Developments in Practice XXXIV: Application Portfolio Management
Bibliographic record
Abstract
APM is the ongoing management process of categorization, assessment and rationalization of the IT application portfolio which allows organizations to identify which applications to maintain, invest in, replace, or retire. To understand current APM strategies and practices, the authors convened a focus group of senior IT managers from a number of organizations. Results of the focus group discussion pointed to the need to develop three inter-related APM capabilities: (1) strategy and governance, (2) inventory management, and (3) reporting and rationalization. To deliver value with APM, organizations must establish all three capabilities. Experience suggests that organizations tend to start by inventorying applications and work from the “middle out” to refine their APM strategy (and how it is governed) as well as to establish efforts to rationalize their applications portfolio. As such, APM represents a process of continual refinement. Fortunately, experience also suggests that there are real benefits to be reaped from the successful development of each capability. The paper concludes with some lessons learned based on the collective experience of the members of the focus group.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.016 | 0.010 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.028 | 0.008 |
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".