Improving Data Quality: Essential for B2B Data Utilization

What Is Data Quality?

Data Quality refers to how well data is suited for its intended purpose. Generally, Data Quality is composed of the following six elements.

• Accuracy

  The extent to which data accurately reflects the actual state of reality.

• Completeness

  Whether all necessary data is present and no information is missing.

• Consistency

  Whether data is maintained without contradiction across different systems or locations.

• Up-to-dateness

  Whether the data is current and free of outdated information.

• Reliability

  Whether the data is obtained from a trustworthy source.

• Availability

  Whether the data can be accessed and utilized whenever it is needed.

By ensuring these elements are met, companies can make faster, data-driven decisions.

Prioritizing Data Quality is considered to provide the following specific benefits.

• Rapid Decision-Making Through Improved Accessibility

  Accessibility is deeply connected to integrity, consistency, and availability, referring to the ability for anyone to easily view data whenever it is needed. High accessibility allows various departments and personnel within a company to access necessary data quickly and effectively. For example, the ability for sales teams to instantly access customer data is essential for improving the quality of proposal creation and customer engagement. Delays in decision-making caused by reduced accessibility lead directly to the risk of losing competitive advantage and delays in customer outreach due to inefficient operations.

• Establishing a Data-Driven Culture Through Improved Productivity

  Productivity is deeply connected to accuracy, reliability, and currency, referring to achieving maximum results with limited resources such as time, effort, and cost. High productivity in B2B data means that data is utilized efficiently and the benefits derived from data utilization are maximized. For example, by accurately identifying target markets through data analysis and focusing sales activities, companies can reduce wasted resources and increase revenue. In companies where productivity is low, resources are not strategically allocated, leading to various opportunity losses that hinder overall corporate growth and result in a loss of market position.

• Building a Data Utilization Environment with Guaranteed Security

  Ensuring security is deeply connected to all elements of data quality, protecting data from unauthorized access and leaks. When data security is guaranteed, it means that critical information such as customer details and transaction data is stored safely and protected from external attacks and internal misuse. By strengthening security, data can be utilized as a tool to enhance corporate trust, thereby strengthening relationships with customers and partners. If security is not guaranteed, the constant risk of data leaks or tampering causing significant losses to the company makes employees feel that utilizing data is a risk.

Why "Improving Data Quality" Is Important

The reason data quality is critical in B2B data utilization is that it directly impacts the speed, accuracy, and efficiency of decision-making. Because information regarding business partners, market data, purchase history, and contract details is frequently used, it affects smooth operations across all departments, including sales, marketing, customer success, and management.

According to Gartner, poor data quality is said to cause significant losses for companies. For example, when data consistency is lost between different departments or systems, information from individual data sources causes contradictions, leading to situations where customer information held by the marketing department does not match the information held by the sales department. Such situations not only delay decision-making across the entire company but also lower the quality of those decisions, increasing the risk of opportunity loss.

In fact, as Gartner has pointed out in other research findings, poor data quality is said to cause an average loss of $12.9 million annually. Therefore, for companies to maintain a competitive advantage in the B2B sector, the maintenance and improvement of data quality are essential, requiring the development of appropriate systems and processes.

Summarizing the concepts proposed by Gartner, it is said that the following specific actions are necessary to improve data quality.

• Data Profiling

  First, begin by grasping the current state of the data and confirming its accuracy and completeness. This allows for the identification of problem areas and clarifies where improvements are needed.

• Data Cleansing

  This is the process of deleting or correcting inaccurate or duplicate data. For example, if the same company is registered under multiple different names, this includes unifying those records.

• Data Integration

  We establish a framework to integrate disparate data sources from both inside and outside the company, providing consistent data. This allows for the consolidation of siloed data and improves overall data quality.

• Establishing a Data Governance Framework

  We clarify data management responsibilities and establish rules for data creation, modification, and usage. This ensures that data quality can be maintained over the long term.

• Continuous Monitoring

  Data quality is not a one-time improvement project. It is essential to continuously monitor data and implement improvements as needed.

For leaders in data management and analytics departments, it is crucial to clarify how improving data quality impacts the business, establish company-wide standards, and communicate the benefits of continuously enhancing data quality across the organization to achieve ultimate business goals.

Actions Required for Improving B2B Data Quality

To improve the quality of B2B data, the following specific initiatives are required:

• Data Standardization

  Data standardization involves unifying the formats and definitions of data used within a company. In Japanese companies, it is common for data to be managed using different formats or definitions across departments, even within the same organization. For example, one department might record a company name in Kanji, while another uses Roman characters, leading to data inconsistencies. This makes data integration and consistent analysis difficult. To advance standardization, it is first necessary to analyze existing data to eliminate duplicates and contradictions. It is also effective to introduce tools that automatically unify formats during data entry. For instance, using an address standardization tool to unify addresses entered in different formats simplifies subsequent processing and prevents errors.

• Digitization of Business Processes

  Digitization of business processes involves converting paper-based operations into electronic formats to streamline data entry, management, and sharing. Many Japanese companies still use paper-based contracts and purchase orders, which presents several issues. First, paper media requires manual data entry, which is prone to human error. Furthermore, it is difficult to share data in real time, which hinders rapid decision-making. By advancing digitization—for example, switching to electronic signatures for contracts—data is immediately saved in a digital format and can be shared instantly among stakeholders. This improves data accuracy and enables real-time updates, thereby accelerating business speed. Additionally, digitized data can be easily integrated into analytical tools to derive insights that support strategic decision-making.

• Utilization of External Data

  The utilization of external data involves building richer and more accurate datasets by combining a company's internal data with reliable external data sources. Especially in the B2B sector, leveraging external data—such as domestic and international market trends, competitor information, and customer intent data (purchasing interest and behavioral data)—is critical for building a competitive advantage. For example, when a Japanese company expands into overseas markets, it is essential to incorporate local corporate information and regulatory data from external sources. Furthermore, by utilizing data from reliable database providers, companies can acquire detailed attributes of target firms and relevant market data, enabling more accurate targeting and market analysis.

Data standardization, digitization, and the proactive utilization of external data will serve as key elements in enhancing corporate competitiveness and supporting success in the global market.

Conclusion

Our customer data integration solution, uSonar, is equipped with LBC, one of the largest corporate information databases in Japan, which is characterized by its accuracy and richness. Furthermore, the matching report utilizing uSonar is highly effective for companies to evaluate and improve their own data quality. This report allows you to cross-reference your internal data with LBC data to identify and correct duplicate records and inaccurate information. It also provides the necessary information to improve data quality, such as data cleansing, attribute enrichment, and the visualization of corporate groups.

As Gartner points out, understanding that improving data quality is directly linked to business success and committing to company-wide data quality improvement is the key to enhancing corporate competitiveness. By leveraging a highly reliable external database like uSonar, you can grasp the current state of your data quality and implement concrete improvement measures to increase the accuracy of your internal data.