An inventory and AOG dashboard for leadership should answer a few core questions: where are we exposed today, what is stuck, what is trending the wrong way, and who owns fixing it. The intent is not to show every data point, but to surface risk to fleet availability, safety‑critical parts, and customer commitments. In regulated environments, this means balancing operational visibility with traceability and data quality constraints from MRO, ERP, and maintenance systems. The dashboard should summarize, not replace, the underlying maintenance, planning, and quality records that remain the system of record. It must also be designed so that changes in logic and thresholds are controlled through formal change management and, where applicable, validation.
The first view leadership usually needs is current AOG exposure and impact on fleets and customers. This typically includes the number of active AOG events, segmented by fleet, operator, or site, and the aircraft or asset hours or cycles currently lost. Where data supports it, a simple classification of AOG events by severity or operational impact can help prioritize attention, but these definitions must be clearly documented. It is also useful to show how many AOGs are driven primarily by parts unavailability versus maintenance, engineering, or documentation issues. In brownfield environments, some of this data will be incomplete or delayed, so the dashboard must make those gaps explicit rather than hiding them behind rolled‑up metrics.
Leadership needs to see how long AOG events remain open and how performance compares to internal or contractual targets. A simple aging breakdown (for example, 0–8 hours, 8–24 hours, 1–3 days, over 3 days) gives a quick view of where the system is stuck. Displaying average and percentile resolution times over recent weeks or months can help distinguish chronic structural issues from short‑term spikes. If service level targets exist, the dashboard can show how many events met or missed them, but should not imply contractual compliance without reference to the authoritative systems and agreements. Any time‑based metric must be backed by clear, traceable time stamps from the maintenance and logistics systems, with known issues in clock accuracy or event closure practices called out.
For inventory, leadership needs visibility into parts that are actively constraining operations or are about to. The dashboard should highlight shortages and stockouts for AOG‑relevant and safety‑critical parts, with counts of aircraft or assets impacted or at risk. It is helpful to distinguish between true unavailability (no stock and no confirmed replenishment) and logistics constraints (stock exists but cannot be moved in time), as they have different owners and remediation paths. Forward‑looking indicators such as projected days until stockout for high‑risk items can add value but are highly sensitive to planning data quality and forecast assumptions. Because many plants operate with fragmented ERP, MRO, and warehouse systems, the dashboard should be clear about which locations and stock types it covers and where blind spots exist.
AOG and inventory risk is often driven less by on‑hand stock and more by the health of the replenishment and repair pipeline. A leadership dashboard should show open backorders for critical parts, segmented by supplier, repair station, or internal shop, and by promised versus actual lead time. Visibility into the repair pipeline—for example, units in inspection, in repair, awaiting parts, or pending test—helps differentiate supplier performance issues from internal capacity or planning constraints. Where available, simple indicators of supplier performance trends for AOG‑relevant items can be useful, but they must be treated as directional and validated against detailed procurement data before being used in formal performance reviews. Partial integrations and manual status updates are common; the dashboard should not present estimated repair or delivery dates as guaranteed outcomes.
Leadership often needs to know not only what is broken, but what mitigations are in place or failing. The dashboard can show how many AOGs have active workarounds, such as part swaps, temporary spares, or aircraft substitutions, and whether these are increasing risk elsewhere. For inventory, it is useful to surface reliance on last‑minute expedites, cannibalization, or frequent part transfers between sites, as these are signs of systemic planning or stocking issues. However, these metrics depend heavily on accurate and timely recording of swaps, deviations, and concessions in the maintenance and quality systems. If current data capture does not support reliable measurement, the dashboard should avoid detailed counts and instead flag the absence of robust mitigation tracking as a risk in itself.
Any executive dashboard in a regulated environment must make data lineage and quality limits visible. For inventory and AOG, this means clearly indicating which systems are the source of record for status, quantities, and event timing, and where manual data entry or spreadsheets are still in use. The dashboard should be able to trace each aggregated figure back to underlying records so that investigations, audits, and root cause analyses can be supported. Logic for classifying events as AOG, safety‑critical, or customer‑impacting must be documented, version‑controlled, and aligned with existing procedures and approvals. Changing thresholds or definitions should go through change control and, where the dashboard feeds operational decisions, through appropriate validation to avoid unintended regulatory or safety implications.
In practice, an AOG and inventory dashboard will sit on top of existing MRO, MES, ERP, and logistics tools rather than replacing them. Many aerospace and other regulated operations use older or heavily customized systems where changes are costly and constrained by qualification or validation requirements. The dashboard should therefore be designed as a read‑only or minimally invasive layer that aggregates and presents data without disrupting established transaction flows. Attempting to replace or deeply re‑engineer core inventory or maintenance systems just to feed a new dashboard often fails due to downtime risk, integration complexity, and the need to re‑validate end‑to‑end processes. A pragmatic approach is to start with a narrowly scoped dashboard, validate its data with users, and then expand coverage and automation as integration quality and trust improve.
A leadership dashboard is only useful if it supports clear ownership and timely action. Each major metric—such as AOG count, average resolution time, critical part stockouts, and open backorders—should have an understood owner and escalation path. The dashboard should make it easy to drill down into sites, fleets, suppliers, or part families so that issues can be assigned quickly, but this drill‑down depends entirely on how well data is structured in the upstream systems. Governance around refresh frequency, incident review routines, and how dashboard data is used in performance discussions helps prevent disputes over which numbers are authoritative. Over time, lessons from recurring AOG and inventory issues surfaced in the dashboard can be fed into continuous improvement, but not without disciplined defect logging, root cause analysis, and change control.
Whether you're managing 1 site or 100, Connect 981 adapts to your environment and scales with your needs—without the complexity of traditional systems.
Whether you're managing 1 site or 100, C-981 adapts to your environment and scales with your needs—without the complexity of traditional systems.
