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Double-digit EBITDA gains from the operations you already run.1

We find the EBITDA points in the four P&L lines an operation can move itself: revenue, material cost, personnel cost, other operating expenses. The first number is in the P&L within four quarters, not four years.

Book a margin review Operations Margin Report: early access

EBITDA bridge, typical engagement

Index points on a baseline of 100. The four P&L lines an operation can move itself.

Illustrative1. Hover a bar for the lever behind it.

+3.5EBITDA index points, modeled

Revenue.

Prices and offers come from the experience already in your systems. Customers who stopped buying come back from your own database. Demand and revenue forecast live, by customer group, product or service line, or segment1.

+3.0EBITDA index points, modeled

Material cost.

Purchasing runs automated, direct and indirect. No maverick buying, because stock and availability are known per location. Purchase prices harmonised across every ERP, and waste measured where it occurs.

+2.5EBITDA index points, modeled

Personnel cost.

Skilled time goes to the work, not to writing it up. Rosters come from the forecast, documentation from the systems that already hold the data, and expert help arrives remotely instead of in person.

+1.5EBITDA index points, modeled

Other operating expenses.

Unplanned outages, rework and audit preparation cost more than most budgets show. Maintenance moves onto the calendar, errors are traced to their root cause and fixed once, and compliance evidence files itself; NIS2 fines reach 2% of turnover7.

Impact

Selected engagements.

What changed in an engagement, one per sector1.

Manufacturing

Tier-1 industrial supplier, DACH

Predictive maintenance across 14 lines. Pay-back inside two quarters.

Plannedrepairs on the calendar, not on the line

See the sector

Healthcare

Regional hospital network

Care coordination and intelligent claims on one operating rhythm.

Same dayclean claims paid, follow-up planned at discharge

See the sector

Hospitality

International hotel group, 14 properties

Dynamic pricing and predictive staffing across properties.

Oneforecast for rates and rosters

See the sector

Financial services

Global investment bank

Anomaly detection across millions of daily transactions.

Replayableevery fraud score, with its inputs

See the sector

Industries

Every industry has a margin problem. We know where yours is.

Manufacturing, healthcare, hospitality and financial services are where most of our work sits.

ManufacturingRepairs planned, not suffered.See the work
HealthcareFollow-up planned at discharge.See the work
HospitalityRates and rosters from one forecast.See the work
Financial services & insuranceClean claims paid the same day.See the work
Life sciencesStudy reports in minutes, audit-ready.See the work
Professional servicesOnboarding from months to weeks.See the work
Public sectorBacklog down, zero lost files.See the work
LogisticsOn-time delivery +12 points.See the work
Energy & utilitiesFixed on the first visit.See the work
Statistical & decision sciencesMonte Carlo, causal impact, forecasting.The practice
Compliance, every sectorShieldOS keeps findings at zero and the audit pack ready.ShieldOS

System

ShieldOS. The compliance operating system.

Every control an industrial enterprise carries, mapped to the place in the operation where its evidence already appears. ISO 27001, 9001, 22301, NIS2, DORA, HACCP, MDR, 21 CFR Part 11, GDPR, the EU AI Act. Audit packs on any day of the year.

  • 1
    Evidence as a by-productVoice checklists, so the technician keeps both hands on the equipment, plus signatures, OCR reads and system exports: all file themselves against the controls that need them.
  • 2
    Certificate lifecycleRenewals started six months out. Zero certificates past expiry, reported daily.
  • 3
    Audit packs on demandSurveillance, customer or regulator: the pack is a filter on the board.
Book a margin reviewAbout ShieldOS

ShieldOS Control board

Plant Nord · Q42 due
Controls in scope214ISO 27001 · 9001 · 22301 · NIS2
Evidence captured this month1,96298% automatic
Open findings0Last audit: zero
Certificates expiring ≤ 6 months2Renewals started
ControlsCertificatesAudit packsRisk registerSuppliers
ControlFrameworkEvidence sourceCoverageStatus
Access reviews, OT networkISO 27001 A.5.18 · NIS2 Art. 21Directory export, monthly
✓Current
Calibration, measuring equipmentISO 9001 7.1.5Voice checklist, signed
✓Current
Business continuity test, line 3ISO 22301 8.5Test record, semi-annual
Due 14 Nov
Supplier security assessmentNIS2 Art. 21(2)(d)Questionnaire, annual
41 of 50
Illustrative board. Controls and evidence sources are typical for an industrial plant.Audit pack: ISO 27001 surveillance, ready

Master Data Management Layer Live

Golden recordLast sync 00:00:41
Golden records1.84MMaterials, customers, suppliers, assets
Connected systems31SAP, Oracle, Dynamics, MES, PLM, legacy
Consistency100%0 silent conflicts
Conflicts resolved, 30 days3,11292% by rule, 8% by owner
SystemsDomainsGovernance rulesConflictsLineage
SystemDomainRecordsDirectionLagState
SAP S/4HANA, plant NordMaterials, BOM, assets612,440Two-way< 1 s✓In sync
SAP ECC 6.0, plant SüdMaterials, customers388,120Two-way2 sMigration wave 2
Oracle EBS, financeCustomers, suppliers214,900Two-way< 1 s✓In sync
Microsoft Dynamics 365, salesCustomers, prices96,310Inbound< 1 s✓In sync
Illustrative. Volumes and lags are typical for a mid-size industrial group.Conflict rule set v14 · 212 rules

System

The V3Qtor Master Data Management Layer.

One golden record for materials, customers, suppliers, assets and lots across SAP, Oracle, Microsoft, MES, PLM and legacy. Real-time synchronisation, governance rules, conflict resolution, lineage. The part of the landscape that survives the ERP transformation.

  • 1
    ERP integrations at the recordSAP S/4HANA and ECC, Oracle, Dynamics 365, MES and PLM, each through its native interfaces, all agreeing on one record.
  • 2
    ERP transformations in five phasesAssess, cleanse, harmonise, migrate, run. Mainstream maintenance for SAP ECC 6.0 ends in 20278; the layer makes the migration a data project that works.
  • 3
    What every model needsRAND names missing data as the second root cause of AI project failure9. The layer is that data.
Book a margin reviewAbout the layer

System

AI Governance. Sovereign, on-premise, deterministic.

AI that runs on your premises, answers the same way every time, and leaves an audit trail for every run.

Book a margin reviewHow it runs
  • 1
    SovereignData, models and logs stay in your jurisdiction under your keys. Residency is a setting the auditor can read.
  • 2
    On-premiseDeployed in your data centre or a sovereign cloud, air-gapped where the plant or the regulator requires it.
  • 3
    DeterministicFixed decoding, schema-constrained outputs, validators before writes, citations, confidence floors, evaluations before every change. Every run replayable.
  • 4
    MeasuredCost per agentic run, per task and in total, GPU utilisation, requests per week and month, per workload.

AI Governance Operations board

On-premise cluster · 8 GPUs30 days
Cost per agentic runCHF 0.84Median across workloads
Cost per task completedCHF 2.31−18% against the prior month
Total cost, 30 daysCHF 18,420Compute, storage, licences
GPU utilisation71%Peak 94%, weekday mornings
WorkloadsModelsEvaluationsRun logCosts
WorkloadRequests, weekRequests, monthCost per runCost per taskBudget
8D fault classification1,2845,310CHF 0.62CHF 1.90✓Within
Claim validation9,76041,200CHF 0.31CHF 0.44✓Within
Discharge letter draft2,1158,940CHF 1.12CHF 3.05Over
Maintenance work-order triage6402,710CHF 0.48CHF 2.60✓Within
Illustrative. Every run is logged with model version, inputs and cost, so the same record that makes it replayable makes it billable.Requests this week: 13,799 · this month: 58,160

Common quick wins

Where the first points usually come from.

The levers we meet in most operations, by P&L line. Few of them need a new system.

Revenue

  • Quotes with price and delivery date in hours, from the experience in your existing systems
  • Forgotten and dormant customers reactivated: the database shows who has not ordered for years or whose enquiry got lost between media
  • AI-assisted market analysis to find new customers and customer segments
  • Order intake, revenue forecast and sales projections live from the system, by customer group, product group or sector
Operations Intelligence

Material cost

  • Purchasing processes automated, direct and indirect
  • No maverick buying: which materials sit in which warehouse, and how fast they are available
  • Purchase prices for raw materials and components harmonised and transparent across all ERP systems
  • Dynamic bills of material and automatic orders with the three best suppliers on your whitelist
  • Automatic purchase-requisition process
  • AI-guarded supplier onboarding, with a human in the loop for approvals
Master Data Management Layer

Personnel cost

  • Rosters from the demand forecast, overtime visible before it happens
  • Documentation drafted from the record instead of typed twice
  • Onboarding with work instructions that adapt to the person and the task
  • Remote support instead of the site visit
  • Back-office routines automated: invoice intake, master-data upkeep
Workforce & Field Enablement

Other operating expenses

  • Maintenance by condition instead of by calendar
  • Scrap and rework down through SPC and 8D
  • Energy managed to ISO 50001, peaks in view
  • Audit packs instead of a project before the audit, no fines
  • AI operating cost reported per run
ShieldOS

Capabilities

What we do, by practice.

Most engagements draw on two or three of them.

Operations Intelligence

Process discovery, conformance checking, bottleneck economics, what-if simulation. We put a number on every queue and a cost on every hand-off.

  • Selected work
  • Production Flow Analyzer manufacturingBottleneck found
  • OEE Intelligence Suite manufacturingLive OEE by loss
  • Kitchen Command Center hospitalityLive station balancing
  • Intelligent Claims Engine insuranceSame-day clean claims

Insights

Reports and news.

Operations Margin Report. Industrial manufacturing edition.

Coming soon. Early access for registered readers.

Where the next EBITDA points sit in an industrial plant: downtime economics line by line, OEE gaps against the 85% benchmark11, the real cost of an open 8D, master data as the precondition for every model, and what NIS2 and the EU AI Act mean for a plant's compliance evidence. With chapters on healthcare, hospitality and financial services.

  • Industrial EBITDA bridges, anonymised
  • Downtime cost benchmark by sector2
  • The CHF 100M threshold: why below it the economics don't hold

News and perspectives

News18 October 2026

Why 80% of AI projects fail, and what we do differently.

RAND, MIT NANDA and Gartner put enterprise AI failure between 80% and 95%. The reasons are organisational, and they are fixable.

SystemAI Governance

How an AI output becomes evidence.

Fixed decoding, validators before writes, and an evaluation before every change. Every run can be replayed a year later.

SystemERP transformations

Move the system. Keep the data.

Mainstream maintenance for SAP ECC 6.0 ends in 2027 (SAP, 2020). The layer holds the record while ECC and S/4HANA run side by side.

Book a margin review.

Tell us about the process or the site you have in mind. Within a week we will say what we would look at first, what the first quarter would produce, and what it would take.

Book a margin review
Notes and sources
  1. 1Illustrative. Anonymised engagement scenarios; figures indicate modeled or targeted impact and are not audited outcomes.
  2. 2Senseye, The True Cost of Downtime, 2021. Fortune Global 500 manufacturing and industrial firms: about 3.3 million hours of unplanned downtime a year, roughly $864 billion, about 8% of revenue; automotive $1.34 million per hour, heavy industry $187,500, FMCG $23,600. Source
  3. 3Deloitte Analytics Institute, Predictive Maintenance, position paper, 2017. Average figures cited: breakdowns down 70%, maintenance costs down 25%, productivity up 25%; uptime up 10 to 20%. Source
  4. 4CBRE Hotels' Americas Research, Trends in the Hotel Industry, 2017 edition, as reported by Lodging Magazine: labour averages roughly half of hotel operating expenses; labour drove 90% of the 2016 rise in operating costs. Source
  5. 5Jacques D et al. Evaluating Nurses' Perceptions of Documentation in the Electronic Health Record. JMIR Nursing 2025;8:e69651. EHR time data showed nurses spent 31% of a 12-hour shift in flowsheets. Source
  6. 6Champions 12.3, The Business Case for Reducing Food Loss and Waste: Hotels, 2018. 42 sites in 15 countries: $7 saved for every $1 invested, 21% less food waste in the first year, 70% of sites paid back within a year. Source
  7. 7Directive (EU) 2022/2555 (NIS2), Article 34: administrative fines for essential entities of up to €10 million or 2% of total worldwide annual turnover, whichever is higher; important entities up to €7 million or 1.4%. Source
  8. 8SAP maintenance commitment announced February 2020: mainstream maintenance for SAP Business Suite 7 core applications (including ECC 6.0) runs to end of 2027, with optional extended maintenance to end of 2030. Source
  9. 9RAND Corporation, The Root Causes of Failure for Artificial Intelligence Projects and How They Can Succeed, RRA2680-1, August 2024. More than 80% of AI projects fail, twice the rate of IT projects without AI; 65 experienced practitioners interviewed. Source
  10. 10MIT NANDA, The GenAI Divide: State of AI in Business 2025, August 2025. About 95% of generative AI pilots show no measurable P&L impact; purchased or partnered deployments succeed about 67% of the time, internal builds about a third as often. Source
  11. 11OEE benchmark widely used in industry (Vorne, oee.com): 85% is considered world class for discrete manufacturers; a typical score is around 60%. Source