MétaCan
Menu
Back to cohort
Record W4221063729 · doi:10.1108/bpmj-10-2020-0459

Learning from sales and operations planning process implementation at ASTRO Inc.

2022· article· en· W4221063729 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBusiness Process Management Journal · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicQuality and Supply Management
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsMindsetContext (archaeology)Process managementProcess (computing)Sales and operations planningSoftware deploymentOrganizational cultureBusiness processComputer sciencePlan (archaeology)Knowledge managementBusinessOperations managementMarketingPerspective (graphical)ManagementWork in processEngineering

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.521
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.026
GPT teacher head0.289
Teacher spread0.263 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it