The importance of data accuracy
Data is one of the most important topics people are talking about in business right now. And if your business is handling large volumes of data, great — you’re bound to be set up for future success. But there is one thing that might get in the way of that and make handling data more of a burden than a success -> inaccurate data. In this insight, we’ll dive into the importance of data accuracy and the top 5 consequences of inaccurate data for your business.
What is data accuracy?
Data accuracy is all about whether the data you’re gathering and using is correct, consistent, and up to date. It should also be presented in a standardized format without any missing information or errors.
Why it's important to collect accurate data
If your business is data-driven, data is not only your biggest asset — top management will be making a lot of decisions based on it. Data can provide immense insight and an understanding of what’s going on in your business, what’s driving its successes, and where you’re losing money or efficiency along the way.
Gathering a bunch of raw data isn’t really where the magic happens — what matters is how you process that data. And often, you need more than one software system to do the processing. That’s where things start to get messy and complicated.
The importance of accurate information in your business
Our world right now is fast-paced, and it's not slowing down anytime soon. A business that wants to compete in the long run needs to respond to competitors, customers, the weather, and major world events quickly.
Having this information at hand (ideally in real-time) can give your business the competitive edge it needs, ensure top management makes the right decisions, and is vital for keeping up with fast-changing markets.
Gathering just as much data as possible, without considering its quality and accuracy, can be fatal to a business. You need to be able to base your decisions on data you can rely on.
What leads to inaccurate data
If it's incorrect, you can't rely on your data — but what leads to this state of affairs? Here’s what we’ve seen happen in companies time and time again:
Data is not up-to-date or live
You have a ton of data and maybe even have processed it and gained huge insights. But the data you got there was gathered years ago, and you only get to present it now. This is a big problem because in a year the market could have completely changed. Or maybe a sales agent of yours is meeting with a client presenting current sales numbers, but when the client asks when these were recorded, the answer is 3 months ago. This traditional way of analyzing and presenting data is no longer current. Basically, you want a live data dashboard where you can immediately and in real-time gain insights and make decisions. This would also ensure that you can catch any changes very early on and act quickly before it's too late.
Employees are manually transferring data
Another typical situation that causes data to be incorrect is the manual transfer of data by your employees. For example, you have a CRM system, a customer support system, and two data sets of customer addresses. When a customer emails you, you have to go into the CRM system to get their phone number and manually put it into the customer support system. That might seem like something tiny, but it causes a lot of inefficiencies, and human error is an issue. By linking the systems and ensuring they only have one source of truth to pull their information from ensures your data is always accurate and correct.
Top 3 consequences of inaccurate data
Using inaccurate data in your business has several consequences, some more fatal than others, but these are the top 3 we've seen play out in businesses so far:
Technology should be helping us do our job, not stopping us in our tracks, making things more complicated, or even causing us to make mistakes we're not even aware of. Let’s take the following example: if I have an employee making decisions based on inaccurate data that impact on how he/she performs at work, it's going to bum them out. It might even cause them to miss out on promotion to a particular position because of certain mistakes attributed to their incompetence. This would cause a lot of frustration and tension among employees. And in case you didn’t know already, employee satisfaction is a huge contributor to the success of your business.
Competitors outrunning you
Especially in highly competitive industries like online retail, gathering data and repurposing it to make advertising decisions can put you ahead of your competitor. If you're not using big data to target your customer service, your competitor will do so and probably outrun you. Or if it so happens that you are targeting customers, but the wrong ones because your data is inaccurate ... well, that's not really going to help your bottom line either, is it?
In a large organization you don't have time to talk to every employee or every customer, so data will be your go-to when it comes to making big strategic decisions. The problem is that you could end up downsizing an entire department, closing down stores, or firing your best marketing lead, all because you think that a particular business sector is not profitable (on paper). But what if the data was incorrect, and it turns out that the business area contributes a significant amount to your bottom line? Well, then you've just made a terrible decision that could break your business.
Data accuracy over quantity
Unless you've been living under a rock, you know that gathering data is important. But what we want to highlight is that actually just gathering any data — and huge amounts of it — is not the way to go. Yet, high-quality data that is accurate can be so much more powerful when it comes to making business decisions.
The first step you can take to gathering accurate data is to integrate your enterprise applications. What do we mean by that? Make sure they talk to each other and only have one source of truth. Check out our intro to Enterprise application integration insight right here to find out what that could look like.
Data and data accuracy is a vast topic, and we're just getting started. In the following weeks, months, and probably even years, we’ll be covering an array of subtopics when it comes to gaining accurate data. What are your thoughts on data accuracy? Is it more important than gathering a bunch of data? Drop us an email at email@example.com — we’d be glad to continue the conversation.
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