Proxima Diagnostic Report Illustrative sample

Diagnostic verdict

64% of exception cycle time is idle queue time. One of five categories is a candidate for human-approved testing.

Illustrative average resolution: 22 hours. The sample suggests a routing wait to validate with real records.

Shipment exception recovery500 hypothetical records330 hypothetical tests4 example systems

Illustrative sample only. Every case, test and number below is hypothetical, not a customer result or a completed automation test. A real review validates source records, cost inputs and owner decisions before any recommendation.

Bottleneck 14.1h

Idle in routing queues between WMS and TMS.

Value at risk Model only

No annual benefit is inferred from this example.

Same-day resolution 31%

Sample scenario only; no external benchmark is asserted.

Automation readiness 1 of 5

One hypothetical category merits a supervised test; none is live-cleared.

Example alignment 88%

Address mismatch alignment. Zero critical errors.

Bottleneck decomposition

WMS->TMS 38% Classification 26% Work 28% External 8%

System idle: no owner assigned (8.4h) Classification wait: awaiting owner (5.7h) Active work: human intervention (6.1h) External dependency (1.8h)

Exception recovery trace

64% idle14.1h idle queueillustrative cost scenario

Automation recommendation

Only validated categories could move forward.

Category	Status	Recommended mode
Address / contact mismatch	Test candidate	Validate on real cases before any human-approved action.
Carrier scan gap	Needs more testing	Suggestion-only test, then re-score. No live trace request.
Warehouse dispatch hold	Keep with people	Improve owner and resolution labels before another test.
Payment / document hold	Keep with people	Human review only. Compliance risk is too high.
Complex exception	Keep with people	Not enough pattern in the sample. Continue manual handling.

Evidence pack

How the verdict was reached.

01 Source data 500 records from four operating systems.

WMS, TMS, carrier API, and support desk events provide the baseline.

A Methodology / C Categories

02 Bottleneck 14.1h idle queue before owner assignment.

64% of cycle time is lost before the team receives the work.

B Baseline findings

03 Test output 330 historical cases scored against human decisions.

Address/contact merits a supervised test. Carrier needs more testing; warehouse stays with people.

D Agent feasibility

04 Decision One of five categories merits human-approved testing.

Payment, document, and complex exceptions stay with people.

E Decision matrix

05 Risk Model costs from stated assumptions.

No live-system action follows from this sample.

F Finance / G Risk register

06 Next step Validate a supervised test before any automation.

The real diagnostic returns the map, scorecard, risk register, and SOW.

H Deliverables

Reference sheets

Open the supporting sheets when you want the method, tables, and test records behind the board.

A.MethodologySystem evidence first, interviews second.Method

A real review starts with timestamps, logs, status codes and outcome records. Interviews help interpret gaps and anomalies in those records.

Phase	Activity	Data source	Sample
Baseline mapping	Trace every exception from flag to closure	WMS, TMS, carrier API, support desk	500
Bottleneck analysis	Measure dwell time per handoff	Queue entry and exit timestamps	500
Categorization	Group by root cause and resolution pattern	Structured and unstructured records	500
Agent feasibility test	Run read-only suggestions and score against human decisions	Historical records	330

Example test gate: A real supervised trial would need an agreed alignment threshold, zero critical safety errors, representative cases and explicit owner sign-off. The hypothetical scores here do not clear any live action.

B.Baseline findings22h average resolution with 64% idle time.Finding

22.0hIllustrative average resolution. 31%Illustrative same-day rate. 2.3Illustrative support touches per case.

Finding: 64% of cycle time, or 14.1 hours, is spent in queues before a human touches the case. This suggests a routing wait to verify with real timestamps; it does not establish team performance.

C.Exception category analysisFive categories sorted by root cause and severity.Map

Category	Share	Root cause	Queue time	Severity
Address / contact mismatch	26%	Customer master out of sync	3.2h	High
Carrier scan gap	22%	Carrier missed scan	5.7h	Medium
Warehouse dispatch hold	18%	Inventory issue post-pick	8.4h	Medium
Payment / document hold	12%	Compliance pending	12.1h	Low
Complex / multi-system	22%	Conflicting status	18.6h	Low

D.Agent feasibility test results330 cases compared with reviewed human decisions.Tests

Test 1: Address / contact mismatchTest candidaten=130

88%Action alignment 0%Critical errors 91%Communication clarity

System input

Order:        ORD-77291-X
Exception:    Pincode mismatch, delivery 560034 vs. master 560102
SLA:          16 Aug 2024, 14:00 IST
Value:        INR 4,200
Customer:     Acme Retail Pvt Ltd | Rajesh K.

Supervisor summary

Hypothetical supervisor draft: confirm the address with the customer, then seek carrier confirmation. Do not promise a revised delivery time before approval.

Test 2: Carrier scan gapNeeds more testingn=110

82%Action alignment 2%Critical errors 91%Severity classification

Hypothetical failure analysis: In this scenario, carrier API timeouts produce a 2% critical error rate when pending is recorded instead of escalated. A real review would require more suggestion-only testing before approval.

Test 3: Warehouse dispatch holdKeep with peoplen=90

79%Action alignment 85%Owner identification 74%Evidence complete

Conclusion: Not cleared. The sample shows too much ambiguity in owner routing and evidence packaging. Keep with people while collecting better resolution labels.

E.Decision matrixOnly validated categories could move forward.Decision

Category	Recommended action	Effort	Timeline
Address mismatch	Validate supervised test	To scope	After real evidence review
Carrier scan gap	14-day test, then re-score	4 weeks	Week 3-6
Warehouse dispatch	Keep with people; improve labels	To scope	After evidence review
Payment / document	Human review only	None	None
Complex exception	Manual handling	None	Ongoing

F.Financial impact modelIllustrative labour assumptions and scenario arithmetic.Finance

160Assumed cases per month 25 minAssumed follow-up per case ₹400/hAssumed loaded labour rate

Arithmetic: 160 cases/month × 25 minutes = 4,000 minutes, or 66.7 hours. At ₹400/hour, follow-up costs about ₹26,667/month. If a controlled change removed 25% of this time, it would release about 16.7 hours, equivalent to ₹6,667/month of capacity. This is not a forecast or cash saving; validate case volume, time and rate, and account for implementation costs.

G.Risk registerEdge cases and controls before live action.Risk

ID	Risk	Likelihood	Impact	Mitigation
R-01	Non-Latin characters in customer master	Low	Low	Route to human queue
R-02	Carrier API timeout logged as pending	Medium	Medium	Approval gate catches before action
R-03	High-value order auto-approved	Low	High	Hard human-review threshold above INR 25K
R-04	Ambiguous customer reply	Medium	Low	Supervisor review required
R-05	Premature controlled automation promotion	Low	High	30-day gate with customer sign-off

H.Deliverables from a real reviewProcess map, cost assessment and recommended next step.Output

Process map with waits, handoffs, owners and approval points.
Cost assessment with case volume, follow-up effort and assumptions shown.
Recommended next step for process improvement or a scoped supervised test, with a clear no-go option.

Next step

Run this diagnostic on your data.

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