Skip to main content

Validation and backing (VN2)

The backing of the paradigm: the VN2 Inventory Planning Challenge (2025-2026), where the winning approach cut total cost by 13% versus the reference method.

Scope — VN2

VN2 is the VN2 Inventory Planning Challenge (2025-2026), an external international competition cited as validation of the paradigm — it is not a policy or a product module. See ESTRUCTURA.md §5.3.

What the VN2 Inventory Planning Challenge is​

The VN2 Inventory Planning Challenge (2025-2026) is an international inventory planning competition, organized independently of Directrix and AInventory. Participating teams receive real historical data and must produce replenishment plans; their results are evaluated against a reference method on the same dataset.

The VN2 is relevant to AInventory not as a product feature, but as external evidence that the predict-then-optimize + simulation paradigm outperforms traditional inventory formulas under real-world conditions.

The key result​

The winning approach in the competition reduced total cost by approximately 13% versus the reference method. That 13% does not come from fine-tuning parameters or a data advantage: it comes from a paradigm shift.

The most significant finding is not the exact figure, but its cause: no winning team used the classic safety stock formula (z · σ_d · √L). The top-performing teams converged on variants of the predict-then-optimize approach — generate scenarios of future demand, evaluate policies over those scenarios, and select by expected total cost minimization — which is exactly the paradigm AInventory implements.

Why VN2 is relevant evidence​

The standard objection to inventory optimization models is that they work well in theory but are fragile in practice: assumptions fail, data is noisy, planners do not trust black boxes. The VN2 addresses that objection directly:

  • Data is real, not synthetic.
  • Participants are independent teams, not the software vendor.
  • Evaluation is objective: total cost on the same dataset.

In that context, a 13% reduction versus a reference method — which typically includes classic safety stock formulas and fixed coverage — is evidence that the paradigm generates measurable value.

What VN2 does not imply​

The VN2 is an academic/professional competition with controlled conditions. Some limits of that evidence:

  • Results depend on the specific competition dataset; generalization to any industry or product category requires caution.
  • The 13% reduction is the result of the winning approach, not a typical expected result for any implementation.
  • AInventory implements the VN2 paradigm but with its own design decisions (four-level cascade, five policies, specific cost model). The VN2 figure supports the paradigm, not a particular implementation.
Position of the evidence

VN2 is an external reference validating the predict-then-optimize paradigm, not a certification of the AInventory product. Its value is showing that the technical direction is correct, not guaranteeing a 13% reduction in any specific case.