“This will only take a few days.”
That sentence has killed more budgets and timelines than any technical bug in history.
Whether you are building a mobile app, a website, or a custom CRM, the story is always the same. You create a plan. You feel confident. Then, reality hits. A simple integration breaks. A key team member gets sick. The client changes their mind.
Suddenly, the project is three weeks late and 20% over budget. This is one of the biggest mistakes when creating estimates, yet we keep repeating it.
Why does this happen to smart, experienced teams? The answer lies in human psychology. We are biologically wired to be bad at creating an accurate estimate.
This article explores the cognitive biases that sabotage your planning and introduces a mathematical method to defeat them.
Table of Contents
- The Planning Fallacy: Why we are wired for optimism
- The Cone of Uncertainty
- The solution: Moving from Single-Point to Three-Point estimation
- Why gut feeling is not data
- How to calculate a risk-adjusted estimate
- How devtimate automates the psychology of pricing
- Checklist
- FAQ
The Planning Fallacy: Why we are wired for optimism
In 1979, psychologists Daniel Kahneman and Amos Tversky coined the term Planning Fallacy.
It describes a phenomenon where people display an optimism bias and underestimate the time needed to complete a future task. Crucially, we do this even if we have knowledge of past tasks taking longer.
When you ask a developer “How long will this take?”, their brain immediately visualizes the “Happy Path.”
- They imagine the code writing itself perfectly.
- They assume no meetings will interrupt them.
- They assume the documentation is correct.
They do not visualize the debugging, the context switching, or the email interruptions. This is why a task that “feels” like 4 hours often takes 12.
To create a reliable estimate, you must force the brain to step off the Happy Path.
The Cone of Uncertainty
Another reason estimates fail is timing. Clients often demand a fixed price at the very beginning of a project, which is the moment we know the least about it.
This concept is called the Cone of Uncertainty.
- At the start: Variability is high (e.g., 4x difference between low and high estimates).
- After design: Variability drops.
- After prototyping: Variability drops further.
- At finish: Variability is zero.
The psychological mistake agencies make is treating an early-stage estimate as a promise. It is not a promise. It is a probability cloud.
If you force a precise number too early, especially when the requirements are unclear, you are gambling, not estimating.
The solution: Moving from Single-Point to Three-Point estimation
How do we fix this? We stop using single numbers.
When you ask “How much is this?”, and you get the answer “$10,000”, you have zero information about risk.
Instead, professional estimators use the PERT (Program Evaluation and Review Technique) or Three-Point Estimation method. For every feature, you must ask three questions:
- Optimistic (O): If everything goes perfectly, how fast can we do it?
- Pessimistic (P): If everything goes wrong (APIs break, bugs appear), how long will it take?
- Most Likely (M): What is the realistic average?
By forcing the team to think about the Pessimistic number, you break the Planning Fallacy. You force them to visualize the risks they were previously ignoring.
Why gut feeling is not data
Many agencies rely on “expert intuition.” A senior developer looks at a brief and says “About 3 months.”
While valuable, intuition is not data. It is often biased by the developer’s most recent project or their desire to please the client (social desirability bias).
A data-driven estimate looks at history.
- “Last time we integrated Stripe, it took 25 hours, not 10.”
- “On average, our QA phase adds 30% to the timeline.”
To make a software estimate that clients actually trust, you need to show them the math, not just share a feeling.
How to calculate a risk-adjusted estimate
Once you have your three points (Optimistic, Pessimistic, Most Likely), you can calculate a weighted average.
The standard formula is: Estimate = (Optimistic + 4 x Most Likely + Pessimistic) / 6
Why does this work? It gives the most weight to the realistic scenario but pulls the final number slightly towards the pessimistic side to account for risk.
Example:
- Optimistic: 10h
- Most Likely: 15h
- Pessimistic: 40h (Risk identified!)
Calculation: (10 + 60 + 40) / 6 = 18.3 hours.
Notice that the single-point guess would have been 15 hours. The risk-adjusted estimate is 18.3 hours. That extra 3.3 hours is your safety margin. Across a whole project, this difference saves your profit margin.
How devtimate automates the psychology of pricing
Doing PERT calculations manually for a 50-feature project in Excel is slow and prone to errors.
devtimate was built with this psychology in mind. It forces you to think in ranges, not single numbers.
- Built-in Ranges: When you select a feature, devtimate encourages you to define a Min/Max range based on complexity.
- Risk Visualization: You can instantly toggle between “Optimistic” and “Pessimistic” views to see how risks impact the total budget.
- Historical Data: It helps you save your own templates, so your future estimates are based on past reality, not current optimism.
By using a tool that structures this thinking for you, you remove the cognitive bias from the equation. You get an estimate that is defensible, realistic, and safe.
Start building risk-adjusted estimates with devtimate.
Checklist
✅ Never accept a single-number estimate from a developer without questioning the risks.
✅ Use the Three-Point method (Optimistic, Realistic, Pessimistic) for complex features.
✅ Account for the “Cone of Uncertainty” by giving wider ranges at the start of the project.
✅ Include non-coding time (meetings, email, management) in your pessimistic scenario.
✅ Base your estimates on historical data from previous projects whenever possible.
✅ Use a tool like devtimate to automate the math and formatting.
FAQ
1. Why is the Planning Fallacy so common?
It is a cognitive bias rooted in our desire for success. We naturally focus on the goal (finished software) rather than the obstacles (bugs, delays). Evolution wired us to be optimistic doers, but good project management requires us to be pessimistic planners.
2. What is the best way to present a risk-adjusted estimate to a client?
Present it as a range. Say: “Based on our analysis of the risks, the project will likely fall between $40k and $60k.” Explain that the lower end assumes standard implementation, while the higher end accounts for specific complexities you identified.
3. Does devtimate use the PERT formula?
devtimate uses a logic similar to PERT by allowing you to define time ranges (min/max) for every task. This automatically builds a risk buffer into your final proposal without you needing to run the formula manually for every line item.
4. How do I handle a client who demands a ‘guaranteed’ price?
You can offer a guaranteed price, but it must be the Pessimistic number from your calculation. Explain that the premium pays for the transfer of risk from them to you. If they want a lower price, they must accept a Time & Materials model or a flexible scope.
5. Can AI help with estimation psychology?
Yes. AI tools don’t have egos or optimism bias. They look at data. You can learn more about what is an AI estimate to understand how algorithms can provide an objective “second opinion” to your team’s gut feeling.
An accurate estimate is not about being a better coder. It is about being a better thinker.
By understanding the psychology of estimation and using the right tools to counter your own biases, you can stop losing money on projects and start delivering on your promises.
Let devtimate handle the math so you can focus on the delivery.
