Handling data is complicated and often difficult for the company. Errors in data processing can create distrust from customers, which leads to a lack of brand loyalty. While some might think that it’s not important, improving data quality is crucial for success and the benefits of data quality can help your organization prosper.
A recent study by IBM estimated that $3.1 Trillion of America’s GDP is lost due to bad data and 1 in 3 business leaders don’t trust their own data. Have we now captured your attention as to why it is important for your business to deal with high-quality data?
The problem with high-quality data is that it is expensive and time-consuming to produce. Organizations have a lot of investment in their current data management strategy, and they are reluctant to change it.
The value of data is not only in its quality, but also in its quantity. Organizations that analyze and extract large amounts of data are more likely to find patterns, trends and correlations between different variables than those who do not have enough data.
The more high-quality data an organization can collect, the better they can understand their customers’ needs and provide them with a personalized experience.
What is Data Quality?
Data quality is the degree to which data, and data processes, meet the organization’s quality objectives.
Data is an asset of an organization and it should be treated as such. It should be managed in a way that it can help the organization stay competitive. It is a measure that can help us determine how well data meets organizational requirements.
Data quality for organizations can be measured with three different dimensions – accuracy, timeliness and completeness. Accuracy measures how close a data point is to the true value of what it represents; timeliness measures how up-to-date the data is; and completeness measures whether all required information has been captured or not.
What are the benefits of using high quality data?
There are many benefits of data quality such as:
1- Improved decision-making
The benefits of data quality are the key to success in today’s competitive business world. They help organizations make informed decisions, and help people make better decisions in their personal lives.
Data is the fuel that powers the digital economy. The more data, the better. But how does quality of data affect business decision making?
The availability of high-quality data has helped businesses make informed decisions about what products to offer, where to locate their stores, and how to price their products. The availability of high-quality data has also helped individuals make better decisions about what schools and colleges to attend, which retirement investments are best for them, and whether they should buy a house now or wait until later.
2- Reduced risk
The most obvious benefit is that it helps in decision making and risk reduction. Better data means better decisions, which means lower risks for the company. It also helps in securing customer relationships and ensures that they are not lost due to poor customer service or some other issue with the company’s operations.
3- Increased customer satisfaction
Better data is crucial for a company to be able to provide their customers with the best possible experience. It is what allows companies to improve the customer journey and create a better customer experience.
One of the ways that high quality data can help increase customer satisfaction is by providing personalized content for customers.
This could be done by using machine learning and AI to analyze past interactions between a company and its customers, as well as their browsing behavior on the website, in order to provide them with content that they are most likely interested in.
4- Reduced costs
One of the most important benefits of data quality is the reduction in operational costs due to a reduction in errors and rework.
Organizations are constantly looking for ways to reduce costs, and high quality data can help to do that. It will enable organizations to reduce data related errors and the complication related to fixing data issues, which will not only reduce operational costs but also improve customer experience.
By reducing errors and mistakes, organizations can save time and money in the long run as they don’t have to redo or correct their work.
5- Enhanced reputation
Another important benefit of data quality is the ability to enhance the overall image and reputation of any organization.
There are many ways that high quality data can be used to improve an organization’s reputation.
First, it can be used to help the organization gain a competitive advantage in the market. Second, it can be used for organizational growth and development. Third, high quality data is often necessary for compliance purposes. Finally, it is also necessary for innovation purposes such as developing new products or services.
6- Increased revenue
Data helps an organization increase its bottom line by understanding how customers will react to different pricing strategies, promotions, and offers that they are likely to respond favorably to based on what they have done in the past with the company or similar companies in the same industry sector or niche market segmentation
7- Increased agility
Organizations that are data-driven are more agile in today’s fast-paced business environment.
One of the most important benefits of data quality is the ability to improve agility.
High data quality is a key to organizational agility. It can be defined as the degree to which data is complete, consistent, and accurate. Organizations need high-quality data in order to make decisions that are timely and accurate to their needs.
How to achieve high quality data?
High data quality can be achieved by following a few simple steps:
1) Define the data quality requirements for your data.
2) Create a strategy that will help you meet these requirements including data quality assessment and monitoring.
3) Make sure to use the right tools to keep your data up-to-date.
4) Continuously measure and monitor your progress.
5) Implement an action plan when you identify any deviations from the desired state of high data quality.
