Poll results no surprise
A recent LinkedIn poll showed data quality is by far the biggest issue getting in the way of quality outputs. Although our poll sample is small, we know this to be true from our own experience working with clients over the years.
Grant Buckley, our Sales & Marketing Director says,
‘It’s the foundational stuff that needs fixing. When your database is optimised, it can assist in preventing poor quality data collection.’
You get out what you put in!
It’s always been the number one issue for organisations, regardless of their size. They struggle with accuracy, completeness and recency of data.
If the foundational stuff isn’t right organisations produce data of dubious quality. The result is evident in the outputs – poor quality data models, visualisations and inaccurate reporting.
So what can be done?
There are some tools to help with data accuracy issues, like Quick Address Search (QAS) for address accuracy and feel free to hit us up for information on others depending on your needs. However, the best way to ensure data accuracy is through a disciplined internal input process and using manual processes to fix and clean your data at the source.
For larger enterprises, these processes can be wrapped up with data governance. Talk with us about Collibra if your organisation needs help with data management tools at scale.
Can the work be outsourced?
For most SMEs data cleansing is best managed internally. This is because it requires subject matter experts. The closer you are to the data the more accuracy you will have.
We have seen a few projects outsourced successfully, but the reality is that your people know your data best.