Strategy, roadmaps and prioritisation

Vision and strategy

• Vision: the long-term change you want to create ("Every student gets hired for what they can do, not where they studied").
• Strategy: the choices about where to play and how to win: target users, the core problem, differentiation, business model, and what you won't do.
• Goals: measurable objectives, often as OKRs (Objectives and Key Results). Objective: "Make freshers hireable on skills." KR: "40% of applications include a completed task by Q4."

North star metric

One metric that best captures the value users get and predicts long-term success: for a job platform, "candidates hired through the platform per month"; for a messaging app, "messages sent"; for Spotify, "time spent listening". Supported by input metrics the team can influence.

Roadmaps

A roadmap communicates priorities and direction, not a promise of dates for every feature. Now / Next / Later roadmaps organised around problems and outcomes are more honest than Gantt charts of features. Update regularly as you learn.

Prioritisation frameworks

• RICE: (Reach × Impact × Confidence) ÷ Effort.
• Value vs effort matrix: quick wins first, then big bets.
• Kano: basic needs (expected, cause dissatisfaction if missing), performance needs (more is better), delighters.
• MoSCoW for release scoping.
• Cost of delay: what do we lose each week we don't ship this?

Frameworks support judgement; they don't replace it. Be transparent about why something is prioritised.

RICE example: Feature A reaches 10,000 users a quarter, impact 2 (high), confidence 80%, effort 4 person-weeks → 10,000 × 2 × 0.8 ÷ 4 = 4,000. Feature B: 50,000 × 0.5 × 0.5 ÷ 2 = 6,250. B scores higher despite lower impact per user.

Check yourself

• Propose a north star metric for an online learning platform and justify it.
• Calculate RICE for: reach 5,000, impact 3, confidence 50%, effort 3.
• Why are outcome-based roadmaps better than feature lists with dates?