The Background Behind the Urgent Need for Core System Modernization
In recent years, many companies have been pressured to modernize their core systems.
In a rapidly changing business environment, companies must leverage digital technology to reform business processes and maintain or improve their competitive edge.
However, the core systems of many companies lack the flexibility required to adapt to these changes.
Core systems that have been in use for many years have become complex due to repeated modifications and feature additions, leading to increased maintenance and management costs.
In many cases, proper maintenance has become difficult due to the retirement or shortage of engineers who understand the system architecture.
These issues are known as the "2025 Digital Cliff."
This issue, highlighted by the Ministry of Economy, Trade and Industry, warns that from 2025 onwards, the maintenance and operation of aging systems will reach their limits, potentially resulting in economic losses of up to 12 trillion yen.
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What Are the Reasons for Failure in Core System Modernization?
So, what are the reasons why core system modernization projects fail? The following are some typical examples.
- The Purpose and Expected Outcomes of Modernization Are Not Clearly Defined
- Over-Reliance on External Vendors
- Misalignment Between Management, Operations, and IT Departments
We will explain each of these individually.
The Purpose and Expected Outcomes of Modernization Are Not Clearly Defined
When initiating a core system modernization project, it is not uncommon to start with vague reasons such as "it is aging" or "maintenance has become difficult."
However, without a clear purpose or defined expected outcomes, the project lacks direction, leading to ad-hoc responses.
Furthermore, it becomes difficult to evaluate the return on investment, making it harder to gain understanding and support from management.
In addition, the success criteria for the project become unclear, creating a risk that proper progress management will not be possible.
To lead a modernization project to success, it is essential to clarify "why the system is being modernized" and "what is to be achieved," and to set specific numerical targets.
Over-Reliance on External Vendors
Modernizing core systems is a large-scale and complex project, which is why it is common to outsource to external IT vendors.
However, if a vendor that does not fully understand your company's operations and challenges leads the project, there is a risk that a system will be built that does not fit your actual business needs.
Furthermore, there are cases where vendor convenience or technical constraints are prioritized, leading to situations where the features and benefits you originally intended to achieve are sidelined.
For a modernization project to succeed, it is essential to establish a structure where your company proactively controls the project and collaborates with the vendor.
It is required that your internal members be deeply involved in critical phases such as requirements definition, progress management, and testing.
Misalignment Between Management, Operations, and IT Departments
Core system modernization involves diverse stakeholders, including management, operational departments, and the IT department.
However, because each department has a different position and perspective, misalignment often occurs.
For example, in operational departments, daily data entry is often perceived as cumbersome and burdensome, and because they only interact with their own department's interface, it is difficult for them to realize the importance of company-wide data integration.
The IT department may face situations where systems and tools are fragmented across departments, making overall maintenance and integration difficult.
On the other hand, management wants to see data integrated across departments, but this is difficult under the current circumstances.
Because the positions and perspectives of each department differ in this way, it becomes difficult to align the objectives and direction of the core system modernization.
As a result, partial optimization tailored to the convenience of each department proceeds, and the modernization project moves forward without achieving overall optimization, ultimately leading to failure.
Data Normalization Is Especially Important When Modernizing Core Systems for DX Promotion
Data normalization is essential to drive DX and achieve a truly effective core system modernization.
Let us examine why data normalization is necessary when modernizing core systems.
Core Systems Consolidate Vast Amounts of Corporate Data
Core systems handle various operational data that form the backbone of a company. Data from diverse departments, such as sales management, inventory management, financial accounting, and human resources and payroll, are accumulated daily.
However, this data is not always stored in an organized state.
It is necessary to appropriately perform data matching to ensure that data from different departments, various business systems, and both new and old records do not become intermingled.
Furthermore, data degrades over time. Maintaining outdated data requires significant costs and man-hours.
Despite this, many companies do not fully recognize the importance of data preparation, often leading to cases where the expected benefits are not realized because only the system was updated.
With the advancement of DX, the amount of necessary data—including customer management, marketing, and procurement—is continuously increasing.
If this data is not properly integrated, matched, and continuously maintained, DX initiatives may end up being nothing more than a pipe dream.
Therefore, data preparation with a forward-looking perspective is indispensable for core system modernization.
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Expected Benefits of Data Normalization
Data normalization facilitates smooth data integration between departments, thereby improving operational efficiency.
Because normalized data can be easily shared and utilized across different departments, it enables the reduction of redundant tasks and the centralized management of information.
Data quality is improved by resolving data duplication and inconsistencies. This reduces the risk of making decisions based on incorrect data, enabling more reliable decision-making.
As a result, it becomes easier to align the perspective of the entire organization, from management to frontline staff.
In addition, normalized data expands the scope of utilization, potentially leading to new value creation and problem-solving.
For example, when utilizing advanced technologies such as AI and machine learning, more precise data analysis and forecasting can be performed.
Examples of Data to be Normalized During Core System Renewal
While it is difficult to make company-wide optimal decisions when data is siloed by department, centralizing data management can enhance efficiency and competitiveness across the entire organization.
So, what specific data should be integrated?
Below, we introduce the primary data that will be normalized during the renewal of core systems.
Customer Data
Customer data is vital information for managing the relationship between a company and its customers.
By normalizing this data, you can gain a deeper understanding of customer behavior and preferences, leading to the development of effective marketing strategies and the improvement of customer service.
This will increase the accuracy of customer segmentation and enable personalized approaches tailored to individual customers.
Examples of Customer Data
- Basic Information (Name, Address, Contact Information, etc.)
- Transaction History
- Inquiry History
- Customer Attributes (Industry, Size, Needs, etc.)
- Customer Satisfaction Data
Product Data
Product data is essential for managing information regarding the products and services offered by a company.
Standardization enables increased efficiency in inventory management, optimization of pricing strategies, and the acceleration of new product development.
Furthermore, by integrating this with customer data, companies can identify cross-selling and up-selling opportunities, thereby contributing to increased revenue.
Examples of Product Data
- Product Code
- Product Name
- Pricing Information
- Inventory Information
- Supplier Information
- Product Attributes (Categories, Specifications, etc.)
Transaction Data
Transaction data refers to information regarding a company's daily commercial activities.
Normalizing this data improves the accuracy of cash flow management and forecasting, which helps maintain financial health.
Examples of Transaction Data
- Order Information
- Billing Information
- Payment Information
- Delivery Information
- Return Information
Financial Data
Financial data serves as the foundational information for understanding a company's economic status and making strategic decisions.
Real-time monitoring of business performance and more precise financial analysis require the proper organization of financial data.
Normalization contributes to the advancement of budget management and improves the accuracy of investment decisions, ultimately leading to the optimization of a company's financial performance.
Examples of Financial Data
- Sales Data
- Cost Data
- Expense Data
- Asset Data
- Liability Data
Independent Simulation: Man-Hours Required for Normalizing Core System Data
Since core system renewals typically span long periods, it is essential to understand the required man-hours in advance.
So, how much time is actually required?
At uSonar, we have simulated the man-hours required for core system data normalization as follows.
Prerequisites (Source: uSonar Research)
- Total Data Records: 100,000
- Data Including Duplicates or Inconsistencies: 40% (40,000 records)
- Processing Time per Record: 5 Minutes (Average processing time including corporate research, correction of inaccurate data, and duplicate checks)
Simulation
- 40,000 records × 5 minutes = 200,000 minutes = 3,333 hours ≈ 416 man-days
In other words, if one person were to work on this for 8 hours a day, it would take approximately 416 days (more than one year) to complete.
However, this workload includes not only simple mechanical tasks but also the following operations.
- Data Identification and Analysis
- Definition and Standardization of Data Items
- Formulation of Data Cleansing Rules
- Development of Data Transformation Logic
- Post-Transformation Data Validation
In reality, this work requires advanced business knowledge and data analysis skills, which may necessitate even more time and effort.
At the same time, this simulation demonstrates that data maintenance accounts for a significant portion of the workload.
uSonar: Supporting Core System Modernization Through Data Alignment
While data normalization is critical when modernizing core systems, it remains a major challenge for many companies.
uSonar maintains one of Japan's largest corporate databases, containing 12.5 million records. By utilizing this as a "dictionary," companies can automatically perform data matching and maintenance for their core systems.
This significantly reduces the man-hours required for data preparation and ensures that data remains accurate and up-to-date at all times.
Furthermore, because uSonar solutions can be implemented without altering existing operational workflows, you can improve data quality while minimizing the impact on business operations.
Summary
Modernizing core systems is a critical initiative for driving corporate digital transformation, yet achieving success involves numerous challenges.
Data normalization is particularly vital.
By properly organizing key data such as customer, product, transaction, and financial data, you can expect to improve operational efficiency and the quality of decision-making.
However, since data normalization requires significant man-hours, it is necessary to leverage external experts and systems.
By doing so, you can efficiently improve data quality through automated data maintenance and phased implementation.
Recognize that the success of core system modernization lies not merely in system updates, but in data organization and its effective utilization; approach this initiative strategically.
