The seemingly elusive goal of data integrity is not as elusive as some businesses think. It just needs to be better understood, for without confidence in your numbers, you can’t make good business decisions. In short, data integrity is not a “nice to have” – it’s essential.
Smart business leaders know the best everyday decisions are made using real-time data. Data integrity assures your day-to-day lead indicators of overall businesses health are valid, and ensures your real-time data is useful, not misleading.
So how to get it, and how to keep it? First, let’s look at what data integrity is.
What is Data Integrity?
Data Integrity has become a catchy buzzword of late, and many (if not all) businesses have committed to the concept in theory and intention, but because the term is so often misunderstood, execution often remains in the too-hard basket.
So, let’s look at Data Integrity, as defined:
- Avoiding unintentional changes to data and;
- Ensuring data is recorded exactly as intended and;
- Ensuring the data is the same (as it was when it was originally recorded) when we go to retrieve it.
The definition makes perfect sense, but what does it really mean? A deeper dive takes us into the specifics. The three key, immutable elements that must be addressed in a business to achieve data integrity are accuracy, completeness, and consistency. We call these the Three Pillars of Data Integrity.
The challenge, of course, is many businesses focus on one or two elements and run out of steam. But if any one pillar is weak, data integrity is unsustainable. Once we understand and commit to the pillars, processes can be embedded into day to day work practices, and create a foundation for solid decision-making.
Accuracy
Unintended changes to data can (most) often be traced to human error. As Charles Colton said some 150 years ago;
“Ignorance is a blank sheet, on which we may write; but error is a scribbled one, on which we must first erase.”
Ask yourself , “Are my data integrity risks due to ignorance or error? Do we need to educate, re-educate or simply take greater care?” If you cant answer this question, fear not. It is likely a unique combination of all three.
Ensuring the “right people are in the right place with the right training” is mission critical to data integrity, and this cannot be overstated. Before we can truly address data integrity, we have to figure out where the problem (and pain) is coming from – and then and only then can we work towards eradication.
Data capturing systems have become very sophisticated, but they don’t respond to good intentions. For example, a robust and user-friendly database platform such as Xero will keep its part of the “data bargain” — but if we take the “garbage-in-garbage-out” adage and run with it – even the most sophisticated platform can only work with what it gets.
Depending on the data involved, an accuracy fail is often as a simple as a single wrong digit in an otherwise perfect file. For example, in an accounting practice, an errant GST code in one transaction can send an entire month-end process into a tail spin.
Depending on the data involved, an accuracy fail is often as simple as a single data process error in an otherwise perfect file. For example, in accounting, an errant GST code can cost a business thousands in GST claims.
An analysis of where the errors or or ignorance lie is the only way forward.
Completeness
Again, human error will always find its way, but when we look at completeness against accuracy, it’s not the same beast. For example, an item left in draft on a database might be accurate, but not processed. Accuracy is left wanting without completeness.
In the finance world, the assertion of completeness is key. In short, financial statements must be thorough and include every single item that should be included for a given accounting period.
While this sounds daunting, modern technology is on our side. Giving visibility to these simple errors using reporting tools that highlight incompleteness is the most efficient and effective way to create the behavioral change necessary for success.
If you can help people understand how an error as simple as a transaction left in draft affects another data point downstream — you’re on the right track.
Consistency
Creating workflow processes that outline the data input-to-output journey will strengthen accuracy and completeness, but it can’t solve the consistency issue.
One of the best ways to manage data integrity? Find a tool that can look for data inconsistencies in your systems. This ensures a proactive approach to identifying a process issue… before it gives you pain.
Using the GST example again, reporting and query tools can enable searches specific to examining the GST coding by account and contact will resolve inconsistencies before it’s too late.
The Way Forward
Underpinning every good business decision is data, but without data integrity, error and risk will also underpin every decision. Time and cost efficient mechanisms such as reporting and query tools that interface seamlessly with your databases will help you to discover your exposure, and manage it.
For more information on how to achieve data accuracy, completeness and consistency, with your client’s Xero file, schedule a call with one of the team at Zerlock today.
