Synthetic demonstration · Not client work · USD · January–June 2026

All case studies

manufacturing · operations intelligence

Finding capacity hidden in downtime

Where does production lose productive hours?

Operational intelligence

Synthetic data · USD · 2026

Ehiz Analytics

Productive hours

11,737

Calculated from selection

Utilisation

77.3%

Calculated from selection

Scheduled hours

15,180

Calculated from selection

Unused capacity

3,443

Calculated from selection

Capacity & productive hours

ScheduledProductive

Capacity utilisation

77%Utilisation
Productive11,737 h
Unused3,443 h

Unused hours by month

Analyst note

77.3% of scheduled capacity was productive. 3,443 hours remain unused in this selection.

Rule-based summary · synthetic figures · not a live AI response

Illustrative scenario · April revenue is below March in this synthetic dataset.

01 · Source

18 deterministic synthetic monthly market records: three markets across six months. No private customer records are used.

02 · Method

Compare scheduled and productive hours by period and market; calculate utilisation from total hours.

03 · Finding

11,737 productive hours represent 77.3% of scheduled capacity. The remainder is an analytical gap, not an inferred cause.

Reproducible approach

A transparent calculation, not a black box.

The preview aggregates synthetic records in your browser. This equivalent SQL example describes the method; it is not a query against customer data.

Limitations: no causal inference, currency conversion or real-world performance claims. Market comparisons represent illustrative scenarios, not geographic benchmarks.

SELECT region, SUM(productive) AS productive_hours,
  100.0 * SUM(productive) / NULLIF(SUM(planned), 0) AS utilisation
FROM illustrative_records
GROUP BY region;
Explore the existing synthetic financial report & exports

Separate legacy financial demonstration · 600 synthetic records · Not the 18-record preview above.

Total revenue

$192,000

Recorded sales

Gross profit

$100,500

Revenue less cost of goods

Operating expenses

$27,300

Recorded expense transactions

Net profit

$73,200

After costs and expenses

+8.7% revenueLatest 30 vs previous 30 days in selection

Revenue & profitability

RevenueNet profit

Data quality & completeness

Records in selection
600
Sales with cost data
500 / 500
Import rejections*
0

Profit is available only when all selected sales have recorded costs. Zero or missing costs are treated as incomplete. *Rejections cover selected source files, not the date filter.

Leading products by revenue

ProductRevenueUnits
Assembly A$76,8001,000
Assembly B$57,600850
Spare parts$38,400700
Packaging$19,200550

Expense breakdown

  • Operations$13,650
  • Personnel$8,190
  • Other$5,460

Notable product changes

Assembly A

+$1,280

Latest 30 vs previous 30 days

Assembly B

+$960

Latest 30 vs previous 30 days

Spare parts

+$640

Latest 30 vs previous 30 days

Packaging

+$320

Latest 30 vs previous 30 days

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