Learning from sales and operations planning process implementation at ASTRO Inc.
Bibliographic record
Abstract
Purpose The purpose of this case study is to develop a complete understanding of the sales and operations planning (S&OP) process implementation effort at ASTRO Inc. and to determine the influential factors that led to its success, the interrelationship between them, as well as the level of influence of each factor compared to their counterparts. As we trace the evolution of S&OP in the organizational context, the view that its implementation leads to a positive impact in changing the way companies do business is not in itself novel. To date, there is limited academic investigation on how and why the S&OP process implementation leads to a successful organizational transformation. Design/methodology/approach The data used in this case study were collected through semi-structured interviews with selected employees and through documentary analyses based on the archives at ASTRO Inc., a large North American company, for the period from 2016 to 2018. The paper adopts a methodology based on a retrospective study and interviews. Findings The analysis shows that the S&OP process design and its implementation required efforts on many distinct but complementary fronts to be successful. However, the level of influence varies across the organizational enablers that contribute to this success. Its successful implementation is fundamentally dependent on the managers' ability to create mindset changes in the organizational culture, and to plan and coordinate the S&OP process deployment. The key enablers need to be skillfully combined, taking into account the contextual variables, namely, the company's internal context, the company's external context and the specific characteristics of the industry in which the company belongs. Originality/value The current study provides a better understanding of the implementation of the S&OP process and highlights the key enablers that led to its successful implementation. It provides practical managerial guidelines for designing, deploying and using an S&OP process in response to and in anticipation of customer demands, and competitive pressures.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".