Discovery
AuraScore 81/100

Industrial Automation Discovery Matrix

Map operational technology gaps and modernization levers across manufacturing plants.

Use during enterprise discovery calls with plant managers and VP of Operations to evaluate legacy OT/IT convergence challenges. It systematically captures machine connectivity hurdles, telemetry deficits, and business value drivers into an executive matrix.

Template

Role: Principal Industrial Solutions Architect specializing in Industry 4.0 automation and plant digitalization.

Context

  • Manufacturing enterprise: {{target_manufacturer}}
  • Plant network footprint: {{facility_footprint}}
  • Deployed control systems and OT infrastructure: {{current_ot_stack}}
  • Reported operational throughput blockers: {{operational_bottlenecks}}
  • Capital expenditure envelope: {{capex_investment_bracket}}
  • Strategic automation goals: {{digitalization_objectives}}

Task

Synthesize unstructured discovery notes into an actionable Plant Modernization Discovery Matrix that correlates shop-floor telemetry bottlenecks with financial impact and proposed technological remedies.

Method

  1. Analyze {{current_ot_stack}} to identify protocol fragmentation, legacy PLC barriers, and data silos across {{facility_footprint}}.
  2. Cross-reference {{operational_bottlenecks}} against overall equipment effectiveness (OEE) metrics, unplanned downtime, and scrap rates.
  3. Map every identified operational barrier to specific production cells, lines, or material handling workflows.
  4. Calculate estimated business loss per operating hour for each bottleneck using {{capex_investment_bracket}} as a scale baseline.
  5. Categorize technical interventions into Edge Compute, SCADA/MES Modernization, and Cloud Telemetry layers based on {{digitalization_objectives}}.
  6. Evaluate buyer technical readiness, OT cybersecurity friction, and shop-floor change management constraints.
  7. Structure findings into a prioritized opportunity matrix ranking modernization urgency versus implementation complexity.

Constraints

  • All evaluations MUST explicitly differentiate between brownfield retrofit constraints and greenfield opportunities.
  • You MUST NOT recommend generic software features without tying them directly to a stated line-level failure mode.
  • Metric estimations must reflect standard discrete and process manufacturing benchmarks.
  • Technical terminology must match ISA-95 standards for enterprise-control system integration.

Output format

Present the analysis in three ordered sections:

  1. Executive Synthesis (150-200 words summarizing the operational posture of {{target_manufacturer}}).
  2. Plant Modernization Discovery Matrix (a structured Markdown table containing: Production Domain, Stated Bottleneck, Technical Root Cause, Quantified Financial Exposure, Proposed Modernization Vector, Implementation Complexity [Low/Med/High], and Deal Priority [P1/P2/P3]).
  3. Discovery Qualification Narrative (3 tactical recommendations for technical validation and next-stage proof-of-value scoping).

Self-review

  • Does the matrix clearly reflect all constraints imposed by {{current_ot_stack}}?
  • Are financial impact estimates grounded in realistic manufacturing downtime and scrap economics?
  • Does the matrix avoid generic IT SaaS language in favor of industrial automation nomenclature?
AuraScore breakdown
81/100Provisional
Instruction clarity15/15 · Strong

Explicit role, a named task, and discrete steps the model can follow.

Context architecture12/12 · Strong

Background, inputs and variables the model needs before it starts.

Constraint engineering12/12 · Strong

Hard boundaries — what the model must and must not do.

Output specification6/14 · Thin

A named, field-level shape for the response.

Reasoning structure10/10 · Strong

Ordered work items that force analysis before an answer.

Model compatibility10/10 · Strong

Length and structure that travel across frontier models.

Token efficiency5/10 · Thin

Signal density — instruction weight without padding.

Reusability7/7 · Strong

Documented variables so the scaffold adapts to new inputs.

Robustness3/5 · Adequate

Quality bar, assumptions and behaviour when inputs are thin.

Observed performance1/5 · Thin

How much real usage the template has behind it.

sales
sales-discovery
manufacturing-industrial
manufacturing
industrial-automation
discovery-matrix