Establishing an authoritative data management programme is essential these days but it requires a lot of work to get into such a position. With a lot of elbow grease and scrutiny – self-assessment is key here – organisations can foster a new era of innovation with data quality at the centre of it all.
As such, carrying out a thorough audit of your asset, one that properly assesses the processes you currently have in place, is essential for establishing a new framework of understanding that leads to greater things.
It's ultimately all about quality. Customer data that has been verified, cleaned and enhanced is going to ensure that your business is well-optimised to achieve at a high level, the kind that is demanded these days.
Data quality can be affected in multiple ways, therefore, in knowing what these are, you can develop strategies that are designed to reduce them from coming to fruition. It can also help you come up with responses that help limit brand damage and preserve reputational integrity.
Your asset is most likely to be compromised because you're not fully engaging in data. While much can be automated, it still requires supervision and engagement from experts – individual or team.
This is why, for example, an inefficient and ineffective data management programme can spiral out of control (either slowly or quickly). Erroneous data can therefore be captured in a system – manually or automatically – without anyone realising internally and likewise, customers can enter flawed information externally.
A lack of awareness then causes problems right from the moment data enters into an organisation, which, added to already captured information degrading – information is susceptible to change – can result in a completely skewered and unreliable picture.
Prioritising data, lavishing attention on it and identifying where you are currently going wrong will help organisations overcome major barriers and ensure that you get to a position where quality is the status quo and not something that you are constantly chasing.