The 5 C Challenges of Business-Driven IT Management and the 5 A Approaches to Addressing Them
Bibliographic record
Abstract
To summarize to business people the main challenges of business-driven information and communication technology (ICT) systems management, we suggest "the 5 C challenges of ICT systems management": 1) cost-benefit relationship, 2) complexity, 3) conformance to higher-level objectives, 4) circumstances and their diversity, and 5) change. We also advocate the slogan "To address the 5 C challenges you need at least the 5 A approaches and a compromise." Here, the "5 As" are the main approaches for addressing the "5 Cs": 1) analysis of benefits and costs, 2) automation of management activities, 3) aims (objectives, policy) modeling and processing, 4) accommodation of different circumstances through customization and context-sensitivity, and 5) adaptability. We also discuss how these 5 Cs and 5 As relate to self-management, policy-based management, and contract-based management and how they can be used for presenting a new project on modeling and using business value information.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.006 | 0.024 |
| Scholarly communication | 0.026 | 0.019 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.011 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".