Utilizing data can be said to be the lifeline for business management, and data analysis can be expected to improve operational efficiency and increase customer satisfaction. Data management is a necessary strategy for data utilization, and data can be used for any business purpose. In this article, we will explain data management in detail and explain key points to ensure smooth data management.
What is data management?
It refers to the strategies companies use to safely and efficiently manage data and use it in a wide range of business situations. The scope of management is wide-ranging, and specific strategies include the following initiatives.
- Establish data utilization policy
- Build, maintain, and manage accumulated data and keep it ready for use at any time
- Improve data quality
As you can see from the details of the initiative, data management is not just about data management, but also includes the process of managing, using, maintaining, and improving it.
Three elements that make up data management
There are three elements that make up data management: Effective data management is only possible when these elements interact. Let’s take a look at what is required for each element.
data management
This is a fundamental element of data management. Efficient data management requires the creation of a system that allows appropriate and speedy access to data, regardless of its type or amount. On top of that, you need to make sure you know where the data is and check the required quality so that it can be used whenever you need it.
Data utilization
After managing the data, consider how to use the data, and the data accumulated in a company can be used for a variety of purposes, including the following.
- When developing products, use past product data and requests from customers as a basis.
- Monitor how customers use products to improve after-sales service
Rather than utilizing these tools only within the company, there is now an emphasis on collaboration with external companies and tools. It is important to discover new value by utilizing data.
data protection
In recent years, cyberattacks targeting companies have increased rapidly, and their methods have become more sophisticated. Additionally, it is important to be aware that there are many cases where servers are infected with viruses, and there is a risk that confidential corporate data may be leaked. Furthermore, if a company holds customers’ personal information, it is essential to focus on security measures from the perspective of privacy protection and take steps to protect personal information. Security systems are required to be updated regularly as their performance has improved significantly.
Four points of data management
In order to carry out accurate data management, it is necessary to proceed with important points in mind. Let’s take a look at the details one by one.
1. Clarify the purpose of data utilization
Data management is a means to an end, not the end itself. By determining the purpose of data utilization, the data to be collected and the required quality can be determined, and the direction of utilization can be clarified. For this reason, it is important to clarify the purpose of use rather than just collecting data.
2. Visualize data
It is also important to understand the overall picture of the data and visualize it so that the necessary data can be used immediately. If you summarize the data format, storage location, usage method, etc. and convert it into a data map, it will be easier to manage the usage.
3. Discover data waste
By visualizing data, you may find waste, such as unnecessary data remaining or the same data being managed redundantly in multiple systems. Improving these wastes will make data management more efficient.
4. Establish a foundation that makes it easy to utilize data
Prepare your data infrastructure on a regular basis so that you can use the data immediately when you need it. Effective methods include storing it in a shared database or converting it with a BI tool. At this time, aim to create a system that allows the data to always reflect the latest information.
There are two types of data management automation methods.
Data management is very complex and cannot be performed manually. There are two methods for automating data management:
manual
In manual data management, we create a custom-made system from scratch for each company. The tasks involved include documenting the entire data management structure, designing the repository architecture, building data pipelines, applying data transformations, and monitoring, maintaining, and updating the system. Therefore, the required resources are very high.
Leverage existing platforms
Using an existing data management platform can reduce costs and enable early implementation. These include a drag-and-drop interface, connectivity between the platform and analytical tools, a dashboard with analytics results, online support, security management, and more. If you want to automate data management, we recommend using a platform rather than a manual.
Automated data management leads to increased operational efficiency
Following the flow introduced earlier, automating data management will lead to significant operational efficiency. In particular, efficiency can be expected in the following operations.
Accounting operations
Accounting work involves a lot of routine work, and since it involves handling money, there is no room for mistakes. Through automation, it can be used for inputting data on vouchers, creating forms, issuing invoices, etc. It enables highly accurate and high-speed business processing without human checking, and is one of the businesses for which the highest implementation effects can be expected.
Human resources operations
In human resources operations, automated tools are extremely useful when you want to perform objective and fair personnel evaluations. When human resources personnel evaluate personnel, it is difficult to completely eliminate subjective evaluations. However, by setting rules for evaluation standards and scoring employees’ abilities and aptitudes, it is possible to give evaluations that are in line with the rules. Furthermore, you will be able to experience the burden of human resources work, which will lead to more efficient personnel evaluations.
Sales operations
In sales operations, if customer information becomes individualized, it becomes impossible to build a common understanding of the customer within the company. By combining customer data that has been scattered throughout the company into one database, you can create an accurate customer list. By using this list, you will be able to centrally manage the progress of your customer service and take the most appropriate approach based on the customer’s behavior history.
Automating your data management provides the following benefits:
Improve operational efficiency
By automating boring tasks and allowing employees to focus on tasks that they find rewarding, they can concentrate on their work, as I introduced earlier. In addition, it is possible to reduce the time and burden required to deal with errors.
cost reduction
Automating data management also has the benefit of reducing various costs associated with business operations. By reducing unnecessary work and time, you can cut costs such as labor costs and man-hours. There are many other cost-cutting techniques, but if you try to do everything at once, it often doesn’t work. Implement them one by one, see the reactions, and find a method that suits your company.
Gaining consistency
Automated data management ensures that the tool performance environment is consistent and efficiently maintained. This reduces human error and further improves consistency.
Companies that feel that data management is not progressing are likely to continue using legacy systems. Legacy systems may not have the functionality required for modern data management and data utilization.
Continuing to use legacy systems increases the likelihood of encountering the “2025 cliff.” This will increase security risks and cause problems such as the inability to handle the huge amount of data due to the introduction of 5G. In order to overcome the cliff of 2025, we need to take action to promote DX by implementing data management.
summary
By utilizing data management, you can make the most of your data and use it to continuously maintain and evolve your business.
