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Operational Intelligence Audit™

Four weeks to see the work clearlyand choose what comes next.

Arrange an Audit Call
Page 1 of the Vital Signs AI Maturity Scorecard sample document
Vital Signs™: AI Maturity Scorecard. Page one of the fictional Hartwell M&E example.Open the readerPDF3 pages

The Audit maps your workflows, documents, data and governance, then returns seven named deliverables for your team to review. Any implementation is optional and agreed separately.

Scope

from the first brief to a decision
Four weeks
named deliverables, yours to keep
Seven
implementation, agreed separately
Optional
scope and fee, in writing
Agreed first

Is the Audit the right first step?

One way to start. Not a prerequisite for every engagement.

An Operational Intelligence Audit is one way to start; it is not a prerequisite for every engagement. It suits an operation that wants its workflows, documents and data mapped before choosing a pack or a build.

  • 01
    A defined outcomeThe change or deliverable is clear enough to scope.
  • 02
    Usable source informationThe team can identify the material the work relies on.
  • 03
    Named reviewersResponsible people can review and decide what is issued.
  • 04
    Start elsewhereA workflow pack or a Built to Order brief can begin without an Audit. Compare the three ways to buy

The four-week cadence

Four weeks. From the first brief to a decision.

  1. W1

    Shape & scope

    Discovery

    Document inventory submitted. Three working sessions booked. Vital Signs scorecard issued at end of week - board-ready, gap-mapped, signed off.

  2. W2

    Hours & £

    Diagnosis

    Bleed Rate analysis. Time and cost quantified across six categories. Root causes traced. First findings reviewed with operations lead mid-week.

  3. W3

    Roadmap & rules

    Direction

    Heat Map ranks AI opportunities. Dry Run prototype produced on a real document. Guard Rail governance framework drafted, RAG-classified, ISO-aligned.

  4. W4

    Board pack

    Decision

    Flight Plan blueprint and Green Light Phase 1 proposal delivered. Board pack ready. Decision yours: act, defer, or take the artefacts elsewhere.

What you get back

Seven deliverables. See what each one makes clear.

Explore each first page, then open the full document to inspect the detail before discussing your own Audit.

  1. 01VSMaturity

    Vital Signs™

    Pulse check across bid, commercial, compliance, reporting, systems, governance - scored 1-5, gap-mapped.

    Page 1 of the Vital Signs deliverable sample document
    3 pagesOpen the readerPDF3 pages
  2. 02BRLeakage

    Bleed Rate™

    Six leakage categories quantified, with annual cost, supporting evidence and improvement opportunities.

    Page 1 of the Bleed Rate deliverable sample document
    3 pagesOpen the readerPDF3 pages
  3. 03HMRoadmap

    Heat Map™

    Six AI opportunities × six criteria, weighted-total ranked, placed into Phase 1, 2 or 3 of the engagement.

    Page 1 of the Heat Map deliverable sample document
    3 pagesOpen the readerPDF3 pages
  4. 04DRPrototype

    Dry Run™

    One real document, run through one workflow, audit-grade governance. The proof-of-fit doc.

    Page 1 of the Dry Run deliverable sample document
    2 pagesOpen the readerPDF2 pages
  5. 05GRGovernance

    Guard Rail™

    RAG data classification, four-gate approval process, audit-trail requirements, ISO 42001 alignment.

    Page 1 of the Guard Rail deliverable sample document
    3 pagesOpen the readerPDF3 pages
  6. 06FPBlueprint

    Flight Plan™

    12-month transformation in three phases - prove-and-recover, visibility-and-control, extend-and-integrate.

    Page 1 of the Flight Plan deliverable sample document
    3 pagesOpen the readerPDF3 pages
  7. 07GLProposal

    Green Light™

    Phase 1 implementation. Fixed scope, 16 weeks, two workflow packs, eight KPI targets. Opt-in, not opt-out.

    Page 1 of the Green Light deliverable sample document
    3 pagesOpen the readerPDF3 pages

About these examples. Hartwell is fictional. Its figures, timescales, targets and states are not client results or promised outcomes.

Green Light is an optional proposal: its 16-week, two-pack and eight-target example is not a standard implementation promise. “Audit-grade” describes the sample review structure; ISO 42001 alignment does not imply certification.

Worked example

See how the Audit works.

Hartwell M&E is a fictional £45m contractor. Its model shows how evidence can be structured and reviewed; it is not a client result or a forecast for your business.

Annual leakage modelled
£1.87m
Of modelled turnover
4.2%
Hours modelled each year
9,600
Bleed Rate model and estimatorSix source categories, pack routes and adjustable assumptions

Example reading view. Interactive controls load on demand.

A starting profile.

The fictional Hartwell model uses 4.2% of turnover as its midpoint. This is a model, not a forecast or quotation.

Annual turnover
£25m
Tenders / year
24
RAMS packs / month
14
CVR cycle (days)
30 days

Annual leakage modelled

£810k–£1.10m

≈ 3.8% of turnover · the starting profile sits toward the lower end of the band.

The Hartwell band spans roughly 3–6% of turnover. A four-week diagnostic can examine the underlying evidence across six categories.

Arrange an Audit Call
Heat Map prioritiesSix opportunities scored against six criteria

Example reading view. Interactive controls load on demand.

Six opportunities. Six criteria.

A standalone scoring demonstration. Each criterion is scored from 1 to 5; the unweighted total adds all six scores, out of 30. These opportunities and phases are separate from the fictional Hartwell weighted ranking. Read the fictional Hartwell Heat Map: weighted ranking out of 5.

  1. Tender response automation

    Bidroom in a Box® · P1 · Unweighted total 24 out of 30

    Value
    5 out of 5
    Speed
    5 out of 5
    Data
    4 out of 5
    Risk
    3 out of 5
    Complexity
    3 out of 5
    Governance
    4 out of 5
  2. Variation pack production

    Commercial Control Kit™ · P1 · Unweighted total 23 out of 30

    Value
    5 out of 5
    Speed
    4 out of 5
    Data
    4 out of 5
    Risk
    3 out of 5
    Complexity
    3 out of 5
    Governance
    4 out of 5
  3. CVR & WIP rebuild

    Margin Cockpit™ · P2 · Unweighted total 22 out of 30

    Value
    4 out of 5
    Speed
    3 out of 5
    Data
    5 out of 5
    Risk
    2 out of 5
    Complexity
    4 out of 5
    Governance
    4 out of 5
  4. RAMS & method statements

    RAMS Factory® · P2 · Unweighted total 22 out of 30

    Value
    3 out of 5
    Speed
    5 out of 5
    Data
    5 out of 5
    Risk
    4 out of 5
    Complexity
    2 out of 5
    Governance
    3 out of 5
  5. Deductions defence pack

    Dispatch Desk™ · P3 · Unweighted total 21 out of 30

    Value
    4 out of 5
    Speed
    3 out of 5
    Data
    3 out of 5
    Risk
    3 out of 5
    Complexity
    4 out of 5
    Governance
    4 out of 5
  6. Pre-con package builder

    Pre-Con Pack™ · P3 · Unweighted total 21 out of 30

    Value
    3 out of 5
    Speed
    3 out of 5
    Data
    4 out of 5
    Risk
    3 out of 5
    Complexity
    4 out of 5
    Governance
    4 out of 5
Dry Run and workflow routingOne sample document, before-and-after review evidence

Hartwell example

Dry Run™ on a 142-page tender pack

These comparison figures belong to the fictional Hartwell scenario. A live Audit uses a document from your operation and records its own before-and-after evidence.

MeasureBeforeAfterDifference
Time to first usable artefact11h 30m47 min−93% time
Quality score (peer review)5168+17 pts
RFI / clarification gaps148−6 gaps
Risk register completeness9 unflagged4 unflagged−5 unflagged
Audit-trail signed lines011+11 traces

05 / Supporting examples

Six supporting examples. Evidence you can follow.

These examples show content, review stages and targets. They do not record a live client engagement or prove that a control has operated.

01 · Findings Pack

Supporting example · AMBER

Why it matters

Links findings to evidence and gives board reviewers a clear basis for challenge and action.

Review control illustrated

The sample links findings to source references and shows drafter, senior and client review stages.

Findings Pack - Tier-1 M&E contractor (sample)

FND-PACK · v1.2 · QA2-approvedAMBER

FND-014 · Variation evidence chain breaks at site instruction

Eight of twelve sampled variations carry no instruction-trail entry between site and commercial. Of those, three were priced and two were paid before the trail was reconstructed retrospectively - exposing the position to challenge.

Classification · Risk · Effort
  • Impact · COMMERCIAL - exposed to retrospective challenge
  • Risk level · HIGH - three live, in-cycle examples in the sample
  • Effort to fix · M - site report template + 2 weeks of cadence
  • Recommended pack · Commercial Control Kit™
Linked evidence
ReferenceTypeSource
EVD-021Email threadSite → Commercial · 14 Mar
EVD-022Site daily report (3 dates)Project diary
EVD-024Variation register entryCost report Apr
Sign-off
  1. QA1 (drafter check)passed
  2. QA2 (senior review)passed
  3. Client approvalin review
Sample artefact · structure mirrors a BuiltAI deliverable. Names, references, figures, states and targets belong to a fictional scenario.
02 · Baseline KPI Sheet

Supporting example · AMBER

Why it matters

Creates an agreed starting point so later impact claims can be compared using the same definitions and sources.

Review control illustrated

The sample gives each metric a source, named owner and confidence rating, followed by review stages.

Baseline KPI Sheet - sample

BKPI · v1.0 · Owner-confirmedAMBER

Metric register
MetricBaselineSourceOwnerConfidence
Tender response cycle (days)14.2Last 6 ITTsCommercial dir.High
Clarification close-rate (%)51Bid log Q1Bid managerMedium
Variation evidence index (%)44Cost report sampleQS leadMedium
RAMS rework rate (%)38H&S log 90 daysH&S managerHigh
Re-measurement cadence
  • Frequency · Monthly, against the same source
  • First re-measurement · Day 60 of the engagement
  • Method · Same source + same definition + same owner - no re-baselining mid-engagement
Sign-off
  1. BuiltAI delivery leadpassed
  2. Client operational ownerpassed
  3. Client sponsorin review
Sample artefact · structure mirrors a BuiltAI deliverable. Names, references, figures, states and targets belong to a fictional scenario.
03 · Risk & Governance Assessment

Supporting example · AMBER

Why it matters

Gives procurement, legal and insurance reviewers a dated, traceable view of AI use, data classification and approval gaps.

Review control illustrated

The sample separates current uses by sanction and classification, records actions and identifies approval gaps for review.

Risk & Governance Assessment - sample

RGA · v1.1 · Procurement-readyAMBER

AI usage map (current state)
ServiceSanctioned?ClassificationAction
Microsoft 365 CopilotYesGreen/AmberContinue under AUP
Public ChatGPT (consumer)ShadowRed exposureBlock; route to enterprise tenant
Custom GPTs in marketingYesGreenDocument; add to approved tools list
Approval gate gaps
  • QA1 missing · RAMS template approval gate is informal - no recorded reviewer
  • Client approval missing · Variations issued before client sign-off in 3/12 sampled cases
Procurement-disclosure readiness

Current AI Schedule covers 2 of the 5 BuiltAI canonical clauses (Permitted Use, Approved AI Tools). Definitions, Human Approval Gate and AI Output IP are absent. Recommended: install full AI Governance Policy Pack before next procurement cycle.

Sample artefact · structure mirrors a BuiltAI deliverable. Names, references, figures, states and targets belong to a fictional scenario.
04 · Pilot Recommendation

Supporting example · GREEN

Why it matters

Gives an operational owner a defined pilot to assess, with scope, responsibilities and measurable exit criteria.

Review control illustrated

The sample records the recommended pack, tender scope, owners, exclusions, baseline figures and pilot targets.

Pilot Recommendation - sample

PILOT · BIDROOM · v1.0GREEN

Headline

Pilot Bidroom-in-a-Box on the next two tier-1 ITTs. Target: clarification close-rate to 95%+ and tender cycle to ≤10 days, against a 14.2-day, 51%-close baseline.

Scope
  • Pack · Bidroom-in-a-Box
  • Tenders in scope · Next 2 tier-1 ITTs (≥£500k)
  • Owners · Bid manager (lead) · QS for pricing · Tech director for narrative QA
  • Out of scope · Tier-2/3 framework call-offs · Public sector OJEU bids
Exit criteria
MetricBaselinePilot target
Clarification close-rate (%)5195+
Tender response cycle (days)14.2≤10
Win-rate uplift (pp)0+3 to +5
Sample artefact · structure mirrors a BuiltAI deliverable. Names, references, figures, states and targets belong to a fictional scenario.
05 · 90-Day Roadmap

Supporting example · GREEN

Why it matters

Turns a proposed pilot into phased action, with clear milestones from mobilisation to handover.

Review control illustrated

The sample sets out three 30-day phases with mobilisation, operating and handover milestones.

90-Day Roadmap - sample

ROADMAP · v1.0GREEN

Days 1–30 · Mobilise
  • Sponsor sign-off · Commercial director nominated; budget cap set
  • Baseline frozen · Owner-confirmed, classification per file recorded
  • Pack template installed · Bidroom-in-a-Box live in CRM workspace
Days 31–60 · Operate
  • Pack live on real tenders · First two ITTs run end-to-end through the pack
  • QA gate active · QA1 + QA2 sign-off on every clarification register
  • Weekly cadence · 30-minute commercial standup, RAG-status update
Days 61–90 · Embed
  • Governance handover · AUP + AI Schedule briefed to procurement
  • Retainer scope agreed · Monthly cadence + cost cap signed off
  • Board pack issued · First post-pilot board pack with recovery narrative
Sample artefact · structure mirrors a BuiltAI deliverable. Names, references, figures, states and targets belong to a fictional scenario.
06 · Data Pack Requirements

Supporting example · GREEN

Why it matters

Makes the information needed for a pilot explicit before delivery starts, reducing avoidable delay and rework.

Review control illustrated

The sample illustrates files, classifications, owners and acceptance states, with a separate acceptance gate.

Data Pack Requirements - sample

DPR · BIDROOM · v1.0GREEN

File-level checklist
FileClassificationOwnerStatus
Recent ITT pack (1 example)AmberBid managerRequested
Clarifications register (current)AmberBid managerAwaiting upload
Pricing breakdown templateAmberQS leadAccepted
Submission narrative (template)GreenBid managerAccepted
Assumptions / exclusions registerGreenBid managerOptional
Acceptance gate

All required files Accepted before kickoff date. Red-classified items routed via the secure handling track - never via this checklist. Optional items can land mid-pilot without blocking.

Sample artefact · structure mirrors a BuiltAI deliverable. Names, references, figures, states and targets belong to a fictional scenario.

06 / Scope and next step

Scope and fee agreed before work starts.

A 30-minute call establishes fit. If an Audit is useful, the written proposal confirms its four-week scope, seven deliverables, timing and fee. There is no commitment to implementation; the next decision remains yours.

Prepared to scope the Audit now? Use the full request

Four weeks · seven deliverables · output stays yours

Review the Audit commitmentsScope, ownership, source handling and freedom of choice

What is not in the Audit

01

Phase 2 sales pitch baked into week 4

The audit closes in week 4 with three paths drawn - Act, Defer, Take Elsewhere. We don't hard-close.

MSA §3.1
02

Workflow-pack pre-sell

Heat Map ranks opportunities against your operation, not our backlog. P1 may not include any BuiltAI pack.

MSA §3.4
03

Multi-week scope creep

Four-week scope, with any change agreed in writing before work continues.

MSA §4.2
04

IP carve-outs or licensing tails

Every artefact (Vital Signs through Green Light) is yours, in perpetuity, the moment it lands.

MSA §6.1
05

Inputs in our training set

Source-material handling, retention and deletion terms are agreed in writing before the audit. Client material is used only for the service and is not used by BuiltAI to train models.

MSA §8.4