Data Utilization in Enterprises: Essential Processes and Challenges to Resolve

Organizing, Distinguishing, and Updating for Corporate Data Utilization

By creating integrated data, companies can not only execute efficient marketing measures based on appropriate STP analysis (*1), but also manage information to implement sales approaches aligned with customer status and execute retention strategies.

However, the challenge is that data cannot always be collected in a "clean state." Taking corporate data (company names) as an example:

• Company names become outdated due to name changes during the fiscal year following business integration.
• Name changes occur for the purpose of strengthening branding.
• Abbreviations become generalized, leading to discrepancies between official names and input information.

These issues occur, making it difficult to identify where the "latest source of information" is located within the company. [As an aside, companies like Dropbox in the U.S. refer to this "latest source of information" as a Single Source of Truth (SSOT) (*2).]

The necessary tasks to make data easier to handle are "Organizing," "Distinguishing," and "Updating." In the specific process of the company name example mentioned earlier, the following tasks occur continuously:

• Organizing
  - Consolidate Duplicate Company Information Into the Official Name.
• Distinguishing
  - Delete Outdated Information.
  - Separate the Latest Information.
• Updating
  - Add the Latest Information to the Consolidated Company Names.

By "Organizing," "Distinguishing," and "Updating" data to create "clean" integrated data, it becomes easier to add not only internal data but also more third-party data.
By adding information that the company previously did not possess, it becomes easier to deepen customer insights and design more concrete sales strategies and marketing measures.

*1: Abbreviation for Segmentation/Targeting/Positioning. One of the representative frameworks in marketing.
*2: Reference URL

Four Challenges for Corporate Data Utilization

Reading through the results (*3) of the "Survey Research on the Measurement of Economic Value of Digital Data and the Current State of Utilization" conducted by the Ministry of Internal Affairs and Communications in 2020, it can be inferred that many B2B companies are not engaging in integrated data utilization measures such as "forecasting" or "AI utilization," and that data utilization in B2B companies is in a situation where they continue to use data without integrating flawed information.

The causes of this situation are common to many companies and are referred to as "data utilization challenges." Specifically, there are the following four items:

1. Integration and Correction (Data Quality Management)

If you assume that all data collected/held by your company is correct, data utilization will fail. As noted in the company name example, it is necessary to take the perspective that outdated and inaccurate information is mixed in.
By creating a management system that distinguishes between necessary and unnecessary items from the data held by the company, you can improve data quality and create a system for faster and more accurate decision-making.
In the U.S., it is said that the average annual loss for companies due to poor data quality reaches $10 million (*4), and the concept of data quality management utilizing technology has permeated.
In Japan, data quality management is also considered an important response item for companies, and a guidebook (beta version) has been released by the Government CIO (*5). However, since data quality management involves major changes and resistance such as complex tool introduction and workflow renewal, the current situation is that many Japanese companies are not progressing as expected.

2. Reinforcement and Standardization

There are other positive effects of improving data quality. It means that the "integrity of data" can be better guaranteed. Especially when performing "data reinforcement," such as adding more information using third-party data, being able to prepare high-quality data that is the latest and has no notation variations is a major advantage.
Most providers of third-party data excel in data updateability. Conversely, this means that old data and incorrectly written data are immediately removed from the database.
Also, third-party data is not perfect. There are providers that have less comprehensiveness in exchange for strengths in updateability. To maximize the use of data from providers that offer the latest data under specific conditions (e.g., limited to listed companies or industry-specific), it is important for the recipient to also maintain accurate data.
To maintain accurate data, it is necessary to establish a standard data format. This standardizes the rules for how data is collected/held. It is also important to grasp what kind of reinforcement data is needed by visualizing the parts that can be collected by the company alone (and the parts where data is missing) from the format.

3. Workflow Organization and Penetration

Even if you prepare an environment for accumulation, it does not mean that preparations for data utilization are complete.
As mentioned at the beginning, it is necessary to prepare an environment where collected data can be easily referenced.
By stipulating certain reference rules and having everyone in the company comply with the usage methods according to the rules, you can maximize the resources of the sales and marketing departments to collaborate on lead acquisition and customer satisfaction improvement, thereby maximizing the company's revenue.
Specifically, you can collaborate on activities such as extracting company lists based on conditions like "ideal customer profile," "high-potential customers," and "customers with high similarity in corporate attributes" from high-quality data collected from inside and outside the company, and further narrowing down the targets to approach now while looking at recent behavioral data (interests) and outgoing content (news).

4. Construction and Operation of a Cloud-Based Data Utilization System

Speed is required in the environment where data is referenced.
If you say, "Data was easily extracted, but it was information from two weeks ago," you cannot approach customers in a way that exceeds their expectations.
Although the sales and marketing departments lead the list creation using data, they cannot handle fresh data with analog methods.
This is where cloud-based data utilization solutions become necessary. The cloud's strengths are the reflection of updated data and the speed of extraction, and it enables multiple people to work simultaneously. Also, since settings can be saved for each individual user, it leads to labor saving and efficiency in routine work.
There is also a secondary benefit that communication between the IT department and sales/marketing can proceed speedily in that data linkage with tools such as MA and CRM that actually create and manage customer touchpoints can be performed smoothly.

To solve all "data utilization challenges," it is important not only to organize data within the company but also to select the provider of third-party data based on certain criteria. A cloud service that combines "updateability" and "comprehensiveness" and has a rich track record of integration with MA and CRM is desirable.

*3: Reference URL *4: Reference URL *5: Reference URL

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[Point Summary] Necessary Preparations for Building a Data Utilization System

The following points are considered important for maximizing the use of first-party data and third-party data.

First-Party Data

• Always manage the latest data.
• Eliminate notation variations and duplicates.
• Manage with a single tool and a single format.
• Create an environment where everyone in the company can see it.
• Identify content that tends to be missing.

Third-Party Data

• Use for reinforcing first-party data.
• Select providers with high updateability and comprehensiveness.
• Providers offering cloud-based services are desirable.

By being conscious of the above points, data utilization in companies will become more sophisticated.

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