Automation Backlog Prioritization: Impact × Feasibility
Overview
Backlogs explode with ideas. Prioritization should be transparent and revisitable as data improves.
Quick definition
Backlog prioritization scores items on business impact, technical feasibility, risk, and platform leverage—often as a weighted matrix with explicit assumptions.
Definition
Impact × feasibility scoring estimates value (time, revenue, risk) against integration difficulty, data quality, and organizational readiness.
Why it matters
Politics picks pet projects; scoring aligns teams—or exposes where data work must precede AI.
Core framework
Step-by-step model as TypeScript interfaces (machine-readable checkpoints).
Impact rubric
/**
* Impact rubric
* Quantify weekly hours, error cost, or revenue latency.
*/
export interface CoreFrameworkStep1ImpactRubric {
/** Order in the core framework (0-based) */
readonly stepIndex: 0;
/** Display title for this step */
readonly title: "Impact rubric";
/** Narrative checkpoints as published in the guide */
readonly narrative: readonly string[];
}
export const CoreFrameworkStep1ImpactRubric_NARRATIVE: readonly string[] = [
"Quantify weekly hours, error cost, or revenue latency."
] as const;Feasibility rubric
/**
* Feasibility rubric
* APIs vs screen scraping, data cleanliness, compliance constraints.
*/
export interface CoreFrameworkStep2FeasibilityRubric {
/** Order in the core framework (0-based) */
readonly stepIndex: 1;
/** Display title for this step */
readonly title: "Feasibility rubric";
/** Narrative checkpoints as published in the guide */
readonly narrative: readonly string[];
}
export const CoreFrameworkStep2FeasibilityRubric_NARRATIVE: readonly string[] = [
"APIs vs screen scraping, data cleanliness, compliance constraints."
] as const;Detailed breakdown
Logic sections encoded as Python functions with structured narrative payloads.
Revisit quarterly
def logic_block_1_revisit_quarterly(context: dict) -> dict:
"""Operational logic: Revisit quarterly"""
# Narrative steps from the guide (logic section)
paragraphs = ["Feasibility changes as platforms improve and debt is paid down."]
return {
"heading": "Revisit quarterly",
"paragraphs": paragraphs,
"context_keys": tuple(sorted(context.keys())),
}Technical patterns
Scoring rubric
- Normalize scores 1–5; document assumptions for impact estimates.
- Platform items get bonus weight (unblocks many flows).
Code examples
Weighted score
Transparent ranking function.
export function priorityScore({ impact, feasibility, risk, platform }) {
return 0.4 * impact + 0.3 * feasibility + 0.2 * platform - 0.1 * risk;
}System architecture
[Intake form]
→ [Normalize scores]
→ [Quarterly review board]
→ [Committed roadmap + parking lot]
→ [Feedback to requesters]Real-world example
A COO killed a flashy “AI insights” project after scoring showed CRM hygiene blocked every dependent workflow—funded cleanup first.
Common mistakes
- Impact only—choosing impossible integrations.
- Feasibility only—optimizing busywork with low upside.
Related topics
PrimeAxiom facilitates prioritization workshops with your data—book a backlog review.