How VYAN decides.
13 capabilities · 3 sub-themes
The deciding layer. Every dimension that matters — demand, supply, inventory, finance, allocation, scheduling — gets resolved in one math object against a single dollarized objective. The Decision Policy becomes a first-class governed artifact, not a buried setting. This is what changes operationally in months three through nine.
One math object4
Concurrent Multi-Horizon Planning
Strategic, tactical, operational, and execution planning run in separate systems on different cycles, exchanging data through reconciliation processes that lose detail and lag reality.
Read card →Multi-Objective Trade-Off Optimization
Trade-offs between revenue, margin, capital, and service get negotiated rather than optimized. Each function brings its own model; the compromise lands in the middle, not at the value-maximizing point…
Read card →Working-Capital-Constrained Planning
Working capital targets are imposed top-down after planning runs. The CFO declares the total too high; the cut lands clumsily across Stock Keeping Units (SKUs) and locations that didn’t need it equall…
Read card →Resilient-EVA Objective Function
Plans optimized to expected outcomes hide the variance they're carrying. The plan that looks best on average is often the same one that blows up worst when variance hits. Risk is priced after the fact…
Read card →Policy as a first-class artifact3
Policy-Driven Autonomy and Governance
Planning systems are all-manual (planner bottleneck) or all-auto (control lost). The middle ground — auto for safe decisions, human for material ones — requires policy infrastructure traditional Advan…
Read card →Decision Lineage and Explainability
Optimization outputs are black boxes. Planners can't see why a decision was made; trust degrades; overrides multiply; Return on Investment (ROI) collapses to the percentage of decisions that survive r…
Read card →Champion-Challenger Policy Improvement
Planning policy changes are deployed as cutovers. If the new policy degrades performance, rollback costs cycles. There's no infrastructure to test against the current policy without committing.
Read card →Decisions at the line6
Continuous Capable-to-Promise
Order promising answers commit questions by checking allocated supply tables. It doesn't verify the production, transport, and inventory chain behind the commit is actually feasible. Sales commits dat…
Read card →Demand-Supply Matching with Commercial Segmentation
Allocation and pegging logic is buried in master data and code that nobody fully understands. Premium customers get backordered while their orders peg to delayed supply; commodity orders consume safet…
Read card →Order Backlog Optimization
When demand exceeds supply, the order book sits in receipt-date sequence. The first orders in get supply; high-margin or strategic-customer orders that arrived later don't. The default is fair, not op…
Read card →Supply-Aware Revenue Management
Pricing, promotion, and channel decisions are made in revenue management without visibility into supply state. Promotions launch into shortage; price cuts apply to inventory that’s about to sell at fu…
Read card →Finite-Capacity Production Scheduling
MRP releases work the plant can't actually run. The schedule that comes out of planning is feasible on paper and infeasible on the floor. Schedulers spend their days reconciling between planning and e…
Read card →Sequencing and Changeover Optimization
Production schedules treat every operation as though it cost the same to start regardless of what ran before. In reality, every changeover carries setup time, scrap, and energy cost — and that cost de…
Read card →See how decides lands in your own enterprise.
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