Feedforward Prepositioning Plan¶
Planning artifact — instantiates Reference Tracking Bandwidth Alignment
Stages capacity, stock, or configuration ahead of forecast reference movement so the loop begins each change already closer to the new target.
A Feedforward Prepositioning Plan spends effort before the reference moves so the loop has less distance to close after it moves. Where ordinary feedback waits for error to appear and then chases it, this artifact reads a forecast of where the reference is heading and physically relocates the resources — people, stock, standby capacity, warm configuration — to where they will be needed, on the schedule at which they will be needed. Its defining idea is that the fix is logistical and committed in advance: the plan is a concrete pre-deployment written against a forecast, so that when the demanded change arrives the loop's starting error is already small and its remaining correction fits inside the bandwidth it actually has.
Example¶
A ride-hailing platform knows, from the venue calendar, that a 20,000-seat arena empties around 10:15 p.m. on concert nights and that surge-driven feedback dispatch always lags the wall of riders that materialises in ninety seconds. The Prepositioning Plan is built the afternoon before: it reads the event forecast (start time, expected egress curve, historical pickup geography), then pre-commits — driver incentives to stage in a specific three-block staging zone by 10:00, a temporary pickup lane coordinated with the venue, and surge caps pre-loaded so the price signal does not overshoot. Setup to outcome: instead of the loop discovering demand at 10:15 and spending twenty minutes pulling cars across the city, roughly 200 drivers are already parked adjacent to the doors when they open. The post-event wait time that normally spikes to eleven minutes settles near three. Nothing about the dispatch feedback loop got faster; the plan simply moved its starting point.
How it works¶
The plan converts a forecast into pre-positioned state through three deliberate steps. First it identifies which reference movements are predictable enough to act on early — recurring, calendared, or leading-indicator-driven — and ignores the rest. Second, for each, it computes the pre-deployment: what to move, how much, to where, and by when, sized so the residual post-arrival correction is within loop bandwidth. Third, it writes the commitment as a dated artifact with a fallback if the forecast misses. Crucially it is open-loop: the plan acts on the prediction, not on measured error, so its whole value depends on the forecast being right and its whole risk is being wrong.
Tuning parameters¶
- Forecast horizon — how far ahead the plan commits. Longer buys more preparation time but leans on a shakier prediction.
- Prepositioning fraction — what share of expected need is staged in advance versus held back for feedback. More upfront cuts lag but strands resources if demand shifts.
- Trigger confidence — the forecast certainty required before committing resources. Higher avoids wasted moves; lower prepositions more aggressively.
- Reversibility — how cheaply a pre-deployed resource can be recalled if the forecast misses. Cheap-to-recall lets you preposition boldly; sunk moves demand caution.
- Coverage breadth — how many predictable movements the plan covers versus concentrating on the few highest-value ones.
When it helps, and when it misleads¶
Its strength is that it defeats lag structurally on any movement you can see coming, without needing to make the loop itself faster — the essence of feedforward control layered ahead of feedback. It shines exactly where feedback is hopeless: reference jumps that are large, sharp, and predictable.
Its failure mode is the failure mode of all open-loop action — it commits to a forecast, and a wrong forecast means resources sit in the wrong place while the real demand goes unserved and the feedback loop, now depleted, tracks worse than if the plan had never run. Overreacting to a noisy or amplified forecast produces the classic bullwhip effect, where each planning layer stages against the last one's overreaction and swings widen upstream.[n1] The guarding discipline is to keep a feedback reserve the plan never pre-commits, and to size prepositioning to forecast confidence, not forecast hope — the plan should degrade gracefully to ordinary feedback when the prediction proves wrong.
How it implements the components¶
feedforward_forecast_channel— the plan is the acting end of the forecast channel: it turns a prediction of reference movement into committed pre-deployment before error appears.bandwidth_bottleneck_intervention— by staging resources at the point of demand, it relieves the coordination/positioning bottleneck exactly when the movement lands, effectively widening usable bandwidth at that moment.reference_cadence_profile— it depends on and encodes the predictable cadence (calendared spikes, egress curves) that make a movement worth prepositioning against.
It does NOT implement effective_loop_bandwidth_estimate or stability_and_safety_guardrail — the online, per-cycle re-optimisation against a loop model belongs to Model-Predictive Tracking Window, its nearest anticipation twin; nor reference_change_control_contract, the advance-notice protocol owned by Lead-Time Change Notice. This plan moves resources; it does not recompute control actions or issue the notice.
Related¶
- Instantiates: Reference Tracking Bandwidth Alignment — supplies the anticipation-by-pre-deployment branch of the archetype's intervention menu.
- Consumes: Lead-Time Change Notice — an advance notice of a reference change is often the forecast the plan positions against.
- Sibling mechanisms: Model-Predictive Tracking Window · Lead-Time Change Notice · Staged Setpoint Ramp · Priority-Band Triage Rule
Editorial Notes¶
Form Classification¶
Form family: Representation, Specification & Plan
Rationale: Feedforward Prepositioning Plan operates as a non-executable information artifact that externalizes static or prospective structure because it stages capacity, stock, or configuration ahead of forecast reference movement so the loop begins each change already closer to the new target.
Independent corroboration: The frozen evidence defines Feedforward Prepositioning Plan as 'Stages capacity, stock, or configuration ahead of forecast reference movement so the loop begins each change already closer to the new target', so its operative form is Representation, Specification & Plan.
Nearest alternative: Analysis, Modeling & Optimization — The plan externalizes dated pre-deployment commitments and fallback actions; forecast sizing computations are prepared upstream.
Review outcome: Independent reviewer agreement; medium confidence.
Origin Attribution¶
Primary origin: Logistics & Supply Chain Management
Origin pattern: Cross-disciplinary synthesis
Present-day reach: Multi-domain
Rationale: Staging capacity or stock ahead of forecast demand is a logistics and supply-chain planning technique.
Related originating lineages:
- Engineering & Design — Feedforward control supplies the reference-tracking interpretation used here.
- Military & Strategic Studies — Military forward supply and prepositioning materially shaped anticipatory staging practice.
- Operations Research — Forecasting and allocation models formalize quantities, locations, and timing.
- Systems Thinking & Cybernetics — Feedforward control supplies the rationale for acting before the reference error appears.
Review resolution: Both reviewers agree that logistics_supply_chain is primary. I retain military_strategic_studies, engineering_design, operations_research, systems_cybernetics only as formative origin lineage(s), without treating every later application as an origin. cross_disciplinary_synthesis is appropriate because the exact artifact combines contributions from multiple professional lineages. Reach is multi_domain as a separate applicability judgment: it does not widen or narrow the recorded provenance. Encyclopedia synthesis is true because the exact generalized artifact is an encyclopedia-authored combination or refinement. The secondary differences are reconciled with no unresolved primary-provenance ambiguity.
Encyclopedia synthesis: The exact catalogued form synthesizes established practice rather than reproducing a single standard historical label.
Review outcome: Reconciled after independent review; high confidence.
Notes¶
[n1] Bullwhip effect — the well-documented amplification of demand variability as it propagates up a supply chain, as each stage reacts to (and over-orders against) the noisy signal from the stage below. It is the canonical warning for any feedforward scheme: prepositioning against an amplified or noisy forecast makes swings worse, not smaller. ↩