Quoriam

// AN OPERATIONAL INTELLIGENCE COMPANY

// 04 · CASE STUDIES

What changes when operations run on evidence.

Real engagements. Names withheld where confidentiality requires.

// CASE STUDY · LIVE · MANUFACTURING

A mid-sized stoneware manufacturer · Eastern Province

The operation

A family-run stoneware manufacturer: four production lines, 161 instrumented assets, two shifts a day. They already had SAP S/4HANA for batch and inventory, a CMMS that had drifted out of regular use, and a historian nobody had opened in over a year.

The problem

Throughput moved shift to shift with no consistent explanation. Maintenance ran on the calendar, not on the condition of the asset. The numbers were reconciled in spreadsheets after the fact, so the decisions they drove always arrived a week late.

What we deployed

Integrated

The existing SAP S/4HANA for batch and inventory; the dormant CMMS for work-order history.

Deployed

Predictive maintenance, OEE tracking with per-line and per-recipe context, and quality / CoA workflows tied to the platform's audit log.

Installed

Vibration sensors on the critical kilns, temperature probes at the kiln entries, and an edge gateway per cell.

What changed

Within the first quarter the dashboards were live at every shift handover. The bottleneck kiln took two interventions in that quarter, both pulled forward by anomaly alerts that fired before the operator noticed anything. Unplanned stoppages fell, OEE climbed, and first-pass yield rose across all four lines.

[PLACEHOLDER — pull quote from anonymised role pending Moayed sign-off.]Production Director · Eastern Province

The operation is now ahead of its own baseline, and two further lines are scoped to come on for the next financial year. Maintenance and shift decisions run end-to-end through the platform.

Currently deploying.

// PILOT · IN-FLIGHT · LOGISTICS

A logistics yard operator · Doha

// PHASE 2 OF 3 · INSTRUMENTING THE FLEET · 90 DAYS IN

We are installing GPS and yard telematics across the fleet, integrating their existing dispatch system, and standing up the yard operating picture. First live KPIs due next month.

Follow the deployment

// ILLUSTRATIVE · NOT A REAL CLIENT

What a Quoriam deployment looks like.

Illustrative scenarios, clearly labelled. Built on representative operations, not anonymised real clients.

// ILLUSTRATIVE

SMART BUILDINGS

Energy and comfort on one operating picture.

Integrate the BMS and sub-metering, deploy zone-level anomaly detection, and surface chiller-load drift before the first tenant complaint.

  • ENERGY INTENSITY TRACKED PER ZONE
  • HVAC DRIFT CAUGHT INSIDE THE HOUR
  • FEWER TENANT-COMFORT INCIDENTS

// ILLUSTRATIVE

AGRICULTURE

Block-level decisions backed by what the field actually did.

Install soil and climate sensors per block, integrate the irrigation controller, and deliver one operating picture on the agronomist's weekly cadence.

  • EARLIER CROP-STRESS DETECTION
  • WATER USE BENCHMARKED VS PRIOR SEASON
  • YIELD DECISIONS BACKED BY MEASUREMENTS

// 09 · START

See what your operation looks like through Quoriam's lens.

A free three-week operational intelligence assessment. You give us read-only access to whatever data you already have; we deliver a 24-page report covering your current data coverage, the five biggest KPI blind spots in your operation, and a 90-day roadmap to close them. No cost, no commitment. Two assessments accepted per month.