What we solve

The symptom

The schedule is confidently published, then quietly overridden by expediting, verbal reprioritisation, and the judgement of a few experienced people. Promised dates and the real state of work steadily diverge, and no one can say with confidence what is actually achievable this week.

Why it matters commercially

Unreliable dates erode customer trust, trigger firefighting and overtime, and make it hard to commit to new work without padding every quote. Decisions get made on stale information, so capacity is both over-promised and under-used at the same time.

What must be proven

That a governed operational model can reconcile the incumbent schedule with real constraints and produce options a planner trusts — on your own representative jobs, not a generic demo.

Intervention options

1. Make the current sources of scheduling truth explicit and agree which one is authoritative.
2. Prove, on bounded and calibrated data, that better-sequenced options can be generated and reviewed.
3. Design a governed loop where a planner approves, adjusts, or overrides each proposed change.

What success would be measured against

What you would measure: the gap between promised and achieved dates, the share of jobs resequenced reactively, and how confidently planners can commit to a date — baselined before any change and reviewed against that baseline.

The symptom

The same quantity reads differently in the ERP, the shop-floor system, and someone’s spreadsheet. Meetings start by arguing about whose figure is right instead of what to do, and reports are quietly reconciled by hand before anyone will act on them.

Why it matters commercially

When people do not trust the numbers, they hedge: extra buffers, duplicate records, and slow, defensive decisions. Investment cases and delivery commitments rest on figures no one fully stands behind, which is a poor foundation for any operational decision.

What must be proven

That a shared operational model can sit over the incumbent systems, reconcile the values that matter for a decision, and surface disagreements openly rather than hiding them.

Intervention options

1. Identify the handful of figures that actually drive the decisions in scope.
2. Reconcile them against the authoritative source and make every disagreement visible.
3. Validate the reconciled view with the people who currently keep the shadow spreadsheets.

What success would be measured against

What you would measure: how often decisions stall on reconciling numbers, the number of competing shadow records for a key figure, and whether teams will act on the shared view without re-checking it themselves.

The symptom

The rules that make the operation work — how to sequence a tricky job, which substitution is safe, what a customer will really accept — live in the experience of a few key people and a trail of personal spreadsheets. When they are on leave, decisions slow down or wait.

Why it matters commercially

Concentrated know-how is a direct continuity and growth risk: it caps how fast you can take on work, makes succession fragile, and turns routine absence into disruption. It also makes the operation hard to improve, because the logic is undocumented.

What must be proven

That the most important tacit rules can be captured as reviewable, governed logic — keeping people in control of the decisions while reducing how much depends on any one individual.

Intervention options

1. Surface the decisions that stall whenever a specific person is unavailable.
2. Capture the underlying rules as explicit, reviewable logic those experts confirm.
3. Run the governed loop so proposed decisions are transparent and any expert can override them.

What success would be measured against

What you would measure: the number of decisions that can only be made by one person, the delay when that person is unavailable, and how much critical logic is written down and agreed rather than remembered.

The symptom

When a non-conformance or a customer query arrives, assembling the story — what was decided, by whom, against which revision, and why — means chasing emails, sign-offs, and memories. The audit trail exists in fragments, not as one coherent, defensible record.

Why it matters commercially

Weak lineage lengthens investigations, weakens your position in disputes and audits, and makes it harder to demonstrate control to regulated or demanding customers. Every unclear decision is a cost and a risk waiting to surface.

What must be proven

That decisions can be governed with an auditable trail — capturing the inputs, the human approval, and the rationale — without adding friction to the people doing the work.

Intervention options

1. Map where decision rationale is currently lost between systems and people.
2. Design a governed decision loop that records inputs, approver, and reasoning as a by-product.
3. Confirm the resulting trail satisfies your quality and customer-facing requirements.

What success would be measured against

What you would measure: the time to reconstruct why a decision was made, the proportion of key decisions with a complete rationale on record, and how readily that record stands up in an audit or dispute.

The symptom

Across engineering changes, substitutions, and shop-floor decisions, the as-built configuration quietly diverges from the as-designed and as-ordered intent. Reconciling what was really made against the record is manual, late, and never quite complete.

Why it matters commercially

Incoherent as-built records cause rework, warranty exposure, and painful spares and support later in the product’s life. For make-to-order work, where every unit can differ, the cost of not knowing exactly what shipped compounds over time.

What must be proven

That a governed model can keep the as-designed, as-ordered, and as-built views coherent through change — with people approving each reconciliation — using your real configurations.

Intervention options

1. Trace where the as-built record diverges from design and order intent today.
2. Prove that changes can be reconciled into one coherent, governed configuration view.
3. Pilot the governed loop on a representative product line before wider adoption.

What success would be measured against

What you would measure: the effort to reconcile as-built against as-designed, the rate of configuration discrepancies found late, and confidence in what was actually shipped for any given unit.