ANALYZE REVIEW ORGANIZE CATEGORIZE OUTLINE EXPLAIN
These two case studies describe how consulting teams use APQC’s Process Classification Framework (PCF) for structured gap analysis, ERP standardization, and KPI frameworks, and they provide concrete patterns you can reuse in your own process/agent frameworks.12
High-level outline
- Document 1 – Sword Group (Gap Analysis, KPIs)
- Organizational background and consulting context.1
- Use of PCF to scope engagements, define in-scope Level 1 categories, and constrain discovery.1
- Five measurement dimensions for gap analysis: process maturity, business alignment, accountability (RACI), risk management, performance measurement.1
- Data collection via interviews using SIPOC + RACI + evidence gathering; reverse-engineered process maps.1
- Maturity matrix (documentation vs compliance) with baseline at “defined”, and scorecards to visualize gaps and priorities.1
- Recommendation scorecard using a benefit vs accessibility 2×2 grid (Strategic, Quick Wins, Nice to Have, No Go).1
- KPI framework and Power BI dashboards built on PCF hierarchy for another client.1
- Lessons learned: securing buy-in, avoiding scope creep, maintaining data quality and auditing methodology.1
- Document 2 – Pearson (ERP & Standardization)
- Pearson’s ERP challenge: multiple regions, different consultants, divergent process mappings.2
- PCF selected as neutral, research-based standard to harmonize finance and operations processes across regions.2
- 3DS methodology: diagnose → design → deliver → sustain, owned respectively by project management, process engineering, change management.2
- Global Process Excellence Workshop with scope document, stakeholder mapping, and collaborative process mapping using the PCF (starting at section 8.0 finance).2
- Use of workshop artifacts: aligned process hierarchy, target operating model, action item list (with PCF IDs, owners, priorities), and metrics.2
- Implementation tracking: action-item status dashboards and metric tracking against baseline.2
- Outcomes: reduced and aligned R2R processes (e.g., 27 → 21), common language, and a pattern Pearson plans to extend to curriculum and operations sections of PCF.2
Categorization and structure
You can think of both documents as instances of four recurring categories:
- Reference framework usage
- Assessment and gap analysis mechanics
- Governance and execution
- Visualization and decision tooling
Cross-document comparison
| Aspect | Sword Group case study | Pearson case study |
|---|---|---|
| Primary driver | Process capability gaps and KPI framework for clients.1 | ERP consolidation and process standardization across regions.2 |
| Methodology backbone | PCF + five-dimension maturity model + scorecards.1 | PCF + 3DS (diagnose/design/deliver/sustain) + workshops.2 |
| Scope mechanism | Level-1 PCF categories used to bound analysis.1 | Section 8.0 (finance) PCF + workshop scope document.2 |
| Prioritization scheme | Benefit vs accessibility 2×2, Strategic vs Quick Wins etc.1 | Action list with priorities (high/medium/low) and dependencies.2 |
| Outputs/artifacts | Process maps, maturity scorecards, recommendation scorecards, KPI dashboards.1 | Standardized process hierarchy, target maps, action items, metrics, monitoring dashboards.2 |
| Key challenges | Buy-in, scope creep, data quality and auditability.1 | Fragmented processes, multiple consultants, change adoption across regions.2 |
Reusable patterns (explanation)
From an agentic / process-framework perspective, these documents give you several reusable patterns:
- Use a neutral taxonomy as “map + compass”
- Separate dimensions of “good”
- Sword’s five dimensions let you distinguish “well-defined but misaligned” from “high-value but immature.”1
- This is directly portable to multi-agent evaluation: separate dimensions for policy clarity, alignment with business metrics, governance, risk, and telemetry.
- Baseline + gap + roadmap as a pipeline
- Workshop/interaction model
- Pearson’s workshop shows an effective “human-in-the-loop” pattern: educate on framework, collaboratively map, then formalize outputs as PCF-aligned artifacts.2
- In an agentic system this maps to: ontology priming → collaborative planning sessions → structuring outputs into standardized schemas (e.g., JSON process graphs with IDs).
Suggested follow-up prompts
Given your use case, these tight prompts should help you drive next iterations:
- For extracting a structured model from these PDFs
- “From the Sword and Pearson PCF case studies, extract a normalized schema for ‘process assessment’ including dimensions, scales, artifacts, and workflow stages, and return it as a JSON schema suitable for implementation.”
- For mapping to an agentic operating model
- “Using the PCF-based methodologies in the Sword and Pearson case studies, design an agentic multi-agent architecture where agents assume roles for diagnose/design/deliver/sustain, including evaluation metrics for each stage.”
- For building a gap-analysis engine
- “Derive an algorithmic procedure for process maturity and gap analysis based on the Sword case study’s five dimensions and scorecards, and express it as stepwise pseudocode suitable for implementation in Python.”
- For KPI and dashboard design
- “From the Sword KPI framework and Pearson monitoring approach, define a generalized telemetry and dashboard model for process and agent performance, including recommended KPIs and data structures.”
- For buy-in and governance patterns
- “Summarize the buy-in, scope control, and governance tactics described in both case studies, and translate them into design principles for rolling out a process framework in a multi-tenant SaaS product.”
If you specify which of these directions you want to go first (schema design, agent roles, algorithms, or governance), the next step can be a focused extraction from the PDFs into implementation-ready structures.
⁂
Data collection via interviews using SIPOC + RACI + evidence gathering; reverse-engineered process maps. For extracting a structured model from these PDFs
“From the Sword and Pearson PCF case studies, extract a normalized schema for ‘process assessment’ including dimensions, scales, artifacts, and workflow stages, and return it as a JSON schema suitable for implementation.” For mapping to an agentic operating model “Using the PCF-based methodologies in the Sword and Pearson case studies, design an agentic multi-agent architecture where agents assume roles for diagnose/design/deliver/sustain, including evaluation metrics for each stage.” For building a gap-analysis engine “Derive an algorithmic procedure for process maturity and gap analysis based on the Sword case study’s five dimensions and scorecards, and express it as stepwise pseudocode suitable for implementation in Python.” For KPI and dashboard design “From the Sword KPI framework and Pearson monitoring approach, define a generalized telemetry and dashboard model for process and agent performance, including recommended KPIs and data structures.” For buy-in and governance patterns “Summarize the buy-in, scope control, and governance tactics described in both case studies, and translate them into design principles for rolling out a process framework in a multi-tenant SaaS product.”
Below are the five deliverables synthesized from both case studies, structured for direct implementation in a multi-agent agentic platform.
1. Normalized JSON Schema for Process Assessment
The schema integrates Sword's five-dimension maturity model, SIPOC/RACI data collection, and Pearson's 3DS workflow stages into a single, implementation-ready structure.34
{
"$schema": "https://json-schema.org/draft/2020-12/schema",
"$id": "https://coditect.io/schemas/process-assessment/v1",
"title": "ProcessAssessment",
"type": "object",
"required": ["id", "pcfReference", "assessmentDimensions", "artifacts", "workflowStage"],
"properties": {
"id": { "type": "string", "format": "uuid" },
"pcfReference": {
"type": "object",
"properties": {
"level": { "type": "integer", "minimum": 1, "maximum": 5 },
"categoryId": { "type": "string", "pattern": "^[0-9]+\\.[0-9]+(\\.[0-9]+)*$" },
"categoryName": { "type": "string" },
"industryVariant": { "type": "string" }
},
"required": ["level", "categoryId", "categoryName"]
},
"assessmentDimensions": {
"type": "object",
"properties": {
"processMaturity": {
"properties": {
"documentation": { "enum": ["none", "draft", "approved", "reviewed"] },
"compliance": { "enum": ["not_performed", "informal", "compliant", "measured"] },
"maturityLevel": { "enum": ["initiate", "defined", "managed", "optimized"] }
}
},
"businessAlignment": {
"properties": {
"businessImportance": { "type": "integer", "minimum": 1, "maximum": 5 },
"alignmentGap": { "type": "integer", "minimum": -4, "maximum": 4 }
}
},
"accountability": {
"properties": {
"raciDefined": { "type": "boolean" },
"raciChart": { "type": "array" },
"governanceScore": { "type": "integer", "minimum": 0, "maximum": 5 }
}
},
"riskManagement": {
"properties": {
"riskIdentified": { "type": "boolean" },
"riskValuation": { "enum": ["none", "qualitative", "quantitative"] },
"responseCapability": { "enum": ["none", "reactive", "proactive", "predictive"] }
}
},
"performanceMeasurement": {
"properties": {
"kpiCount": { "type": "integer" },
"kpisDefined": { "type": "array" }
}
}
}
},
"sipocData": {
"properties": {
"suppliers": { "type": "array" },
"inputs": { "type": "array" },
"processSteps": { "type": "array" },
"outputs": { "type": "array" },
"customers": { "type": "array" }
}
},
"artifacts": {
"properties": {
"processMap": { "type": "string", "format": "uri" },
"maturityScorecard": { "type": "string", "format": "uri" },
"actionItems": {
"type": "array",
"items": {
"properties": {
"id": { "type": "string" },
"pcfRef": { "type": "string" },
"description": { "type": "string" },
"owner": { "type": "string" },
"priority": { "enum": ["high", "medium", "low"] },
"status": { "enum": ["not_yet_started", "in_progress", "completed", "abandoned", "parking_lot"] }
}
}
}
}
},
"workflowStage": { "enum": ["diagnose", "design", "deliver", "sustain"] },
"recommendations": {
"type": "array",
"items": {
"properties": {
"benefit": { "type": "integer", "minimum": 1, "maximum": 5 },
"accessibility": { "type": "integer", "minimum": 1, "maximum": 5 },
"quadrant": { "enum": ["strategic_initiative", "quick_win", "nice_to_have", "no_go"] }
}
}
}
}
}
2. Agentic Multi-Agent Architecture (3DS Roles)
Maps the 3DS methodology to specialized agents, each with distinct responsibilities and evaluation metrics derived from both case studies.43
| Agent Role | 3DS Stage | Responsibilities | Evaluation Metrics |
|---|---|---|---|
| DiagnoseAgent | diagnose | Scope definition via PCF Level-1 selection; SIPOC/RACI extraction from interviews/docs; evidence collection and audit trail | Coverage of PCF categories scoped, SIPOC completeness %, evidence corroboration rate 3 |
| DesignAgent | design | Maturity assessment across 5 dimensions; gap analysis; process map generation; recommendation scoring (benefit × accessibility) | Maturity assessments completed, alignment-gap accuracy, recommendation quadrant distribution 3 |
| DeliverAgent | deliver | Action item generation with PCF refs and owners; priority assignment (high/30d, medium/60d, low/90d); change communication | Action items generated, priority distribution, owner assignment coverage 4 |
| SustainAgent | sustain | Action item tracking (status transitions); KPI monitoring against baselines; intervention triggers for stalled items | Action item completion rate, KPI variance from target, intervention frequency 4 |
| OrchestratorAgent | all | Stage transitions; scope boundary enforcement; multi-tenant isolation; handoff coordination | Stage transition latency, scope creep incidents, inter-agent message throughput |
Agent interaction protocol
DiagnoseAgent → emits: ScopeDefinition, SIPOCCollection, EvidenceBundle
DesignAgent → consumes: ScopeDefinition, SIPOCCollection
→ emits: MaturityAssessment, GapAnalysis, RecommendationScorecard
DeliverAgent → consumes: GapAnalysis, RecommendationScorecard
→ emits: ActionItemList, CommunicationPlan
SustainAgent → consumes: ActionItemList
→ emits: StatusUpdate, InterventionAlert, KPIReport
3. Gap Analysis Algorithm (Python Pseudocode)
Derived from Sword's five-dimension maturity matrix, benefit-accessibility scoring, and prioritization logic.3
from enum import IntEnum
from dataclasses import dataclass
from typing import List
class Documentation(IntEnum):
NONE = 0
DRAFT = 1
APPROVED = 2
REVIEWED = 3
class Compliance(IntEnum):
NOT_PERFORMED = 0
INFORMAL = 1
COMPLIANT = 2
MEASURED = 3
class MaturityLevel(IntEnum):
INITIATE = 0
DEFINED = 1
MANAGED = 2
OPTIMIZED = 3
MATURITY_MATRIX = {
(Documentation.NONE, Compliance.NOT_PERFORMED): MaturityLevel.INITIATE,
(Documentation.DRAFT, Compliance.INFORMAL): MaturityLevel.INITIATE,
(Documentation.APPROVED, Compliance.COMPLIANT): MaturityLevel.DEFINED,
(Documentation.REVIEWED, Compliance.COMPLIANT): MaturityLevel.MANAGED,
(Documentation.REVIEWED, Compliance.MEASURED): MaturityLevel.OPTIMIZED,
}
MATURITY_BASELINE = MaturityLevel.DEFINED
@dataclass
class ProcessAssessment:
pcf_id: str
documentation: Documentation
compliance: Compliance
business_importance: int # 1-5
raci_defined: bool
risk_identified: bool
kpi_count: int
def compute_maturity(doc: Documentation, comp: Compliance) -> MaturityLevel:
"""Lookup maturity from documentation × compliance matrix."""
return MATURITY_MATRIX.get((doc, comp), MaturityLevel.INITIATE)
def compute_alignment_gap(importance: int, maturity: MaturityLevel) -> int:
"""Gap = importance - maturity; positive = under-invested."""
return importance - int(maturity)
def compute_priority_score(gap: int, importance: int) -> float:
"""Priority weighted by gap magnitude and business importance."""
return gap * importance
def assess_process(p: ProcessAssessment) -> dict:
maturity = compute_maturity(p.documentation, p.compliance)
gap = compute_alignment_gap(p.business_importance, maturity)
priority = compute_priority_score(gap, p.business_importance)
below_baseline = maturity < MATURITY_BASELINE
return {
"pcf_id": p.pcf_id,
"maturity_level": maturity.name,
"alignment_gap": gap,
"priority_score": priority,
"below_baseline": below_baseline,
"accountability_score": 5 if p.raci_defined else 0,
"risk_score": 3 if p.risk_identified else 0,
"measurement_score": min(p.kpi_count, 5),
}
def classify_recommendation(benefit: int, accessibility: int) -> str:
"""2x2 quadrant classification per Sword model."""
if benefit >= 3 and accessibility >= 3:
return "quick_win"
elif benefit >= 3 and accessibility < 3:
return "strategic_initiative"
elif benefit < 3 and accessibility >= 3:
return "nice_to_have"
else:
return "no_go"
def run_gap_analysis(processes: List[ProcessAssessment]) -> List[dict]:
results = [assess_process(p) for p in processes]
return sorted(results, key=lambda x: -x["priority_score"])
4. Telemetry and Dashboard Model (KPIs + Data Structures)
Combines Sword's Power BI hierarchy approach with Pearson's action-item tracking charts.43
Recommended KPIs
| KPI Category | Metric | Source | Aggregation |
|---|---|---|---|
| Process Performance | Cycle time, Efficiency ratio, Staffing utilization | Sword KPI framework 3 | Per PCF category, drillable by level |
| Maturity Distribution | % processes at each maturity level | Maturity scorecard 3 | Histogram across PCF scope |
| Alignment Gap | Avg gap by PCF category | Gap analysis 3 | Heat map |
| Action Item Velocity | Completion rate, Avg days to close | Pearson tracking 4 | Time series by priority |
| Action Item Status | Counts by status (not started, in-progress, completed, abandoned, parking lot) | Pearson tracking 4 | Pie chart + priority pivot |
Data structures for dashboards
{
"telemetryEvent": {
"eventType": "process_assessment | action_item_update | kpi_snapshot",
"timestamp": "ISO8601",
"tenantId": "string",
"pcfRef": "string",
"payload": {}
},
"kpiSnapshot": {
"pcfRef": "8.1.1.2",
"kpiName": "cycle_time",
"baseline": 5.0,
"target": 3.0,
"current": 4.2,
"unit": "days",
"timestamp": "ISO8601"
},
"actionItemStatus": {
"itemId": "string",
"pcfRef": "string",
"priority": "high | medium | low",
"status": "not_yet_started | in_progress | completed | abandoned | parking_lot",
"ownerEmail": "string",
"dueDate": "date",
"lastUpdated": "ISO8601"
}
}
Dashboard hierarchy (PCF-based)
Level 1 (Category) → Level 2 (Process Group) → Level 3 (Process) → Level 4 (Activity)
└─ KPIs attached here
5. Buy-in, Scope Control, and Governance Design Principles
Distilled from challenges and lessons learned in both case studies, translated for multi-tenant SaaS rollout.34
Buy-in tactics → SaaS design principles
| Case Study Tactic | SaaS Design Principle |
|---|---|
| Explain/educate on external framework value 3 | Onboarding wizard with interactive PCF explainer and tenant-specific vocabulary mapping |
| Adapt vocabulary to customer context 3 | Tenant-configurable terminology layer over canonical PCF taxonomy |
| Use neutral location/facilitator 4 | Collaborative workspace (shared canvas) with role-based access; no single-region bias |
| Stakeholder scope document with explicit sign-off 4 | Digital scope contract with version history, e-signatures, and change-log audit |
Scope control tactics → SaaS design principles
| Case Study Tactic | SaaS Design Principle |
|---|---|
| Define breadth/depth upfront using PCF levels 3 | Scope boundary enforcement at config time (select PCF levels 1–N); alerts on out-of-scope activities |
| Reuse existing process docs when available 3 | Import/sync from BPM tools (Signavio, ARIS, Camunda) with auto-alignment to PCF |
| Clarify scope in contracts/statements 4 | Embedded scope attestation in project initiation flow; immutable once approved |
Governance tactics → SaaS design principles
| Case Study Tactic | SaaS Design Principle |
|---|---|
| RACI as explicit assessment dimension 3 | RACI-as-code in tenant config; enforced ownership validation before stage transitions |
| Monthly/quarterly review cadence 4 | Automated review reminders and SustainAgent-triggered escalations based on KPI variance |
| Audit methodology for data quality 3 | Evidence provenance tracking; immutable audit log per assessment with corroboration links |
| Single governance model for process, data, systems 4 | Unified policy engine (OPA/Cedar) with PCF-scoped policy bindings per tenant |
Next-step prompts (focused extraction)
- Schema validation and extension "Generate TypeScript interfaces and Zod validators from the ProcessAssessment JSON schema, including tenant-aware factory functions."
- Agent implementation scaffold "Produce a LangGraph or CrewAI agent graph definition for the 3DS multi-agent architecture, with state transitions and tool bindings for each agent role."
- Gap analysis engine integration "Wrap the gap analysis algorithm in a FastAPI service with OpenAPI spec, supporting batch assessment and streaming scorecard updates."
- Dashboard prototype "Design a Grafana or Metabase dashboard configuration JSON for the telemetry model, with PCF hierarchy navigation and action-item status panels."
⁂
Data collection via interviews using SIPOC + RACI + evidence gathering; reverse-engineered process maps. DESCRIBE THIS PROCESS IN DETAIL STEP BY STEP
The data collection process is a structured interview- and evidence-driven pipeline that moves from scoping, through SIPOC/RACI capture, to reverse‑engineered process maps and maturity inputs.5
1. Prepare scope and interview design
- Use PCF Level‑1 categories in scope to define which processes and functions you will investigate at Company A.5
- Derive an interview guide that explicitly covers SIPOC elements, RACI roles, and the five measurement areas (process design, documentation, roles, risk, tools, KPIs, business contribution).5
2. Select interviewees and plan sessions
- Identify interviewees at different levels and areas of the business so you see end‑to‑end value chains, not just local steps.5
- Schedule sessions so that for each in‑scope process you have representation from owners, performers, upstream/downstream stakeholders, and governance roles.5
3. Conduct SIPOC‑oriented interviews
- For each process in scope, elicit SIPOC data: suppliers, inputs, high‑level process steps, outputs, and customers.5
- Capture this in a structured template so you can later compare perceptions across interviewees and reconcile discrepancies.5
4. Capture RACI and governance details
- For each process, ask who is Responsible, Accountable, Consulted, and Informed, and how this is documented today.5
- Record whether formal RACI charts exist and note gaps or overlaps in ownership that might signal governance issues.5
5. Gather corroborating evidence
- Request documents and data that support interview statements: procedures, process descriptions, logs, reports, audit trails, and system screenshots.5
- Treat this as an auditing step: cross‑check statements about how work is done with actual records to enable objective data analysis.5
6. Drill down on key process aspects
- Use follow‑up questions on:
- Process design and execution transactions (how work flows in practice).5
- Process documentation, maintenance, and audit cycles.5
- Roles and responsibilities in more detail than the high‑level RACI (who actually does what).5
- Risk management practices (identification, valuation, response to unforeseen events).5
- Applicable tools and techniques (systems, applications, methods).5
- Existing KPIs and measurements (definitions, baselines, usage).5
- Contribution of the process to business objectives and perceived importance.5
7. Consolidate interview and evidence data
- Aggregate SIPOC, RACI, and evidence into a structured dataset per process category to eliminate duplication and resolve conflicting accounts.5
- Normalize terminology to the PCF categories so that local names and variants are mapped to a common process language.5
8. Reverse‑engineer process maps
- Using the consolidated SIPOC and transaction-level insights, reconstruct end‑to‑end process maps for each in‑scope category.5
- Ensure that maps reflect both the formal process and how work is actually performed, adjusting where evidence contradicts documented procedures.5
9. Feed maturity and gap analysis
- Take the documented vs executed flows, governance, risk, tools, KPIs, and business contribution data as inputs to the five measurement categories.5
- Use these structured inputs to populate the documentation–compliance maturity matrix and subsequent scorecards for each process.5
⁂
DESCRIBE EACH COMPONENT IN DETAIL OF SIPOC
A SIPOC is a high-level way to describe a process by explicitly naming who provides what, what happens, what comes out, and who receives it. Each component focuses on a different aspect of how value flows through the system.78
Suppliers (S)
- Suppliers are the internal or external parties that provide what the process needs to run, such as departments, teams, systems, vendors, or customers themselves.910
- They can be people, organizations, or technology services that directly impact the quality, timing, and availability of inputs (for example: HR as supplier of employee data, an API service as supplier of transaction events).11
Inputs (I)
- Inputs are the resources consumed or transformed by the process, including materials, data, triggers, tools, and specifications.127
- Typical input types include information (forms, requests, tickets), physical resources, systems access, and roles or skills needed for the process steps to execute successfully.1312
Process (P)
- The process is the set of 5–7 high-level activities that convert inputs into outputs, described at a coarse-grained level rather than detailed task steps.1013
- It usually includes a defined start and end point, with each step specifying what is done, in what sequence, and by whom, but without going into detailed work instructions or technical implementation.1410
Outputs (O)
- Outputs are the products, services, decisions, or data produced by the process that have value for customers or downstream processes.87
- They include both primary deliverables (for example, an approved contract or shipped product) and secondary artifacts (notifications, reports, logs), and their quality and completeness are what customers ultimately experience.1511
Customers (C)
- Customers are the recipients or beneficiaries of the outputs, and can be internal roles (next process in the chain, other departments) or external users and organizations.78
- Understanding customers clarifies whose requirements define “success” for the process, and is often used to bring VOC/requirements directly into process design or improvement work (for example, COPIS variants explicitly start from the customer).815
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How to write detailed examples for each SIPOC component
Common mistakes when defining SIPOC inputs and suppliers How to map process steps for a complex workflow How SIPOC integrates with RACI for roles and responsibilities Templates for SIPOC diagrams in Excel or PowerPoint
Below is a concise, implementation-focused guide you can lift into docs, with examples and anti-patterns.
1. Writing detailed SIPOC examples
Suppliers – how to write examples
- Be explicit and granular enough that ownership is clear.
- Example for an incident-management process:
Inputs – how to write examples
- Describe inputs as concrete artifacts or signals, not vague “information”.19
- Example for the same process:
Process – how to write examples
- Receive and log incident.
- Triage and assign severity.
- Diagnose root cause.
- Implement workaround or fix.
- Validate resolution and update ticket.
- Communicate with customer and close ticket.21
Outputs – how to write examples
- Tie outputs to what customers actually perceive as value.22
- Example outputs:
Customers – how to write examples
2. Common mistakes for Suppliers & Inputs
Typical mistakes
- Confusing inputs with outputs: e.g., listing “approved invoice” as input when it is the result of the process.21
- Listing roles as inputs: people are usually suppliers; what they provide (form, data, decision) is the input.2419
- Missing critical stakeholders: ignoring regulators, supporting functions, or downstream teams as suppliers/customers.25
- Too generic inputs: “data”, “documents” instead of “customer onboarding form v3, JSON schema X”.26
- Over-detailing inputs: capturing every field instead of grouping into logical artifacts, which clutters a high-level map.2625
How to avoid them
- Validate each input with: “Is this consumed by a process step, and who provides it?”.19
- Run a quick stakeholder review: “Who is missing that can block or veto this process?”.25
3. Mapping process steps for complex workflows
- Start with clear start/end boundaries: define the trigger event and the final value outcome.19
- Cluster detailed activities into 5–7 macro-steps using value-chain segments (e.g., capture → decide → fulfill → settle).2521
- For each macro-step, ensure:
- For very complex flows, build multiple SIPOCs for sub-processes rather than one giant diagram.25
4. Integrating SIPOC with RACI
- Use SIPOC to identify what happens and which entities are involved, then overlay RACI to define who plays which role.27
- Practical sequence:
- Build SIPOC with process steps (P column).19
- For each step, list involved roles from Suppliers/Customers columns and internal stakeholders.27
- Create a RACI matrix where rows = process steps, columns = roles; assign R, A, C, I per step.2827
- Checks: every step must have at least one Responsible and one Accountable; avoid multiple Accountables per step.2928
5. Templates for SIPOC in Excel / PowerPoint
You can implement generic templates quickly:
Excel layout (one-sheet SIPOC)
- Columns:
Suppliers | Inputs | Process Step 1..N | Outputs | Customers.30 - Rows: each row represents a logical grouping or scenario; use merged cells for multi-line process descriptions.30
- Add a header row for project name, scope, and date; optionally a column for key metrics (SLA, defect rate).22
PowerPoint layout
- Use a 5-column table:
S | I | P | O | Cacross the slide.2230 - Under
P, create numbered bullets 1–7 for the high-level steps; use concise phrasing.21 - For workshops, use one slide per process and treat each cell like a sticky-note area where participants contribute items.19
If you share your target process (e.g., “multi-tenant SaaS customer onboarding”), a next step could be a concrete SIPOC with fully populated examples plus an aligned RACI grid you can drop into your design docs.
⁂
Provide a template for detailed SIPOC examples per component
Checklist to avoid mistakes when listing suppliers and inputs Step-by-step method to map complex process steps How to combine SIPOC and RACI in one workshop agenda Example interview questions to elicit SIPOC inputs and suppliers
Below is a compact, copy-pastable toolkit addressing each of your bullets.
1. Template for detailed SIPOC examples
Use this structure per process; each cell should have concrete, domain-specific entries.3637
Process name:
Scope (start → end):
Date / Owner:
S – Suppliers
- [Org/Team/System]: what they provide, frequency, interface
- ...
I – Inputs
- [Artifact/Data/Trigger]: format, minimal fields, source, quality criteria
- ...
P – High-level Process Steps (5–7)
1. [Verb + object] – key purpose, main actors, main systems
2. ...
N. ...
O – Outputs
- [Deliverable/Result]: format, consumer, quality/timeliness expectations
- ...
C – Customers
- [Role/Org]: what they need, how they consume the output, key CTQs
- ...
Optional add-ons per row: key metrics (CTQs), systems, risks.36
2. Checklist to avoid supplier/input mistakes
Use this quick checklist when reviewing S and I.383936
Suppliers
[ ] Each supplier is an entity (team, org, system, vendor), not a document or dataset.
[ ] For every input listed, at least one supplier is explicitly named.
[ ] Both internal and external suppliers are considered (incl. upstream departments, platforms, regulators).
[ ] No customer is incorrectly listed as supplier unless they truly provide an input (e.g., order form).
Inputs
[ ] Every input is something consumed or transformed by a process step (data, material, trigger, tooling).
[ ] Inputs are described concretely (e.g., “onboarding form v3 JSON” not “customer data”).
[ ] Inputs are not future outputs of the same process (avoid “approved X” as an input).
[ ] Non-essential noise is removed; only critical inputs for successful execution are listed.
[ ] For each input, acceptance criteria or quality expectations are known (even if not shown on SIPOC).
3. Step‑by‑step method to map complex process steps
A simple 7-step method you can reuse.404136
1) Define boundaries
- Start event: what triggers the process?
- End condition: what must be true to consider it complete?
2) List detailed activities
- Brain-dump all tasks (from procedures, SMEs, logs).
- Don’t worry about order yet.
3) Cluster into value stages
- Group tasks into 4–7 logical stages (e.g., Capture → Decide → Fulfill → Settle).
- Each cluster should represent a distinct value transformation.
4) Name macro-steps
- For each cluster, define a verb + object name (“Validate application”, “Provision environment”).
- Ensure each macro-step has at least one input and one output.
5) Order the macro-steps
- Arrange steps in true execution order; handle loops by naming them in the dominant happy-path.
6) Validate against SIPOC
- For each macro-step, confirm:
• At least one input exists in I.
• At least one output either feeds the next step or appears in O.
- Add missing inputs/outputs if needed.
7) Sanity-check with stakeholders
- Ask: “Can someone unfamiliar with the process understand the flow from this alone?”
- Reduce or split if you have more than ~7 macro-steps; consider sub-process SIPOCs.
4. How to combine SIPOC and RACI in one workshop agenda
You can run a ½–1 day workshop using this skeleton.4243
0. Pre-work (offline)
- Facilitator drafts initial SIPOC (v0.1) from existing docs.
- Identify candidate roles (functions) for RACI.
Workshop Agenda (4–6 hours)
1) Introduction (15–30 min)
- Objectives, scope, start/end of process.
- Brief refresher on SIPOC + RACI and how they will be used together.
2) SIPOC refinement (1.5–2 hours)
- Validate boundaries (trigger, end-state).
- Group exercise: refine Suppliers, Inputs, Outputs, Customers.
- Map/confirm 5–7 high-level Process steps.
- Outcome: agreed SIPOC v1.0.
3) Break (15 min)
4) Build RACI on top of SIPOC (1.5–2 hours)
- List roles/teams on whiteboard (columns).
- Use SIPOC “Process” steps as RACI rows.
- For each step: assign R, A, C, I with the rule “exactly one A; at least one R”.
- Challenge any step with unclear or multiple A’s.
5) Gaps and actions (30–45 min)
- Identify steps with missing R/A or overloaded roles.
- Capture actions: clarify ownership, adjust org/roles, update procedures.
6) Close (15–30 min)
- Confirm next steps: finalize artifacts, circulate SIPOC + RACI, integrate into process docs/tooling.
5. Example interview questions (Suppliers & Inputs)
These are phrased to be dropped directly into an interview guide.444546
To identify Suppliers
- “Who performs the very first task when this process starts?”46
- “Which teams/systems provide the data or materials you need before you can begin?”3846
- “If their data or materials are late or wrong, who would you contact to fix it?”44
- “Are there external vendors, partners, or customers who send you anything you rely on?”38
To identify Inputs
- “What specific documents, forms, or files must you have before you can proceed?”4036
- “In what format do you receive this information (tool, file type, API payload)?”38
- “What are the minimum fields or attributes you check before you accept an input?”36
- “Can you recall recent cases where missing or poor-quality inputs caused issues? What exactly was missing?”37
If you share a concrete process (e.g., “multi-tenant SaaS onboarding”), the next iteration can be a filled-in SIPOC + RACI-ready workshop agenda tailored to that domain.
⁂
DESCRIBE THE RACI concept in detail step by step with definitions of each component and how to apply
RACI is a responsibility-assignment model that clarifies who does the work, who owns the outcome, who must be consulted, and who is kept informed for each task or deliverable. It is typically represented as a matrix with tasks as rows and roles as columns.565758
1. Core concepts and definitions
RACI is an acronym for Responsible, Accountable, Consulted, Informed.5856
- Responsible (R)
- Accountable (A)
- Consulted (C)
- Informed (I)
2. Step‑by‑step: how to build a RACI
Step 1 – Identify scope and tasks
- Define the scope: which project, process, or initiative you are mapping (e.g., “customer onboarding”, “feature release”).6162
- List the key tasks, activities, or decision points as rows: requirements, design, implementation, testing, approval, rollout, etc.61
Step 2 – Identify roles / stakeholders
- List roles or stakeholder groups as columns: e.g., Product Manager, Tech Lead, Developer, QA, Security, Legal, Operations, Customer Success.6362
- Use roles or functions (not individual names) for matrices that must stay stable over time.64
Step 3 – Create the matrix structure
- Build a table where:
- Rows = tasks/deliverables.
- Columns = roles.
- The cell at (task, role) will contain one of R, A, C, or I (or be blank if the role is not involved).6264
Step 4 – Assign RACI roles per task
For each task:
- Ask “Who actually does the work?” → mark R for those roles.58
- Ask “Who ultimately owns the outcome and approves it?” → mark A (exactly one).6058
- Ask “Who needs to be consulted because they have expertise or are impacted?” → mark C.56
- Ask “Who needs to be kept informed of progress or completion?” → mark I.56
Best‑practice rules:
- Every task has at least one R.5958
- Every task has exactly one A to avoid decision ambiguity.6458
- Keep Cs and Is to the minimum needed to avoid communication overload.60
Step 5 – Review and balance
- Check each row: ensure R and A are present and that A is not duplicated.6258
- Check each column: make sure no role is overloaded with Rs or completely missing across critical tasks.6058
- Adjust assignments where necessary so responsibilities are realistic and aligned with authority and expertise.60
Step 6 – Validate with stakeholders
- Walk through the matrix with the team and sponsors, verifying that everyone agrees on their role for each key task.6162
- Clarify any disagreements (e.g., two roles claiming to be Accountable) before finalizing.61
Step 7 – Use it operationally
- Incorporate the RACI into project plans, process documentation, onboarding materials, and change-management communications.5764
- Refer to it during status meetings and escalations: “Who is A for this task?”; “Who should we consult?”, “Who needs to be informed?”.5760
3. Applying RACI in practice
For projects
- Use RACI to define ownership for milestones: project charter, architecture decisions, security review, UAT sign‑off, release go/no‑go.6561
- This reduces confusion in cross-functional teams and speeds up decision-making by clarifying who can decide and who must be consulted.6160
For recurring processes
- Apply RACI to stable processes (e.g., incident management, change management, onboarding) so that everyone knows their standing responsibilities.6456
- Combine with SIPOC:
For governance and escalation
- When an issue arises, use the matrix to locate the A for the affected task; this is the person who must resolve conflicts or make trade-offs.6061
- For cross-team changes, RACI ensures all Cs are looped in early and all Is receive updates after decisions, reducing rework and resistance.6260
If you want, the next step can be a concrete RACI matrix for a specific process you’re working on (e.g., “multi-tenant SaaS onboarding” or “AI model release pipeline”) in a table you can paste directly into your docs.
⁂
When should you use RACI versus other responsibility models
How to map RACI roles to my project team members Examples of RACI for a product launch project How to handle tasks with multiple Responsible people Best practices to avoid RACI anti patterns and conflicts
RACI is best for clarifying execution ownership per task; variants or other models are better once you move into complex decision rights. Below is a concise guide covering your five angles.
1. When to use RACI vs other models
Use RACI when:
- You need clarity on who does what for many tasks or deliverables in a project or process.7071
- The main pain is operational ambiguity: duplicated effort, dropped balls, or “I thought they owned it.”70
Prefer DACI / RAPID / DDDI / RASCI when:
- You are mainly clarifying decisions, not day‑to‑day work (e.g., strategy, roadmap trade‑offs) → DACI, RAPID.7270
- You have many stakeholders and high‑stakes decisions needing explicit Recommend / Input / Decide / Execute separation → RAPID.7270
- You need an explicit “Support” role (people who provide resources but don’t own the task) → RASCI, RASCI for large cross‑functional projects.7374
Rule of thumb:
2. Mapping RACI roles to your project team
- List work items
- Take your WBS / backlog / process steps and list key tasks or deliverables (rows).76
- List roles, then people
- Assign A first
- Assign R next
- Ask: “Who actually does the work?” → mark Responsible.78
- This may be the same as A for small teams, or different (e.g., Dev is R, Tech Lead is A).
- Then C and I
- Review and balance
3. Example: RACI for a product launch
Illustrative matrix for a B2B SaaS launch (roles simplified).8081
Roles:
- PM = Product Manager
- PL = Engineering / Tech Lead
- MKT = Marketing Lead
- SALES = Sales Lead
- CS = Customer Success Lead
| Task / Deliverable | PM | PL | MKT | SALES | CS |
|---|---|---|---|---|---|
| Define launch goals & KPIs | A/R | C | C | C | C |
| Finalize value proposition & messaging | A | C | R | C | C |
| Launch readiness checklist | A | R | C | C | C |
| Build/ship launch features | C | A | I | I | I |
| Create marketing assets (LP, email) | C | I | A/R | I | I |
| Enablement deck & sales training | C | I | C | A/R | C |
| Day‑one support playbook | C | C | I | C | A/R |
| Launch go/no‑go decision | A | C | C | C | C |
| Post‑launch KPI dashboard | A | C | C | C | C |
This pattern matches real-world SaaS launch templates where RACI clarifies which team leads what across marketing, product, sales, and CS.8280
4. Handling tasks with multiple “Responsible” people
Multiple Rs are acceptable but must be structured.
- It is fine to have several Rs for large tasks (e.g., “Develop features” with multiple developers).
- Ensure there is one coordinating R or an A who can deconflict and aggregate the work (e.g., Tech Lead as A or lead R).7978
- Avoid “everyone is R” patterns: if a role has many Rs but no clear lead, split the task into smaller items or designate a sub‑owner (R1 owns backend, R2 owns frontend, etc.).79
- When many Rs exist, make explicit how they coordinate (standups, tickets, ownership of sub‑tasks) outside the RACI matrix.
Practical rule:
- Many Rs are okay, many As are not. You can scale Rs if there is one clear A and a clear breakdown of work.7879
5. Best practices to avoid RACI anti‑patterns and conflicts
Common pitfalls and how to avoid them:837879
- Pitfall: Multiple Accountables per task
- Pitfall: Too many Consulted (C overload)
- Pitfall: RACI as a one‑time static artifact (“set and forget”)
- Pitfall: Assigning roles without team input
- Pitfall: Overly detailed tasks in RACI
- Pitfall: No link to real workflows
If you share your actual team structure (roles) and a brief task list for an upcoming launch or project, a next step can be a tailored RACI matrix plus a short “usage protocol” you can drop into your internal playbook.
⁂
Prefer DACI / RAPID / DDDI / RASCI break each of these down in detail and their applications
These models all clarify “who does what” but each optimizes for a different kind of work, especially around decisions. Below is a compact breakdown you can plug into your governance design.
DACI
What it is DACI is a decision-making framework: Driver, Approver, Contributor, Informed. It focuses on who moves a decision forward and who has final say, more than on day‑to‑day task execution.919293
Components
- Driver (D)
- Approver (A)
- Contributors (C)
- Informed (I)
Applications
- Product decisions (e.g., “ship / slip / kill” feature decisions, roadmap trade‑offs).9493
- Cross-functional initiatives where “who decides” is ambiguous (e.g., pricing changes, partner integrations).
- Any decision where you want one person “driving” and one entity “approving,” with clear expert input.
RAPID
What it is RAPID (Bain) is a decision-accountability model: Recommend, Agree, Perform, Input, Decide. It explicitly decomposes the decision lifecycle into roles and centers on the Decide role.959697
Components
- Recommend (R)
- Agree (A)
- Perform (P)
- Input (I)
- Decide (D)
Applications
- High-stakes, cross-functional decisions: entering markets, large investments, structural org changes.9596
- Environments with many powerful stakeholders where approvals and veto rights must be explicit.
- Governance for strategy execution: mapping RAPID roles for each “big bet” decision.
DDDI
What it is DDDI is a decision-centric model emphasizing the flow of decisions in complex environments, typically called Define, Decide, Do, Input or similar variants depending on the source. It is less standardized than DACI/RAPID but serves the same purpose: making decision roles explicit and fast.98
Components (canonical pattern)
- Define
- Clarifies the problem, scope, and decision criteria.98
- Ensures everyone agrees what decision is being made and why.
- Decide
- Holds the authority to choose among options, based on the defined criteria and input.98
- Do
- Implements the decision; equivalent to Perform/Responsible roles in other models.98
- Input (sometimes integrated into Define/Decide)
- Provides data, analysis, and perspectives to inform the decision.98
Applications
- Fast-moving environments where decision clarity matters more than detailed task mapping (e.g., agile product orgs, crisis response).
- Nested decision structures: using DDDI for key decisions inside a larger process that might also use RACI for execution.98
- As a complement: RACI for work execution, DDDI for key decisions inside that work.98
RASCI
What it is RASCI extends RACI with an extra Support (S) role: Responsible, Accountable, Support, Consulted, Informed. It is still a responsibility matrix, but adds nuance for teams that provide hands‑on help without owning the work.99100
Components
- Responsible (R)
- Accountable (A)
- Support (S)
- Provide hands‑on assistance, resources, or specialized services to R (e.g., Platform team supporting application devs, Security enabling a rollout).100
- Not ultimately accountable, but materially involved in execution.
- Consulted (C)
- Informed (I)
Applications
- Cross-functional processes where some teams consistently help but don’t own tasks (e.g., shared platform, data, design, or security teams).100
- Regulated contexts where support functions (compliance, QA) are structurally separate from line ownership but heavily involved.
- Large programs where basic RACI underrepresents how enabling teams contribute.
How to choose among them (quick guide)
- Need to clarify responsibilities for tasks and process steps:
- Need to clarify who drives and approves decisions in product or project work:
- Need to manage high-stakes, multi-stakeholder decisions with explicit veto and execution roles:
- Need fast decision clarity inside a larger process, especially in agile or multi-layer orgs:
- Use DDDI for key decisions, alongside RACI/RASCI for the surrounding work.98
If you describe one of your real flows (e.g., “AI model release pipeline” or “multi-tenant SaaS onboarding”), the next iteration can be:
- a DACI mapping for roadmap decisions,
- RAPID roles for risk/approval decisions, and
- RASCI/RACI for day‑to‑day execution, all in matrix form you can drop into your governance docs.
⁂
Compare DACI and RAPID: when to choose which framework
Step-by-step template for running DACI in a product team How to map existing roles into a RAPID chart DDDI versus RASCI: pros and cons for fast decision making Examples of decisions suited to RASCI over DACI or RAPID CREATE A DECISION LOGIC MODEL FOR THE DECISION PROCESS OF WHICH to APPLY AND THE LOGIC GATES THAT INFORM THE DECISION WiTH The APPLICATION OF THE LOGIC WHY AND HOW
Below is a compact comparison plus a decision-logic model you can wire straight into governance docs or an agentic “framework selector.”
1. DACI vs RAPID: when to choose which
- You need speed and momentum on recurring cross-functional decisions (e.g., prioritizing features, choosing a vendor).
- The decision has clear ownership and relatively few formal veto points.
- You want one person driving the process (Driver) and one approver with final say (Approver).
- The decision is high-stakes and complex, with many stakeholders and formal sign-offs (legal, risk, finance).
- You need strong, explicit Agree rights (veto/gatekeeper) in addition to Input and Recommend.
- You want to clearly separate recommendation vs decision vs execution and document the sequence.
Rule of thumb (Plain English):
- “Decisions stall and we lack a driver” → DACI.109
- “Decisions are political/regulated with many vetoes” → RAPID.110109
2. Step-by-step template: running DACI in a product team
Use this pattern for a product decision (e.g., “Adopt Feature X for Q3 launch?”).112113114
- Define the decision and context
- Decision statement: “Decide whether and how to implement Feature X for Q3 release.”
- Constraints: timeline, budget, technical and regulatory constraints.
- Assign DACI roles
- Gather inputs (Driver with Contributors)
- Develop and socialize the proposal
- Driver drafts a Decision Brief: options, recommendation, rationale, risks, impact.
- Circulate to Contributors for comments and iterate until there’s a solid recommendation.
- Decision meeting with Approver
- Communicate & track
- Driver informs all Informed stakeholders; updates roadmap, docs, and tickets.
- Define follow-up: metrics to watch and timebox for revisiting decision if assumptions fail.
- Retrospect
- After implementation, quickly evaluate: did the DACI roles work; did the decision flow stall anywhere?
3. Mapping existing roles into a RAPID chart
Example: mapping for “Change pricing for Pro plan”.111116117
- List key org roles
- Product, Finance, Sales, Legal, Marketing, Operations.
- Define RAPID roles per decision
- Recommend (R)
- Who will draft the pricing recommendation?
- E.g., Product + Pricing Analyst jointly (one “R” role with named individuals).
- Input (I)
- Agree (A)
- Decide (D)
- Perform (P)
- Who executes: Billing/Operations (system changes), Marketing (communication), Product (in-app changes).
-
Create a simple table | Role | R | A | P | I | D | | :-- | :-- | :-- | :-- | :-- | :-- | | Product | X | | | | | | Pricing Analyst | X | | | | | | Finance | | X | | | | | Legal | | X | | | | | Data Science | | | | X | | | Sales Ops | | | | X | | | CS | | | | X | | | GM / VP Product | | | | | X | | Ops / Billing | | | X | | | | Marketing | | | X | | |
-
Validate with stakeholders
- Confirm each role understands what their RAPID letter means in this context.
- Adjust for culture (e.g., do you truly want both Legal and Finance as A’s?).
4. DDDI vs RASCI: pros/cons for fast decisions
DDDI (decision-centric)118
- Pros
- Very lightweight; focuses on “who defines, who decides, who does, who inputs”.
- Good for fast, iterative decision flows (e.g., agile product teams).
- Cons
- Less explicit on support/enablement roles.
- Not ideal when you also need detailed task-level accountability.
RASCI (responsibility-centric)119120
- Pros
- Strong for complex execution with many enablement teams; clarifies Support (S) vs Responsible (R).
- Helpful in regulated / enterprise environments where support functions are critical.
- Cons
- Heavier artifact; slower to update than a small decision model.
- Focuses on execution, not decision rights, so decisions can still stall if not complemented with DACI/RAPID/DDDI.
For fast decision making:
- Use DDDI when: decisions are frequent, iterative, and embedded in the team’s daily work (e.g., story-level or design trade-offs).
- Use RASCI when: the bottleneck is not the decision itself but who actually executes or supports the work once a decision is made.
5. When RASCI beats DACI/RAPID
Examples of decisions better served by RASCI (execution-heavy, decision is relatively straightforward):120119
- “Who is responsible for standing up and maintaining a new shared platform service?”
- Decision (build the platform) may already be made; challenge is allocation of R vs S across Platform, Security, and App teams.
- RASCI clarifies: Platform (R), Platform Lead (A), Security (S), Apps (C), Leadership (I).
- “Who does what in an incident response process?”
- Need clarity on who leads, who supports, who is consulted and informed, across SRE, Security, Comms, Legal.
- RASCI is better because Support (S) roles—e.g., Legal, Comms—are structurally important.
- “Who supports client onboarding in a multi-tenant SaaS?”
- Decision to onboard is already taken; complexity lies in interplay between Sales, CS, Implementation, Security, Compliance.
- RASCI spells out: CS (R), Implementation (S), Security (S/C), Compliance (C), Sales (I or C).
In all these, DACI/RAPID would be overkill; the primary need is to structure execution rather than discrete decisions.
6. Decision logic model: how to choose the framework
You can think of this as a small decision tree / logic-gate model implemented as an internal “framework selector.”108110109
Pseudocode-style logic
INPUTS:
- primary_need: "execution_clarity" | "decision_clarity"
- stakes: "low" | "medium" | "high"
- stakeholder_count: "few" | "many"
- formal_veto_needed: true | false
- support_roles_critical: true | false
- decision_frequency: "one_off" | "recurring" | "high_volume"
LOGIC:
1) If primary_need == "execution_clarity":
If support_roles_critical == true:
USE RASCI
WHY: Need to distinguish Support vs Responsible across many teams.
Else:
USE RACI
WHY: Need clear Rs and As for tasks, no complex support pattern.
2) Else if primary_need == "decision_clarity":
If stakes == "high" AND stakeholder_count == "many":
If formal_veto_needed == true:
USE RAPID
WHY: Need explicit Agree and Decide roles with traceable recommendation flow.
Else:
USE DACI
WHY: Many stakeholders but fewer formal gatekeepers; need Driver and Approver.
Else if stakes in {"medium","low"}:
If decision_frequency == "high_volume":
USE DDDI
WHY: Lightweight roles focused on Define/Decide/Do for fast, repeated decisions.
Else:
USE DACI
WHY: Simple structure to keep decisions moving with a clear Driver and Approver.
3) Optionally:
After a RAPID or DACI decision is made:
USE RACI or RASCI to map execution responsibilities for implementation.
Logic gates explained (why and how)
- Gate 1: primary_need
- Why: Distinguishes “who does the work?” vs “who decides?” problems.109
- How: Ask “Are we blocked because tasks are unclear, or because decisions stall?”
- Gate 2: stakes + stakeholder_count
- Gate 3: formal_veto_needed
- Gate 4: support_roles_critical
- Why: When enabling teams are structurally important but not owners, RASCI’s S role adds necessary nuance.120
- How: If platform, security, compliance, or design teams repeatedly “help” but don’t “own” tasks, prefer RASCI.
- Gate 5: decision_frequency
- Why: High-volume micro-decisions cannot bear RAPID’s or even DACI’s overhead; DDDI is lighter.118
- How: If the same decision pattern appears daily or per sprint, DDDI gives enough structure without bureaucracy.
If you want, the next step can be a concrete JSON or YAML “framework-selector” spec you can embed into an agent, plus example inputs/outputs for a few real Coditect decisions (e.g., “adopt new sandbox tech”, “onboard regulated tenant”).
⁂
DEVELOP THE SAME FLOW FOR CHOOSING ANY ONE OF THE FRAMEWORKS AND THE LOGIC FLOW AND DECISION PROCESS TO CHOOSE
Here is a generalized selection flow you can apply to choose any one framework (RACI, RASCI, DACI, RAPID, DDDI) for a given situation.
1. Define inputs to the decision
Use these variables as inputs to the selector:
primary_need: "execution_clarity" | "decision_clarity"
stakes: "low" | "medium" | "high"
stakeholder_count: "few" | "many"
formal_veto_needed: true | false
support_roles_critical: true | false
decision_frequency: "one_off" | "recurring" | "high_volume"
regulation_constraint: true | false
2. Top-level logic: execution vs decision
Gate 1 – What problem are you solving?
- If the core issue is:
3. Branch A: execution clarity (RACI / RASCI)
Gate A1 – Are support/enablement roles structurally important?
Question: “Do we have teams that repeatedly support others (platform, security, compliance, design) without owning tasks?”
- If yes (support_roles_critical = true) → choose RASCI.
- If no (support_roles_critical = false) → choose RACI.
- Why: RACI is simpler and enough when you mostly need Rs and As; support is not structurally distinct.137
- How: Use R, A, C, I at the level of key steps/milestones; avoid modeling every micro-task.
Optional refinement – regulation_constraint
- If regulation_constraint = true (e.g., pharma, finance): prefer RASCI even if support_roles_critical is borderline, because QA/Compliance/Security typically act as S/C roles in a structured way.138
4. Branch B: decision clarity (DACI / RAPID / DDDI)
Gate B1 – Stakes and stakeholder complexity
Question: “What is the consequence if we get this decision wrong? How many powerful stakeholders are involved?”
- If stakes = high AND stakeholder_count = many → go to Gate B2 (RAPID vs DACI).
- If stakes = low/medium OR stakeholder_count = few → go to Gate B3 (DACI vs DDDI).
Gate B2 – Are formal vetoes or sign-offs required?
Question: “Are there functions with formal veto/sign-off rights (Legal, Risk, Compliance, Finance) for this decision?”
- If formal_veto_needed = true → choose RAPID.
- If formal_veto_needed = false → choose DACI.
Gate B3 – Frequency of decision
Question: “How often do we make this kind of decision?”
- If decision_frequency = high_volume → choose DDDI.
- Why: High-volume micro-decisions (sprint-level trade-offs, operational tweaks) cannot carry DACI/RAPID overhead.143
- How: Use DDDI roles (Define, Decide, Do, Input) to keep decisions fast and lightweight.
- If decision_frequency = one_off OR recurring (but not high volume) → choose DACI.
5. Combined decision-logic (pseudo-code)
You can encode this logic directly:
def choose_framework(
primary_need,
stakes,
stakeholder_count,
formal_veto_needed,
support_roles_critical,
decision_frequency,
regulation_constraint
):
# Branch 1: Execution clarity
if primary_need == "execution_clarity":
if support_roles_critical or regulation_constraint:
return "RASCI", "Execution is complex and support/QA/compliance roles are critical; use RASCI to model Support explicitly."
else:
return "RACI", "You mainly need clear Rs and As for tasks; RACI is simpler and sufficient."
# Branch 2: Decision clarity
if primary_need == "decision_clarity":
# High stakes, many stakeholders
if stakes == "high" and stakeholder_count == "many":
if formal_veto_needed:
return "RAPID", "High-stakes decision with multiple veto/sign-off stakeholders; RAPID models Recommend/Agree/Input/Decide/Perform explicitly."
else:
return "DACI", "High-stakes, many stakeholders, but no formal veto requirement; DACI with Driver + Approver is lighter and sufficient."
# Low/medium stakes or fewer stakeholders
if decision_frequency == "high_volume":
return "DDDI", "Frequent decisions; DDDI is light-weight (Define/Decide/Do/Input) and avoids DACI/RAPID overhead."
else:
return "DACI", "Medium/low stakes or fewer stakeholders; DACI clarifies Driver and Approver without RAPID's complexity."
# Fallback
return "RACI", "Default to RACI when context is unclear; refine once you know whether the main issue is execution or decision rights."
Each return includes both the framework and a short why string so an agent or UI can explain the choice.
6. How to apply this logic in practice
- Step 1 – Capture context: At the start of an initiative, have the PM/lead answer the input questions (can be a short form or CLI params).
- Step 2 – Run selector: Feed those values into the logic; record the chosen framework in the project “governance” section.
- Step 3 – Instantiate template:
- If RACI/RASCI: create a responsibility matrix for key tasks.
- If DACI/RAPID/DDDI: create a decision-role table for key decisions.
- Step 4 – Review with team: Sanity-check that the chosen framework fits culture/scale; override only with explicit rationale.
- Step 5 – Re-evaluate on threshold events: If stakes, stakeholders, or regulatory constraints change materially, rerun the selector and migrate to a different framework if needed.
If you want, next step can be a JSON schema + example payloads for this selector, or a prompt/DSL for an “Agent: GovernanceFrameworkSelector” that uses this logic inside your multi-agent system.
⁂
SUGGESTIONS?
Three focused suggestions you can wire into your workflow:
- Turn the selector into a callable “GovernanceFrameworkSelector” service
- Implement the logic model as a small API (or internal function) that takes the inputs you defined (primary_need, stakes, stakeholder_count, etc.) and returns
{framework, rationale, next_steps}. - Use that service as a first step in project kickoffs or as a tool inside your orchestration agent so every initiative starts with an explicit framework.
- Implement the logic model as a small API (or internal function) that takes the inputs you defined (primary_need, stakes, stakeholder_count, etc.) and returns
- Attach framework templates to the selector output
- For each framework (RACI, RASCI, DACI, RAPID, DDDI), predefine:
- a minimal matrix/table template,
- a checklist of “good enough to start” fields,
- one concrete example.
- When the selector returns “DACI”, auto-instantiate a DACI decision brief doc; when “RASCI”, spawn a responsibility matrix skeleton.
- For each framework (RACI, RASCI, DACI, RAPID, DDDI), predefine:
- Instrument a feedback loop on framework effectiveness
- After each major decision or milestone, capture 2–3 meta-metrics: “decision latency”, “rework due to unclear roles”, “escalations due to ownership disputes”.
- Feed those back to adjust thresholds (e.g., when to jump from DACI to RAPID) and to learn which frameworks work best for your org patterns over time.
If you tell me which part you want to operationalize first—selector service, concrete templates per framework, or metrics/feedback—I can produce an implementation-ready spec (JSON + example) for that piece next.
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what is the overarching category of this subject? decision proceses????
The overarching category here is responsibility and decision-rights frameworks for organizational decision-making and execution.149150
More specific umbrellas you could use in docs:
- Responsibility assignment matrices (RAMs) – classic term in BPM / PM literature for RACI/RASCI and similar.151152
- Decision-making frameworks and role models – common label when you include DACI, RAPID, DDDI, OVIS, etc., alongside RACI-like models.150153
- Governance and accountability frameworks – broader umbrella tying these to org design, decision rights, and process governance.149150
If you want one canonical label for a section in an architecture or ops manual, something like:
“Decision Rights and Responsibility Frameworks”
will comfortably cover RACI/RASCI, DACI, RAPID, DDDI, and related models.
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