One of the hottest topics in the business world these days is data. Many business owners are delighted with the insight and value that their business data can give them. Data is seen as one of the most valuable resources.

However, this does come with a caveat. Data is only a valuable resource if it is high-quality. Low-quality data is, at best, inconsequential and, at worst, can drive businesses to make costly mistakes. For example, the Data Services Insight report from Royal Mail concludes that bad customer data can cost organisations around 6% of their annual revenue.

These bad data costs tend to comprise the time employees need to spend correcting bad data and the impact on customer service.

So, as you can see, improving the quality of your data is vital for businesses. Take a closer look at data quality and why it is so important.

What is Data Quality?

Data quality is a measure of the condition of data based on factors such as accuracy, completeness, consistency, relevancy, timeliness and validity:

  • Accuracy refers to how well the data represents the real-world conditions it aims to describe. Inaccurate data will cause businesses problems, leading them to make decisions that might not have the desired effects.
  • Completeness – all the data that is supposed to be collected needs to be collected. Otherwise, there will be gaps. If data is incomplete, businesses may have trouble gathering accurate insights.
  • Consistency – there should be no difference between multiple versions of a single data item across multiple databases or data sets. Otherwise, different departments may operate under different assumptions of what is true.
  • Relevancy – the data your business collects must be useful for the campaigns and initiatives you plan to use. It is not useful if it is not relevant to your business.
  • Timeliness – data should be recorded as soon after the real-world event occurs as possible, as it becomes less accurate and less useful the longer.
  • Validity – this factor refers to how the data is collected rather than the data itself, as if it is not of the correct type or doesn’t fall into the right range. You may have issues with organising and analysing it.

Why is Data Quality important?

More and more businesses are relying on data to help them make more informed decisions about finance, marketing, product development and so on to keep up with their competition.

For this data to benefit a company, it must be of high quality. The better the data quality you collect, the more you can get out of it. If business decisions are based on bad data, you will likely fail.

New technologies, such as artificial intelligence (AI) and automation, are also increasing the importance of data and its quality, as they rely heavily on large volumes of accurate data. The more high-quality data a machine learning algorithm has, the faster it can produce results, and the better these results will be.

It is no wonder that data is becoming an increasingly integral part of many business operations, with successful companies integrating it into everything they do. However, this increased data integration means that quality is vital to the success of many aspects of a business – from content creation and marketing to sales.

Data quality is also a critical aspect of compliance-related issues. As regulations surrounding data (such as GDPR) continue to develop, it is becoming more and more important for companies to manage their data properly. It is much harder to demonstrate compliance if your data is disorganised and poorly maintained.

What are the benefits of good Data Quality?

As we have seen, good data quality is crucial for businesses to take advantage of opportunities and keep up with (or even overtake) their competition.

High-quality data can also provide the following benefits for businesses:

  • Better audience targeting – allowing you to develop content or products that appeal to the right people.
  • A competitive advantage is discovering potential opportunities before your competitors and therefore beating them to sales.
  • Easier implementation of data – due to not having to spend time fixing poor-quality data to make it usable and ensuring all of your departments are working on the same data.
  • Improved relationship with customers – you will get to know them better and can build a strong, trusting relationship with them.
  • Increased profitability – as high-quality data helps you decrease waste and increase sales.
  • More informed decision-making – giving you more confidence in your decisions, thanks to a decrease in risk.
  • More effective marketing campaigns – as you will know more about your audience and can create adverts and content that appeals to them.

The technologies your business uses and the team you have to provide data play a central role in your data quality strategy. Working with Agile Recruit to strengthen your data quality team can make ensuring data quality much easier.

Want to learn more about how Agile Recruit can help you ensure data quality and make the most of your data? Contact us today!

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