Workflow vs. Integration vs. RPA

Choose the right pattern for the job. Workflow routes human work with rules and evidence. Integration moves data between systems through contracts. RPA drives user interfaces when APIs do not exist and screens stay stable. Link each choice to risk and control.

Overview

Design first. Fix handoffs and approvals before you automate. Then pick a pattern that matches the work: human coordination → workflow, system-to-system data → integration, UI steps with no API → RPA. Keep one source of truth.

Decision framework

Work profile

  • Human routing, SLAs, evidence → Workflow
  • Structured data exchange → Integration
  • No API, stable screens, narrow scope → RPA

Change risk

  • Frequent screen changes → avoid RPA
  • Unstable schemas → guard integration contracts
  • New policy or approvals → workflow fits

Controls

  • Approvals, logs, SoD → workflow
  • AuthN/AuthZ, audit, data lineage → integration
  • Runbooks, kill switch, replay → RPA

Workflow

Use for

  • Human tasks with SLAs, queues, and evidence
  • Cases with ad-hoc steps (pair with CMMN)
  • Approvals and escalations with audit trails

Design notes

  • Model with BPMN 2.0; events, gateways, lanes (OMG spec)
  • For case work, use CMMN (OMG CMMN)
  • Externalize rules with DMN (OMG DMN)

Strengths / limits

  • Strong for roles, evidence, and SoD
  • Slower than direct system integration for pure data flow

Integration

Use for

  • System-to-system data movement and sync
  • APIs, events, ETL/ELT jobs, and data contracts
  • Near-real-time updates (events/streams) or scheduled batches

Design notes

Strengths / limits

  • Fast, scalable, testable; clear lineage
  • Needs stable schemas and API discipline

RPA

Use for

  • UI steps where no API exists and UI is stable
  • Legacy or partner portals with narrow tasks
  • Short-lived bridges while you build APIs

Design notes

  • Follow IEEE RPA definitions for scope (IEEE 2755)
  • Use reliable selectors; prefer accessibility trees / WebDriver (W3C WebDriver)
  • Small surface area; version-locked; kill switch and rollback

Strengths / limits

  • Fast to deploy; no changes to systems
  • Fragile with UI change; higher run/maintain cost than APIs

Where AI fits

Good fits

  • Classify, extract, summarize, rank, or draft from text/images
  • Agent-assist in workflow; suggestions with human approval
  • Document intelligence with confidence thresholds

Guardrails

  • Policy, prompts, retrieval, redaction
  • Logging for prompts/responses/overrides
  • Risk frameworks: NIST AI RMF (NIST)

Controls & risk

Workflow

Approvals at thresholds, SoD, immutable audit trail, evidence stored at the step.

Integration

AuthN/AuthZ, input validation, idempotency, schema versioning, monitoring, replay.

RPA

Runbooks, credential vault, selector governance, change alerts, kill switch, rollback.

Cost & operating model

Cost drivers

  • Workflow: user seats, forms, storage, approvals volume
  • Integration: API traffic, queues, data ops, reliability targets
  • RPA: bot minutes, VM/runner cost, maintenance from UI change

Run rules

  • Owners, SLOs, dashboards, alerts
  • Change windows and regression tests
  • Quarterly value review; retire low-yield bots and jobs

90-day starter

Days 0–30

  • Map the flow (BPMN); list exceptions
  • Score fit: workflow vs. integration vs. RPA
  • Baseline KPIs and KCIs

Days 31–60

  • Pick the pattern; define contracts or selectors
  • Add controls; write runbooks and rollback
  • Draft ROI and success measures

Days 61–90

  • Pilot; track cycle time, FPY, exception rate
  • Install monitoring; publish deltas
  • Plan scale; retire manual steps

References

Pick the right pattern. Prove the value. Keep control tight.

If you want a suitability scorecard and pattern picker, ask for a copy.

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