What If You Knew?

You can’t fix what you can’t see. But what if you could?

Imagine this.

You’re leading a team. The vision is clear. The strategy is ambitious. Your next big goal is public, maybe it’s reaching a revenue milestone, entering a new region, or shipping a major product.

You’ve shared the plan with your board. You’ve mapped the timeline. Everyone’s aligned.

And yet, in the quiet moments, before a team all-hands or while reviewing a forecast, you pause.

Not because you doubt the mission or the team. But because no one can answer the one question that matters:

“What are the real odds we’ll hit this goal?”

You ask around. Some people are confident. Others say, “It depends on execution.” But you know what this is: guesswork. Hope wrapped in spreadsheets. Fog, dressed like clarity.

What if there were another way?

What if you typed in your actual numbers, your real metrics, growth targets, and timelines, and instantly saw a probability of success? Not a vibe. Not a hunch. A number.

A probability grounded in data. Powered by math. And usable today.

A Realistic Scenario: Inspired by Shopify

Let’s take a real example and run it through the Pi Trajectory Model.

We used public data to plug this goal into the Pi Trajectory Model. Here’s what the model considered:

• Historical Volatility: Shopify’s revenue has varied by around 52% over time

• Growth Target: 16%

• Time Runway: 1 year

• Downside Risk Factors: Market conditions, macroeconomic fluctuations, and internal execution risks

Result: 46.81% probability of success.

That number isn’t good or bad. It’s just real. Imagine someone inside Shopify seeing that number and thinking, “If this is our baseline, what would it take to improve it?”

Why It Matters

We track KPIs, obsess over dashboards, and build slides for every quarter. But no one ever shows you the probability of hitting the goal that matters most.

We over-communicate ambition and under-measure feasibility.

That’s what The Pi Trajectory Model changes.

It doesn’t ask, “Did we hit the goal?” It asks, “Are we likely to?” And that shift - from postmortem to foresight - changes everything.

From Guessing to Guiding

Let’s say the model shows a 46.81% chance of success. You don’t shrug and move on. You ask better questions.

What happens if we extend the timeline by 6 months?

What if we reduce churn by 10%?

What if we hire 2 more engineers this quarter?

The model updates. The probability moves. You’re no longer making decisions in the dark, you’re navigating with visibility.

Who It’s For

This isn’t just for finance teams or quants. The Pi Trajectory Model was designed to help real people make real decisions:

• Founders trying to raise based on realistic growth

• Product Leaders gauging the viability of timelines

• Revenue Teams aligning headcount with upside

• CEOs making bets, not blind leaps

And because the model uses your own numbers, you don’t need a consultant or a PhD to use it. You just need the truth.

Coming Soon: Tailored Recommendations

We’re building something even more powerful.

Imagine this: The model doesn’t just say “You’re at 46.81%.” It also tells you:

• “Hire 2 more engineers” → moves you to 55.3%

• “Cut marketing waste by 12%” → moves you to 59.4%

• “Add 3 months runway” → moves you to 63.1%

Each recommendation is backed by math, not guesswork. Each suggestion is tied to an outcome.

This is what we’re calling the Recommendation Layer - a new feature in development that closes the loop from awareness to action.

This Isn’t Just a Model. It’s a Movement.

Because teams are tired of spinning their wheels. Because leaders deserve more than “let’s see how it goes.” Because setting goals shouldn’t feel like crossing your fingers.

The Pi Trajectory Model helps you stop guessing and start guiding - with clarity, confidence, and a path forward.

And sometimes, knowing your odds is all you need to beat them.

Published Paper Reference:Rai, Piyoosh (2025). The Pi Trajectory Model: A Probabilistic Framework for Forecasting Business Goal Achievement.DOI: 10.17605/OSF.IO/FA472