In 2006, Google's Avinash Kaushik coined the term HiPPO — Highest Paid Person's Opinion — to describe a pattern he saw repeatedly in data-driven organisations: when there was ambiguity, decisions defaulted to whoever had the most authority rather than the best evidence.
Two decades later, the pattern is as common as ever — and it's quietly corrupting sprint planning sessions, roadmap reviews, and prioritization workshops at companies of every size.
How HiPPO actually manifests in meetings
It rarely looks like a boss issuing a decree. More often it's subtle:
- A VP mentions they 'really want to see' a feature, and suddenly it appears at the top of the backlog without a formal prioritization discussion.
- During dot-voting, team members watch where the senior person places their stickers before committing their own.
- In ranking discussions, items championed by someone senior get longer defences and fewer challenges.
- People 'pre-align' before a meeting, meaning they've already lobbied the most influential person and shaped the outcome before anyone sits down.
None of these require malice or even awareness. They're the natural byproduct of social dynamics and status gradients in groups.
What it costs
The direct cost is obvious: you build the wrong things. A study by McKinsey found that companies in the top quartile of decision-making quality generate returns nearly 6% higher than those in the bottom quartile. Prioritization quality is a core input to that number.
The indirect costs are subtler but significant. When people consistently see their judgment overruled by authority rather than evidence, they stop contributing honestly. Meetings become performances. The people closest to the work — engineers, support staff, frontline teams — disengage from prioritization entirely because they've learned their input doesn't matter.
HiPPO doesn't just produce bad priorities. It produces teams that stop trying to produce good ones.
Why standard fixes don't work
Telling people to 'be more objective' doesn't work. Social influence is unconscious and persistent — you can't think your way out of it in a meeting room.
Anonymous written surveys help but introduce a new problem: they're asynchronous, slow, and disconnect the voting from the context of a live discussion.
RICE and similar scoring frameworks shift the bias from people to the scoring system. Now debates are about what counts as high Reach rather than about the actual work. The HiPPO influence reappears in how people estimate scores.
How live pairwise voting breaks the pattern
Pairwise voting in a workshop session neutralises HiPPO through structure, not willpower. Three properties make the difference:
- Simultaneous voting. Everyone votes at the same time, on their own phone. There's no observable order to anchor on. The VP and the junior engineer submit their comparisons at the same moment.
- Individual not group comparisons. You're not asked to rank a whole list or justify a score. You're asked a single binary question: of these two specific things, which matters more right now? It's hard to be diplomatically vague about a binary choice.
- Aggregate results only. No one sees who voted for what. The team sees a ranking that emerges from collective judgment — not a list of individual positions that can be traced back and challenged.
The result is that the ranking represents what the group actually thinks, not what they think they should say in front of the person who controls performance reviews.
Using the ranking constructively
Pairwise voting doesn't eliminate the HiPPO's legitimate input — it just moves it to the right place. After the ranking is revealed, senior stakeholders can absolutely weigh in: 'I notice X ranked low, but there's a board commitment we haven't shared with the team yet.' That's valuable context. What changes is that it requires explicit justification rather than passive social influence.
Teams that run regular pairwise workshops consistently report that post-vote discussions are shorter and more productive. With an objective starting point, debate becomes focused on the real exceptions rather than relitigating everything from scratch.