Information Value Chain Analysis

Information Value Chain Analysis involves mapping relationships between two sets of elements, typically represented in matrices. Most data relationship matrices focus on CRUD (Create, Read, Update, Delete) functions.

Historical Context

This technique was developed in the early 1980s for IBM’s business systems planning (BSP) and later integrated into James Martin’s information engineering methodology during the information systems planning (ISP) phase. It remains a critical component of enterprise architecture.

Key Concepts

The technique was renamed after Michael Porter’s Business Value Chain concept, illustrating direct contributing functions sequenced from left to right. Indirect functions provide support from above or below.

Element Sequencing

The elements are sequenced using the Business Value Chain, creating a familiar and intuitive layout. This analysis incorporates both functions and subject areas, utilizing both X (horizontal) and Y (vertical) axes.

Data/Process CRUD Matrices

These matrices provide different levels of detail, including:

• Subject areas and business functions
• Business entities linked to functions or processes
• Data attributes associated with processes and their information products

Additional CRUD Matrices

There are other potentially useful CRUD matrices, such as:

• Data/Organization CRUD Matrix: identifies who is responsible for data
• Data/Role CRUD Matrix: highlights responsibilities by role
• Data/Location CRUD Matrix: illustrates where data is stored
• Data/Application System CRUD Matrix: shows where data is managed

Affinity Analysis

Affinity analysis involves sorting one or both axes to group related processes and subject areas/entities together.

Affinity analysis

Importance of Value Chain Analysis

This analysis is essential for several reasons:

• It aligns with process models.
• It helps validate the data model.
• It enhances the understanding of data sources.
• It aids in analyzing data quality issues.
• It facilitates change impact analysis.
• It assists in defining information products.