Instituting a company‐wide strategic conversation at Procter & Gamble
Bibliographic record
Abstract
Purpose The paper aims to explain how Procter & Gamble's new strategy review meeting structure and new inquiry culture established a new norm for communication between leaders and their teams throughout the organization. Design/methodology/approach The authors, one a former P&G CEO and the other a long‐time consultant to the firm, describe how the firm instituted a robust process for creating, reviewing and communicating about strategy. Findings The P&G process was designed to open a dialog between top management and the leaders of each business to discuss five strategic choices. What is your winning aspiration? Where will you play? How will you win? What capabilities must be in place? What management systems are required? Practical implications At P&G the Objectives, Goals, Strategy, Measures (OGSM) statement for a brand, category, or company was the framework for articulating a clear and explicit expression of where to play and how to win, choices that connected with the aspirations of the business and the measures of success indicated. Originality/value The paper explains the learning and communication techniques P&G used to foster an authentic, effective company‐wide dialog about strategy.
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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 | 0.019 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.009 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".