The Model-based Ecosystem committee of the IPX Congress seeks participants for a survey examining the impact of model-based approaches on Configuration Management (CM). The survey, consisting of 11 questions, aims to gather insights on risks and opportunities related to CM processes. Results will be shared on LinkedIn and the Future of CM Blog.
OpenAI’s release of GPT-4 enhances Large Language Models (LLMs) capabilities for impact analysis in configuration management. By leveraging LLMs, knowledge graphs can be utilized to reveal implicit relationships and support decision-making during changes. Upcoming tools, like NeoChat, hint at significant advancements in data exploration for engineers and managers.
The first The Future of CM newsletter of 2023 discusses the Circle of Competence, highlighting its importance in decision-making and change assessment in Configuration Management. It emphasizes the need for knowledgeable individuals during impact analysis, while addressing the Dunning-Kruger Effect, which leads to overestimation of one’s expertise. The CM Baseline aids in identifying relevant competencies and managing personnel changes effectively.
Prof. Dr. Jörg W. Fischer sparked a debate on the relevance of Form-Fit-Function (FFF), suggesting it is gradually losing significance. FFF’s misuse and complexity in modern systems necessitate a cross-functional approach for effective impact assessments. While FFF remains valuable, its application must adapt to evolving requirements and increased complexity in product design.
This article introduces a series on mental models for preventing ethical fading in Configuration Management. It focuses on the compounding effect of changes, highlighting how decisions can have cumulative positive or negative impacts over time. Understanding dependencies and risks is essential for facilitating beneficial outcomes and avoiding detrimental compounding effects.
Organizing data within organizations enhances efficiency, flexibility, and agility. A well-structured system facilitates collaboration among groups, while improper alignment can create inefficiencies. The article proposes a model comprising network nodes, datasets, and relationships to streamline information organization, ensuring clarity and integrity during change assessments. An effective structure leads to improved interactions.
The CM Baseline is essential in the CM2 Model, providing accurate configuration data and insights into changes over time. It enhances impact analysis across various domains, aids scenario-based assessments, determines optimal change introduction dates, supports what-if analyses for disturbances, and examines commonality from multiple perspectives, ultimately improving decision-making and minimizing risks.
I joined Thom Singer and Craig Brown for a second time on the Digital Enterprise Society Podcast. I talk about the Future of Configuration Management. Topics like the CM2 Baseline, Machine Learning and Software over-the-air updates were discussed.
This article continues the CM Baseline series by discussing ‘Change Dependencies,’ the third component. It outlines the types of dependencies—logical, preferential, and resource—that affect the sequence of implementing changes. Understanding these dependencies aids project management by providing a clear roadmap for navigating the implementation phase and optimizing change processes.
The article discusses managing changes in the CM Baseline series using analogies related to flights. It introduces the Impact Matrix as a critical component that captures the intentions behind changes, detailing affected objects and relationships. The post emphasizes the significance of effective visualization and analysis for collaborative decision-making in change management.
