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Virtual Stock, Real Constraints: Production-Grade Supply Chain Visibility Between Two Incompatible ERPs, Without Breaking Either

Duygu Unlu

Abstract

When a major automotive OEM asked a Tier-1 supplier for near-real-time fulfillment visibility by assembly plant, the challenge was not data transport but model alignment. The supplier's ERP could accurately report total available stock, yet that answer was insufficient for the customer's real question: which plant requirements were covered, which were exposed, and where a shortage would hit first. Reconfiguring the supplier's core planning model around a single customer perspective was not operationally viable, so a virtual allocation layer was designed instead.

This paper presents the architecture and production design of that solution: a virtual allocation engine that recalculated from scratch every 30 minutes, handled three distinct inventory scenarios, applied a tie-breaking cascade for shortage cases, and published a plant-level fulfillment view to the customer. To make the design usable in live operations, it was supported by parametric rules, supplier-side visibility that helped prevent misallocation between runs, and manual exception handling.

The paper argues that the hardest integration problems are often modeling problems rather than connectivity problems. It also shows that edge cases are part of the design, not implementation detail: when identified before building, they are boundary conditions; when discovered afterwards, they become incidents.

Published in
Proceedings of the Raptors Conference, Vol. 1 (2026)
Conference
Raptors Conference 2026, 21 October 2026, online
Accepted
2026-09-16
DOI
https://doi.org/10.68495/rc.2026.C018
Presentation
Slides (PDF)
Licence
© 2026Duygu Unlu. Published under Creative Commons Attribution 4.0 International (CC BY 4.0).
Publisher
Hackathon Raptors, Community Interest Company 15557917, London, United Kingdom
Permanent address
https://proceedings.raptors.dev/unlu-virtual-stock-real-constraints

Open access. Every entry in the Proceedings is free to read, with no charge to authors and no charge to readers. Slides are served from this site, so they stay available at the paper's permanent address.

Cite this paper

Duygu Unlu (2026). Virtual Stock, Real Constraints: Production-Grade Supply Chain Visibility Between Two Incompatible ERPs, Without Breaking Either. Proceedings of the Raptors Conference, Vol. 1 (2026). Hackathon Raptors, London. https://doi.org/10.68495/rc.2026.C018

@inproceedings{raptors2026-c018,
  title     = {{Virtual Stock, Real Constraints: Production-Grade Supply Chain Visibility Between Two Incompatible ERPs, Without Breaking Either}},
  author    = {Unlu, Duygu},
  booktitle = {Proceedings of the Raptors Conference},
  volume    = {1},
  year      = {2026},
  publisher = {Hackathon Raptors},
  address   = {London, United Kingdom},
  doi       = {10.68495/rc.2026.C018},
  url       = {https://doi.org/10.68495/rc.2026.C018},
  abstract  = {When a major automotive OEM asked a Tier-1 supplier for near-real-time fulfillment visibility by assembly plant, the challenge was not data transport but model alignment. The supplier's ERP could accurately report total available stock, yet that answer was insufficient for the customer's real question: which plant requirements were covered, which were exposed, and where a shortage would hit first. Reconfiguring the supplier's core planning model around a single customer perspective was not operationally viable, so a virtual allocation layer was designed instead. This paper presents the architecture and production design of that solution: a virtual allocation engine that recalculated from scratch every 30 minutes, handled three distinct inventory scenarios, applied a tie-breaking cascade for shortage cases, and published a plant-level fulfillment view to the customer. To make the design usable in live operations, it was supported by parametric rules, supplier-side visibility that helped prevent misallocation between runs, and manual exception handling. The paper argues that the hardest integration problems are often modeling problems rather than connectivity problems. It also shows that edge cases are part of the design, not implementation detail: when identified before building, they are boundary conditions; when discovered afterwards, they become incidents.}
}
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DO  - 10.68495/rc.2026.C018
UR  - https://doi.org/10.68495/rc.2026.C018
AB  - When a major automotive OEM asked a Tier-1 supplier for near-real-time fulfillment visibility by assembly plant, the challenge was not data transport but model alignment. The supplier's ERP could accurately report total available stock, yet that answer was insufficient for the customer's real question: which plant requirements were covered, which were exposed, and where a shortage would hit first. Reconfiguring the supplier's core planning model around a single customer perspective was not operationally viable, so a virtual allocation layer was designed instead. This paper presents the architecture and production design of that solution: a virtual allocation engine that recalculated from scratch every 30 minutes, handled three distinct inventory scenarios, applied a tie-breaking cascade for shortage cases, and published a plant-level fulfillment view to the customer. To make the design usable in live operations, it was supported by parametric rules, supplier-side visibility that helped prevent misallocation between runs, and manual exception handling. The paper argues that the hardest integration problems are often modeling problems rather than connectivity problems. It also shows that edge cases are part of the design, not implementation detail: when identified before building, they are boundary conditions; when discovered afterwards, they become incidents.
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