

Here we are looking at the data on group level but you can also look at this on user level. It can help managers to identify issues and training opportunities. In this case, we probably need to do a refresher on logging interviews for the whole company and not just Charlie. 

Tip 3: Name and shame your top data quality offenders

When you are doing a big push on data quality, it can also be useful to highlight this on cubeTV. Ranking the person with the highest number of ‘Interviews With No Candidate’ at the top of the leaderboard – so it will highlight your top offenders instead of your top data loggers. 

Nothing wrong with a bit of naming and shaming every now and again! As long as you work with your teams on fixing the issues of course. 

These are just a few ideas using some of our standard metrics. If you have any questions about this, please contact the Customer Success team at support@cube19.com or speak to your Customer Success Manager directly.