Prioritisation: Impact, Effort & the Eighty-Twenty Rule
A product team has ten customer complaints, three investor asks, two bugs, and one launch deadline - all marked “urgent.” The leader who wins is not the one who works hardest; it is the one who can calmly say, “These two things move the business, these five can wait, and this one is a trap.”
- Prioritisation means choosing the next best action under constraint - time, money, people, attention, or risk.
- The Impact-Effort Matrix separates quick wins, big bets, fill-ins, and avoidable distractions.
- The 80/20 rule is a heuristic: a few causes often drive most outcomes, but you must prove which few.
- Good prioritisation uses impact, effort, confidence, urgency, risk, and strategic fit - not gut feel alone.
- Never rank initiatives before defining the problem; otherwise you optimise activity, not results.
- In interviews, state your criteria first, score options second, then recommend with trade-offs.
- The most common mistake is treating “low effort” as “high priority.” Easy work is not automatically valuable.
Big Picture: Prioritisation Is a Filter, Not a To-Do List
Prioritisation is the discipline of converting a messy universe of possible actions into a focused sequence of decisions. Before you prioritise, you must know what problem you are solving; if that step is shaky, revise Defining the Problem Before Solving It first.
Core Explanation: How to Prioritise Without Guessing
The simplest mental model is: value created minus cost of action, adjusted for confidence and timing. That is why impact and effort are necessary, but not sufficient.
Impact asks: “If this works, how much does it move the goal?” Effort asks: “What will it consume?” Confidence asks: “How sure are we?” Urgency asks: “Does timing change the value?”
The Four Zones of the Impact-Effort Matrix
Use the matrix to classify options quickly, then apply judgement. Each quadrant has a different managerial action.
The matrix is powerful because it forces trade-offs into the open. It is dangerous when candidates use it mechanically and ignore dependencies - for example, a “low impact” compliance fix may still be mandatory.
The Eighty-Twenty Rule: Find the Few Drivers That Matter
The 80/20 rule says that a minority of inputs often explains a majority of outputs. In business, that may mean a few SKUs drive most contribution, a few branches drive most complaints, or a few customer segments drive most profit.
The 80/20 rule is a prioritisation heuristic: a small share of causes often accounts for a large share of effects.
Use it as a searchlight, not a law. Do not assume the split is exactly 80 and 20. The real question is: which few variables explain most of the movement in the target metric?
A Five-Step Prioritisation Process
When the problem is ambiguous, do not jump straight to a matrix. Use this sequence.
Metrics and Scoring: What to Track
In interviews, you do not need perfect data, but you do need a disciplined scoring logic. Use a simple table like this.
Worked Example: Prioritising Three Growth Actions
Suppose a food delivery app wants to increase repeat orders in one city. The team has three options. Scores are hypothetical and only for learning.
The recommendation is not “do the biggest idea.” It is: fix late-delivery refunds first because it is high-confidence, low-effort, and directly linked to repeat trust; then improve the reorder button; test the campaign only if the unit economics support it.
A quick-commerce team cannot stock every item in every dark store. It prioritises high-frequency essentials, local demand patterns, and substitution logic before long-tail assortment. The primary driver is basket relevance in a tiny catchment; supporting drivers are inventory turns, picking simplicity, and delivery promise reliability. So what: prioritisation protects both customer experience and working capital.
Definitions You Should Be Able to Say
- Prioritisation: Choosing the best sequence of actions when resources are limited.
- Impact: The expected improvement an action creates in the target outcome.
- Effort: The resources, time, complexity, and coordination required to execute an action.
- Opportunity cost: The value of the best alternative you give up by choosing one action.
- 80/20 rule: A heuristic that a few causes often explain a large share of results.
Zerodha: Prioritising Trust Over Feature Sprawl
Zerodha shows prioritisation by focusing on a few trust-building choices - simple digital broking, transparent pricing, stable platforms, and investor education - instead of chasing every financial-services opportunity.
Situation: Indian retail investing became more digital, more competitive, and more feature-heavy. Brokers could chase many directions at once: advisory, lending, social trading, wealth products, aggressive promotions, and more.
The move: Zerodha built its proposition around a focused set of priorities: a clean trading experience, low-friction digital access, transparent brokerage, and education through Varsity. The primary driver was trust through simplicity. Supporting drivers included product usability, founder-led communication, operational discipline, and a community of self-directed investors.
Outcome and lesson: The strategic lesson is not “simple products always win.” It is sharper: when customers are anxious about money, the highest-impact priority may be reducing confusion and building trust, not adding more features. Zerodha’s prioritisation works because the choices reinforce one another - pricing, platform, education, and communication all point to the same promise.
How AI Changes Prioritisation
AI does not remove prioritisation; it changes the speed and evidence base behind it.
- Faster issue clustering: AI can group thousands of reviews, tickets, or sales notes into recurring themes, helping teams spot the “critical few” faster.
- Better impact estimation: Machine-learning models can estimate which customer segments, SKUs, stores, or journeys are most likely to move the target metric.
- Scenario testing: Teams can use AI to compare “what if” options - for example, what happens if we improve conversion, reduce churn, or cut fulfilment delay first.
The caveat: AI can rank options based on available data, but it may miss political constraints, brand risk, operational dependencies, or ethics. A manager must still make the trade-off call.
Use ChatGPT or Claude like a prioritisation sparring partner: paste the case facts, ask it to list options, score impact-effort-confidence, then challenge every score with “What assumption would make this wrong?” Do not outsource the decision; use AI to expose weak assumptions.
Interview Relevance
“A company has ten possible initiatives to improve profitability, but only budget for two. How would you prioritise?”
Say, “I will prioritise based on expected value, feasibility, and confidence - then adjust for urgency and risk.” That one sentence makes you sound structured before you do any math.
Common Mistake
Mistake: Candidates pick the easiest initiative and call it prioritisation. Why it costs them: it shows activity bias, not business judgement. Fix: always rank by impact first, then use effort, confidence, urgency, and risk to decide the sequence.