The “Kaisha Shikiho: Industry Map” source of information on issues in DX and an example of business analysis in the manufacturing industry.
Kaisha Shikiho: Industry Map” as a source of information on specific issues in DX
Sources of information on specific challenges in digital transformation (DX) include:
1. News Articles and Industry Reports: Keeping up with the latest news and industry reports related to DX helps in understanding the issues faced by companies and industries, along with examples of initiatives. Sources like ITmedia, Nikkei BP, and BCN Ranking provide valuable information on this topic.
2. Corporate Websites and Investor Relations (IR) Information: Corporate websites and IR information offer insights into the challenges faced by companies, their approach to DX, and specific examples of their DX initiatives. Major IT companies such as Microsoft, Google, and Amazon have publicly shared their stance on DX.
3. Seminars and Conferences: Attending seminars and conferences on DX allows one to learn about the latest trends and issues. Additionally, interacting with peers in the same industry or field can provide ideas and hints for DX. Examples of such events include Japan IT Week, Interop Tokyo, and CEATEC JAPAN.
4. Specialized Books and Papers: Reading specialized books and papers on DX offers in-depth knowledge and specific solutions to problems. Notable examples include “DX Compendium” (Shoei-sha), “Digital Transformation Strategy Theory” (Nikkei Publishing Inc.), and “Digital Transformation at Scale” (MIT Press).
“Kaisha Shikiho: Sangyo Chizu” is a specialized issue of the corporate information magazine Kaisha Shikiho, published by Nihon Keizai Shimbun, Inc. Released annually in March and September, it is available for purchase at bookstores and online for several thousand yen per copy. This publication serves as an analytical map, providing a comprehensive overview of market trends and company performance evaluations by industry.
The special issue offers detailed insights into the market size and share of each industry, sales and profit margins of leading companies, as well as the latest industry trends and challenges. It also highlights various companies' unique characteristics, strengths, and competitive landscapes, making it an invaluable resource for investors and corporate strategists.
Covering 174 industries and 4,000 companies, it meticulously illustrates industry-specific information and trends. For example, it presents:
Within these analyses, issues for each industry and company are thoroughly examined. When considering digital transformation (DX), specific issues can be identified by extracting challenges faced by companies within similar business categories and generalizing these issues for industries within specific domains.
This information serves as a foundation for conducting further detailed analysis using general issue analysis methods such as SWOT analysis, PEST analysis, Porter’s Five Forces analysis, and the KJ method. These methods allow for the quantification of KPIs, KGIs, and OKRs as target values, using quantification methods detailed in “Methods for Clarifying Issues.”
To address these challenges, advanced technologies such as machine learning, artificial intelligence, and ICT are employed. Through these analyses and technological implementations, problems are systematically resolved, driving successful digital transformation initiatives.
- SWOT Analysis: is a method to analyze a company’s strengths, weaknesses, opportunities, and threats. Analysis
- PEST analysis: is a method of analyzing the impact of DX on companies by focusing on the four factors of politics, economy, society, and technology. Porter’s Five Competitiveness Analysis
- Porter’s Five Competitive Analysis: Porter’s Five Competitive Analysis is a method for analyzing the competitive environment of an industry, which analyzes the competitive situation within the industry, barriers to entry, existence of substitutes, bargaining power of customers, and bargaining power of suppliers. The DX issue analysis will analyze how competitive relationships within an industry and barriers to entry change as a result of DX, and how the existence of substitutes may change as a result of DX.
- KJ method: is a method for organizing complex problems and coming up with solutions, by organizing the results of brainstorming, the essence of the problem can be clarified and solutions can be derived. ideas for solutions.
Kaisha Shikiho: Sangyo Chizu” can be one of the easily usable information sources for such analysis.
Specific Business Analysis Steps
The general steps of the business analysis are as follows
Definition of Purpose and Scope: Define the purpose and scope of the business analysis. Specifically, define what is to be analyzed, what problems are to be solved, and who is to be involved. Refer to “Problem Solving Methods, Thinking Processes, and Experimental Designs” for more information on extracting and quantifying the solutions to these problems. For example, the manufacturing industry is facing the following labor-saving and personnel issues, which require measures to solve them.
Understand the business process: To understand the business process, it is essential to delve into the specifics of the process under consideration and document its purpose, flow, procedures, stakeholders, and risks. This step involves gathering, organizing, and analyzing detailed information about the business process.
Taking the manufacturing industry as an example, we can consider a before/after workflow to illustrate the potential improvements. In the current workflow, inefficiencies due to manual labor and rework are prevalent, leading to wasted man-hours. By identifying these inefficiencies, we can anticipate a significant reduction in man-hours through process optimization. The expected improvements can be depicted as follows:
Before Workflow:
- Manual data entry
- Repetitive tasks prone to human error
- Frequent rework due to inaccuracies
- High reliance on paper-based documentation
After Workflow:
- Automated data entry using digital tools
- Streamlined tasks with minimal human intervention
- Reduced rework through enhanced accuracy
- Transition to digital documentation and real-time data access
By documenting and analyzing these changes, stakeholders can better understand the impact of digital transformation on the manufacturing process, leading to more efficient operations and significant time savings.
Proposed Solution
To address the identified problems, propose a solution that encompasses process, technical, and organizational improvements. The solution should target the root cause of the issues. In this context, integrating AI technology with advanced search capabilities is recommended. This includes utilizing “Artificial Intelligence Technology” from the domain of “Natural Language Processing Technology” and “Machine Learning Technology” detailed in “Theory and Implementation of Topic Models.” Additionally, reference the various examples provided in “Artificial Intelligence Technology as a Case Study for DX” to guide the solution design.
Prototype Implementation
Develop a comprehensive implementation plan for the proposed solution. This plan should outline:
- Responsibilities: Identify who will be responsible for each aspect of the implementation.
- Deadlines: Set clear timelines for each phase of the project.
- Resources Needed: Determine the necessary human, technological, and financial resources.
- Budget: Allocate a detailed budget for the implementation.
- Evaluation Methods: Define specific metrics and methodologies for evaluating the solution’s effectiveness.
Leveraging AI and search technologies, the specifications, budget, and evaluation methods should be precisely defined. Implement these using programming technologies such as Python and machine learning frameworks as described in “Python and Machine Learning.”
Monitoring of Results
After implementation, closely monitor the results to ensure no unforeseen issues arise. If monitoring reveals that improvements or adjustments are needed, take appropriate action promptly. Should the business analysis outcomes align with initial expectations, proceed to build a production system using advanced IT infrastructure technologies like cloud computing and DevOps, as outlined in “IT Infrastructure Technology.” This ensures scalability, reliability, and continuous improvement of the implemented solution.
