Product Portfolio Management with Production Flexibility in Agribusiness
Bibliographic record
Abstract
The acquisition of production flexibility is a well-documented strategy pursued by many firms to counteract certain operational constraints. However, these flexibilities can increase the complexity of a production system and the difficulties in managing increased complexity may hinder exploiting the full benefit of flexibility. In this paper, we consider one such flexibility paradox at an agribusiness firm for an annual $800 million production decision: The firm produces a number of products (hybrid seeds) using limited inventories of several raw materials (parent seeds) and a production process that is subject to random variations. To handle the raw material availability constraint and to partially mitigate the supply risk, the firm invests in a costly second production in South America that can be used if the yield in the first production in North America is low. We solve this joint problem of raw material allocation and sequential production by reformulating it as a tractable simultaneous optimization problem. This tractable reformulation provides an exact solution in practical time durations for large assortments of products. We also establish that when profit margins are sufficiently high, sequential production has less cost, on average, than single production. The solution developed is in use at the firm and has led to an estimated increase in profit by 2%–3% annually.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".