Accruing data has never been simpler. But how can you ensure you’re collecting, maintaining, and analysing the right data?
You rely on your data to make informed decisions and develop robust business strategies. That’s why it’s vital the data you use is of a satisfactory standard, so you can trust in the insights it affords.
Not all data is created equal, and one of the major downsides to amassing big data sets is an overreliance on poor quality information. This can lead to errors, inaccuracies and bad decision making, so you need to take steps to improve the quality of your data.
In this post, we’re taking a closer look at ‘good data’, defining what it is and how you can improve it to aid sound business decisions. Use the links below to navigate or read on for the full guide.
- What is Good Data?
- What Are the Characteristics of Good Data?
- How Can You Improve the Quality of Your Data?
What is Good Data?
The term good data can sound somewhat abstract, so it’s perhaps more appropriate to think of it as data quality. Ultimately, it comes down to using data of an acceptable standard, which will help you to meet objectives and support business decision making.
To further complicate things, there is no real difference between good and bad data. Instead, it’s how and why you collect the data that defines its quality, as well as the processes you use to clean it, consolidate it, and ensure it is accurate and valuable.
Since the emergence of big data, brands have sought to gather as much information as they can. But doing so without a clear objective can lead to a drop in data quality and make it much harder to glean actionable insights from these large, uncontrolled data sets.
Rather than collecting masses of data, it’s much better to accrue a smaller volume of data that directly relates to your overarching business objectives. For instance, you might be looking to analyse your sales rep performance or supplier performance. By setting out the ‘why’ you want to collect certain data you’ll not only improve decision making, but make it much easier to collect and maintain data quality and accuracy.
What Are the Characteristics of Good Data?
First and foremost, good data should serve a purpose, bringing value and insights to your operation. But there are other characteristics that define it too, as we explore below.
- Accurate – data accuracy can be hard to distinguish if it’s been accrued without a clear objective in mind. When you know how the data will be used, you’ll know what to look for, which will make it much simpler to maintain accuracy, precision, and relevancy.
- Consistent – good data relies on steady, controlled collection, so you need to have an appropriate mechanism in place to automate data accrual. The right software allows systematic collection from multiple data sources, so you can guarantee a reliable, consistent stream of data into your business.
- Meets the requirements – collecting data without a goal in mind can quickly lead to a drop in data quality. That’s why it’s important that all departments understand why they’re collecting data and what they plan to do with it. Data should meet set requirements, fulfilling a pre-defined purpose. This ensures the validity and legitimacy of the data you collect.
- Data completeness – any gaps in your data collection strategy can be damaging, jeopardising the accuracy and value of potential insights. Missing data can also leave you without the complete picture, which will make decisive and informed decisions more difficult to achieve.
- Accessibility – if the data you collect is poorly managed, organised, and difficult to access, your teams simply won’t be able to use it. Careful management is a crucial factor in maintaining data quality, so be sure to invest in a software platform that allows for streamlined and efficient data management and control.
How Can You Improve the Quality of Your Data?
Improving the quality of your data isn’t a quick fix you can make overnight. However, there are tools and practices you can implement to begin to transform your data, as we take a look at below.
Set minimal data entry standards and policies
Data entry rarely comes from one source. Information streams into your business from multiple avenues, with each department utilising information and insights differently.
To maintain good data quality, you need to set a minimum benchmark for data entry. This will help to safeguard data quality irrespective of when and where it’s accrued, and who by.
Agreeing data entry standards across the business can reduce inaccuracies, data gaps and duplication. The cumulative effect of such measures can have a lasting, positive impact on the quality and completeness of your data.
And of course, the technology you use to gather data across multiple sources is imperative here. ERP systems enable you to enforce data cleansing, enrichment, and validation rules in your business so you can be sure your data sets are relevant, complete and of the highest quality.
Customise your business management software for quality data capture
Setting up your business management software to ensure data accuracy and quality is maintained company-wide is easy when you utilise the power of modern ERP systems.
With the latest ERP software, you can set up user interfaces to only show what a role or department needs on a day-to-day basis. For instance, your sales personnel can be presented with a data capture form that contains all the vital fields they need to fill out to maintain a quality database. You can make certain fields required so important information isn’t missed and you can set up alerts to ensure all essential information is captured at the point of entry.
When using 3rd party applications or EDI, it’s also essential to validate any imported data by running business logic rules, ensuring the information received meets your database requirements.
So, when it comes to data quality, the systems you use to run your business are vital in providing you with a streamlined means of gathering and distributing your data that ensures total accuracy and predictability.
Reduce/Remove duplication & historical data
If you’re working with legacy data sets and want to consolidate the information you have, one of the first things to prioritise is a data clear-out.
Given the volume of data your system deals with daily, it’s not uncommon to see a build-up of old and irrelevant data which may affect your report running or transaction processing. A lean and relevant database is key to your operations so a great way to remove this unwanted and historical data is to perform a ‘data clear-out’ on your system. Not only does this process allow you to archive unwanted data, but it also drastically reduces your database size while improving the speed and performance of your system.
How do you reduce duplicates from your data going forward? You’ll need the right software to help you detect and flag copies and inconsistencies as they happen.
Some modern ERP systems enable you to set up unique identifiers on any field and highlight the exact information you need, for example, phone numbers or addresses in a certain way. You can set up unique identifiers on product codes, customers, or suppliers and if a user tries to input a duplicate, the system will alert them. And as mentioned above, you can also set required fields to ensure certain data is always captured.
It’s all about getting your data right in the first place. Your system plays a key role in ensuring this happens from the outset.
When you run multiple disparate systems and applications across your business, this can compromise the quality and consistency of your data sets. With departments operating different platforms, it becomes impossible to maintain accurate data entry, thus leading to errors, duplication, and poor data sets.
Rather than continuing with this fragmented way of working, switch to an integrated solution, like ERP software. Such a platform allows departments to work with different applications from a single, unified database, so all the data and assets they gather and use are contained in a centralised location.
Integrating software in this way is one of the most powerful means of improving the quality of your data sets. It also improves the accessibility and usability of your data, so you and your teams can put these assets to better use.
Improving the quality of your data can feel like an uphill battle, but with the right software in place, it doesn’t have to. At Intact, we offer innovative business solutions that can streamline your day-to-day operations, including data entry, capture and consolidation. For more information or to learn more about our products and services, visit the homepage or get in touch today.