Using Three-Point Estimation to Improve Confidence Voting in SAFe PI Planning

1. Intro: Why Confidence Voting Often Fails

In SAFe PI Planning, teams use Confidence Voting to express how confident they feel about meeting the PI objectives. It’s a quick 0–5 scale where 5 means full confidence and 0 means no confidence at all.

It sounds simple, but the method has some flaws:

• Groupthink: People tend to vote like others, especially if team leads or strong voices speak first.
• Anchoring: Once someone says “I’m at a 4,” others unconsciously stay near that number.
• Overconfidence or underconfidence: Some teams routinely vote high to move things along, others vote low to flag concerns, even if those concerns are vague.
• No context behind the numbers: A 3 from one person might mean “this is risky,” while from someone else it might mean “it’s fine, but not perfect.”

The core problem: we reduce a complex judgment into a single number, without capturing uncertainty or reasoning. That’s where Three-Point Estimation can help—it gives structure to the fuzziness behind those numbers and makes room for better conversations.

2. What is Three-Point Estimation?

Three-Point Estimation is a way to express uncertainty in planning. Instead of guessing a single value, you give three:

• Optimistic (O) – What if everything goes right?
• Most Likely (M) – What you think will probably happen.
• Pessimistic (P) – What if it goes worse than expected?

It’s often used in risk analysis and effort estimation. The idea is to avoid committing too early to a single guess and instead work with a range that reflects real uncertainty.

You can also calculate a weighted average from the three points:

(O + 4M + P) / 6

This puts more weight on the “most likely” estimate but still keeps the range in view. You don’t need the formula to use the method, but it helps if you want a single value that still reflects variation.

In the context of SAFe PI Planning, this technique helps shift the conversation away from simple agreement and toward shared understanding of risk and confidence.

3. How It Applies to Confidence Voting

Instead of asking each team member to give a single number on the 0–5 scale, you ask for three numbers:

• Best-case confidence – if everything goes as planned
• Most likely confidence – based on current understanding and risk
• Worst-case confidence – if key assumptions fail or blockers appear

This simple shift gives everyone space to think in ranges, not absolutes.

In practice:

• Team members write down or share their three confidence scores.
• You can quickly scan for spread. Is everyone hovering around 4–5, or are there 1s in the worst-case column?
• Use the variation as a starting point for discussion—not to average out scores but to explore why the gaps exist.

This approach surfaces:

• Misalignment in assumptions
• Hidden risks or dependencies
• Places where more clarification is needed

The goal isn’t precision. It’s exposing uncertainty early—before it becomes an issue during the PI.

4. Benefits of Using Three-Point Estimation

Adding Three-Point Estimation to Confidence Voting gives you more than just a different number—it changes how teams think and talk during PI Planning.

Key benefits:

Reduces anchoring: People form their confidence range individually before sharing. This lowers the chance they just echo others.

Highlights uncertainty: A single “4” hides risk. A 5–4–2 range reveals it. The spread shows how unsure someone really is.

Improves the discussion: You can spot outliers fast and ask why someone sees it differently. This usually leads to better alignment—or better mitigation.

Focuses the team on assumptions: When confidence drops in the pessimistic case, it usually ties back to something specific: a dependency, a late deliverable, unclear scope. That’s what needs the conversation.

This method doesn’t slow the team down. It sharpens the conversation and gets you to real concerns faster.

5. Example: Before and After

Let’s look at how Three-Point Estimation changes the way you read Confidence Voting results—moving from surface-level agreement to something you can act on.

Standard Confidence Voting

The team votes on their confidence in meeting a key PI Objective:

• Votes: 4, 4, 5, 5, 3
• Average: 4.2

This looks solid at first glance, so the team probably moves on without digging deeper. But no one questions the 3, and the spread between 3 and 5 doesn’t lead to a conversation.

You don’t really know:

• Where the risk sits
• Who’s uncertain
• Or why that 3 happened

Three-Point Estimation Voting

Each person adds a best-case and worst-case confidence score, framing their estimate as a range:

(Using the above votes as the “Most Likely” values)

• Average Weighted Confidence:(3.83 + 3.83 + 5.00 + 4.33 + 3.67) / 5 = 4.13
• Average Uncertainty (O - P):(3 + 1 + 0 + 4 + 1) / 5 = 1.8

What This Tells You

• The average confidence drops slightly to 4.13, but the real insight is in the uncertainty.
• Two team members (A and D) think things could go as low as 2 and 1, even though their “most likely” scores were 4 and 5.
• Only one person (C) is fully confident with no variation.

Average uncertainty

In this example, the (difference between optimistic and pessimistic scores) was 1.8 on a 0–5 scale. That’s a wide range.

It means the team’s confidence isn’t as solid as the simple 4.2 average suggests. There’s hidden risk, likely from unclear assumptions or dependencies. Even though no one voted lower than a 3 in the original round, the pessimistic estimates reveal that at least two team members think confidence could drop to 1 or 2 in a bad-case scenario.

Use this number as a signal. Anything close to 2 or more usually means the team doesn’t fully agree on what “success” looks like—or how likely it is.

What to Do With This

Don’t focus only on the weighted average. The uncertainty gives you a reason to ask:

• What assumptions are behind the optimistic and pessimistic scores?
• Why do some people see a big gap between best and worst outcomes?
• Are there blockers, unknowns, or risks that need clarification?

A 5-minute follow-up conversation could fix a major misalignment before it turns into a delivery problem. You don’t get that opportunity with standard voting alone.

6. Tips for Introducing This in Your Next PI Planning

You don’t need a workshop or new tooling to start using Three-Point Estimation in PI Planning. Just add it to how your team already does Confidence Voting—especially for objectives that feel unclear or risky.

Here’s how to keep it practical:

Keep it lightweight

• Don’t force every team to use it for every objective. Pick 1–2 high-impact or high-uncertainty objectives.
• Timebox the discussion. Five minutes per objective is enough to expose gaps and surface assumptions.

Use shared, visible tools

• Drop the scores in a shared sheet or Miro/Mural board so everyone can see the spread.
• Use conditional formatting or colors to flag large uncertainty ranges.
• If you’re remote, use breakout rooms for fast group estimation.

Focus on alignment, not the numbers

• You’re not trying to get perfect estimates—you’re trying to reveal misalignment before it causes delivery problems.
• Ask: “Why does your worst case drop to 2?” or “What’s driving your optimistic 5?”That’s where the real value is.

After the vote: debrief what matters

• Don’t just average the scores. Look at the outliers and ranges.
• Decide if something needs clarification, mitigation, or just acceptance as a known risk.

You’re not replacing the confidence vote. You’re just making it smarter. Most teams already have the insight—they just need a better format to surface it.

7. Conclusion

Confidence Voting in SAFe is meant to trigger conversations about risk—but too often, it just turns into a numbers game. You see a few 4s and 5s, maybe a 3, and move on. Teams rarely dig into why people feel uncertain, and real risk gets glossed over.

Using Three-Point Estimation in SAFe fixes that without adding ceremony. It gives teams a way to express uncertainty in a structured way, not just guess a number. The method helps you spot misalignment early, surface risks, and have better planning conversations.

You don’t need to roll it out across the board. Start small. Use it when things feel shaky, when the confidence scores are inconsistent, or when an objective seems loaded with assumptions. All it takes is three numbers instead of one—and a short conversation about the gaps.

That’s where the value is.

Further Reading

If you want to explore more about how Three-Point Estimation works in different contexts, check out these related posts:

• The Power of Three-Point EstimationA practical look at why this method is better suited for uncertainty than single-number estimates.
• Estimations in Software Development: A Dive into Three-Point Estimation vs Story PointsA side-by-side comparison of estimation techniques—and why switching from story points to ranges might save you from misleading precision.