Data is the center of business nowadays. However, if the data quality is poor and the records are inconsistent, it results in lost business opportunities, operational issues, and invalid analysis. With poor, inconsistent data, teams operate in silos, wasting time cleaning data in spreadsheets rather than driving business growth. According to Gartner, organizations lose an average of $12.9 million annually due to poor data quality.
For most companies, it is not a question of removing faulty data, it is a question of avoiding errors from occurring in the first place and having a process in place that maintains data accuracy and consistency as it flows through the company. To solve these issues, a corporate Data Quality Initiative was undertaken by a renowned firm, creating a rule-based, automated, scalable Data Quality Dashboard (DQD) that would identify and fix data errors within minutes.
“Bad data is not a technical issue, it is a business issue,” states one of the solution’s principal designers, Chandra Bonthu. “When you have poor data quality, sales teams miss opportunities, analytics teams can’t deliver insights, and operations teams can’t deliver services. We needed a system that would cut through those roadblocks and ensure that bad data wouldn’t interfere with business processes.”
The project began with a proof of concept demonstrating the impact of automation in data quality issue identification and correction. Depending on leadership approval, a new and scalable DQD was created, which can handle multiple business units without a huge code overhaul. The goal was not just to clean data but to create a long-term system that would ensure high-quality data for all departments.
Preventive steps were adopted when data entry was initiated. Further validation procedures ensured that data entry teams did not enter wrong data into the system before it became an issue. By implementing real-time checks and data validation rules, the organization could prevent bad data at the source, reducing the necessity for expensive manual repair.
In just a couple of years, the business saw a significant reduction in data quality errors, greatly enhancing overall performance. Bid win rates increased as sales teams could depend on complete and accurate data while developing proposals. Analytics and BI teams provided more precise insights, enabling leaders to make better-informed decisions based on data. Operations teams improved service delivery, offering clients more accurate, timely, and efficient solutions. The business launched new products informed by analytics, generating additional revenue through enhanced data insights.
Because of this success, the DQD architect received an internal award recognizing the impact of this project across the enterprise.
However, data quality was only half of the issue. Another large issue was having variable data throughout the company. In the absence of a single source, various teams relied on contradictory records for customers, suppliers, healthcare professionals, healthcare organizations, clinical trials, and trial sites. This variability led to issues in business processes, duplicated efforts, and unstable analytics models.
To address this issue, a multi-domain Master Data Management platform was implemented. This provided a single source of truth for high-quality data for the company.
“Having the same, clear data throughout the business makes groups perform better and more quickly,” Chandra says. “With MDM, we removed duplicate records, cleaned up our datasets, and gave groups the most accurate and current information available.”
The MDM platform revolutionized the way data was handled. This revolution allowed the creation of stronger customer relationships since sales and service teams could utilize a single correct record rather than inconsistent data. Product development and service provisioning happened quickly. Operations teams could rely on high-quality data to accelerate project schedules. Improved analytics and AI models were developed since data scientists had clean and standardized data to make more accurate predictions. Furthermore, the global MDM market is projected to grow from $17.64 billion in 2024 to $20.5 billion in 2025, reflecting a compound annual growth rate of 16.3%.
By using the Data Quality Dashboard and the Master Data Management platform, the business revolutionized data processing, management, and use. The solutions improved efficiency, decision-making, and set the business up for long-term success.
“Data is more than numbers in an organization; it allows businesses to make critical decisions,” says the project architect. “By fixing our data problems, we did not just fix a technical problem, we allowed our business to grow, compete, and thrive in a data world.”
With improved data quality, increased chances to win bids, improved analytics insights, and more efficient business processes, the company is now better positioned to develop even more innovations in the future. As businesses keep innovating, data will be significant in discovering new opportunities, simplifying things, and remaining ahead of the competition in an even more competitive market.
