The importance of supplier data integrity is not a new thing. Organisations have always had access to this data in one form or another, whether on paper records or information stored in spreadsheets or desktop-based software (much of which can now be referred to as legacy software).
Even though the premise of data integrity is not new, it’s not an exaggeration to say it’s more important now than it’s ever been. And, given that the amount of data that businesses have access to, it is only going to continue growing, as will the importance of data integrity.
What is data integrity?
To boil supplier data integrity down to its simplest form, it’s about ensuring that you maintain the accuracy of the information. And as anyone who has worked with data will know, this sounds much easier than it actually is.
Essentially, to maintain data integrity, you need to make sure that the information is as accurate as possible when it is first created. That much is obvious.
Beyond that however, you also need to focus on maintaining its accuracy down the line, meaning that whenever the data is ‘read’ or used, it maintains the same integrity it had when it was created. In other words, you need to make sure that the information hasn’t been wrongly altered in the process of being used (yet, at the same time, that it can be updated easily and efficiently).
If you’re thinking that this sounds very familiar to data quality or data governance, then you’d be right. There’s a lot of crossover between these disciplines, because clearly they all focus on maintaining the quality of your data from the point of its creation, and also maintaining the robustness of your data gathering and management processes.
What are the differences between data integrity and data quality?
Even though there are of course similarities between data quality and data integrity, they are not identical.
Data quality refers more to the initial phase in which supplier data is created, and making sure that when it is created it isn’t hampered by incompleteness (missing values), inaccuracy (incorrect values), inconsistency (presenting the values in different ways), non-standardised values (formats that can’t be processed by the system), and so on.
Data integrity relates more to the overall management of supplier data (after it has been created) across its ongoing lifecycle, to ensure that it does not get compromised during future use.
How can data integrity be compromised?
Broadly speaking, the ways in which data integrity can be threatened fall under the following three categories:
‘Commission’ – when you create or record data that didn’t actually exist in the first place (e.g. a supplier that doesn’t exist, or one that isn’t working with you and therefore shouldn’t be in the system, etc)
‘Omission’ – when you delete data, and all transactions associated with that data (e.g. contracts, communications, etc), meaning it essentially never existed in the system
‘Manipulation’ – when data gets changed from its original form, and the changes are hard to detect unless you have prior knowledge of that information
While all of these categories are clearly problematic, manipulation is arguably the most damaging of the three. This is because, unlike Commission and Omission, which are fairly easy to detect (for instance, there’s data present that isn’t related to anything, or a gap where data should be but isn’t present), data manipulation is harder to identify because the changes are often subtle and made over a longer period of time.
Think of it like a game of Chinese whispers. The message or phrase that you start out with slowly gets altered as it goes from person to person. The same thing can happen to your supplier data as it moves between systems and from user to user without proper governance or scrutiny, so data manipulation – whether intentional or not – is always something you need to very aware of and proactively trying to prevent from happening.
How to maintain the integrity of your supplier data
Supplier data integrity is closely related to supplier data governance, and having good governance policies and measures in place will certainly support your data integrity management efforts.
Some of the steps you can take might sound basic, but it’s always important to get the fundamentals right if you want to build a data integrity strategy that stands the test of time. Some examples of practices you’ll need to put in place include:
- Making sure that data needs to go through a validation and approval process when it’s initially created
- Tracking changes that are made to the data records, including whenever new information is added, modified or deleted
- Regularly backing up data (automatically)
- Carrying out regular internal data audits
- Restricting access to the data, or putting in place tiers of authorisation, so that sensitive information can’t be accessed by those who don’t need access to it
However, while organisations are increasingly realising the benefits that come from no longer positioning those in IT as the ‘gatekeepers’ of information and creating a culture of self-service business intelligence, this doesn’t mean that there shouldn’t be any controls in place whatsoever. Giving everyone in procurement access to all of the data is not only unnecessary, but it’s also risky.
This again ties in data governance, and the need to establish clear roles and responsibilities for who can and can’t access certain data, and furthermore, who can and can’t edit it.
You can read much more about data governance in the following resources:
- Supplier Master Data Governance Part One
- Supplier Master Data Governance Part Two
- Data Governance: The Benefits For Organisations
- Why You Need A Data Governance Framework
The growing importance of data integrity
“By 2022, 90% of corporate strategies will explicitly mention information as a critical enterprise asset and analytics as an essential competency.”
Whether or not you’ve seen the above quote from Gartner before, it’s worth paying close attention to those numbers. In just a couple of years’ time, nine out of ten organisations will define data as a critical enterprise asset, not just a ‘nice to have’.
That means it won’t just be your organisation viewing supplier data in that way – your competitors will be too. If you’re not focusing on using data as a competitive advantage, then other organisations in your industry definitely will be.
Maintaining the integrity of your supplier information is a crucial part of building confidence in your data. If there are question marks about how accurate or trustworthy your information is, then there will be doubts about any analytics, reports or decisions that are made off the back of such data.
Findings already suggest that confidence in corporate data and analytics is low, with just 35% of senior executives saying they have “a high level of trust in the way their organization uses data and analytics”.
As such, every aspect of supplier information management – be it data integrity, data quality, data governance or data security – is something you need to have control over. If you don’t make the most of this critical enterprise asset, you could soon find yourself playing catch up.
If you found this blog useful, why not check out our detailed white papers and reports here