THE IMPACT OF STRATEGIC PLANNING AND THE BALANCED SCORECARD METHODOLOGY ON MIDDLE MANAGERS' PERFORMANCE IN THE PUBLIC SECTOR
Bibliographic record
Abstract
The aim of this research is to study the impact of two strategic management systems, strategic planning and the Balanced Scorecard, on the performance and managerial competencies of middle managers working in the public sector. The two strategic management systems are both integrated in a business planning process and the organisation in question is the Defence Department of Canada. The research, supported by a questionnaire, identifies that strategic planning and the Balanced Scorecard are well implemented in the Canadian Defence Sector. Secondly, we discovered that the middle managers working for the Defence Department have the perception that the use of the two strategic management systems has a positive impact on their general performance and also on their managerial competencies. More precisely, we discovered that the competencies of managing change and organisational awareness are the most impacted by the use of the two strategic management systems. Finally, there is a correlation between the two strategic management systems. The more time a managers spends doing strategic planning, the more they are inclined to spend time doing balanced scorecard activities and believe that their performance is increased.
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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 | 0.012 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".