Estimation is one of the trickiest parts of agile software development. The fluid nature of agile can make it difficult to predict how much effort is needed for a task. Teams often struggle to come up with accurate estimates, leading to missed deadlines, scope creep, and frustrated stakeholders.
The good news is that there are techniques you can use to get better at agile estimation. By leveraging historical data, embracing a collaborative process, and frequently revisiting estimates, teams can set realistic expectations even with changing requirements.
In this blog, we’ll explain common reasons teams struggle with estimation and provide actionable tips to overcome those challenges. You’ll learn techniques like planning poker, t-shirt sizing, dot voting, etc. to make your agile estimates more precise. With the right approach, your team will be able to confidently commit to delivering working software in each sprint.
- What Are Agile Project Estimation Techniques?
- Why Run Agile Estimations?
- Challenges and Advantages of Estimating Agile Projects
- Agile Estimation Techniques to Improve Your Project Outcomes
- ClickUp: Your Agile Estimation Ally
What Are Agile Project Estimation Techniques?
Agile project estimation techniques are approaches used by agile teams to estimate the size, effort, and duration of tasks or user stories within a project. They leverage historical data, analysis, and consensus-building to arrive at estimates and forecasts.
Since the goal is accurate planning despite fluid requirements, you must design these estimation techniques to make them iterative and adaptable to the changing nature of agile projects.
Why Run Agile Estimations?
The primary goal of agile estimations is to provide an accurate and quick assessment of the work involved in a project, allowing the team to plan and prioritize tasks effectively.
Agile estimations are essential components of agile project planning and execution. They provide valuable insights for effective team collaboration.
Here are some key reasons why agile teams run estimations:
- Prioritization and planning: Teams plan sprints and releases based on the estimated size of user stories, ensuring they address the most valuable and feasible work first
- Resource allocation: Teams allocate resources and determine the capacity needed for upcoming sprints or releases based on estimations
- Setting expectations: Estimations help set realistic expectations for stakeholders, including product owners, project managers, and customers
- Team collaboration: Agile estimation techniques, such as Planning Poker, allow the entire team to work together and contribute to the estimation process
- Continuous improvement: Teams use historical data on estimation accuracy and velocity to continuously improve their ability to estimate and plan effectively
- Risk management: Agile teams factor in risks during estimation and develop strategies, improving overall project resilience
- Sprint and release planning: Release planning relies on estimations to determine when a team can deliver a set of features or user stories
- Facilitating feedback: Teams use the estimation sessions to clarify requirements, identify dependencies, and gather feedback to improve the overall understanding of the work and the performance required
- Measuring velocity: Estimations contribute to calculating velocity, which helps teams plan future sprints and releases
- Adaptability: Teams adapt their plans based on new information and insights gained through estimations, ensuring flexibility in response to evolving project needs
Challenges and Advantages of Estimating Agile Projects
Challenges of estimating agile projects
- Uncertainty and change: Frequent changes in priorities or scope often impact the reliability of initial estimates
- Overemphasis on velocity: Relying solely on historical velocity without considering changes in team composition, technology, or project dynamics can lead to inaccurate predictions
- Cognitive bias: Cognitive biases, such as optimism bias or anchoring, can influence estimation processes, which impact the accuracy of estimations
Advantages of estimating agile projects
- Visibility and transparency: Estimations enable transparency, which helps in managing expectations and fostering trust, allowing stakeholders to understand the effort required for project completion
- Stakeholder alignment: Stakeholders can make informed decisions based on the estimated effort and expected delivery dates
- Increased predictability: Teams can leverage estimation data to create more reliable forecasts, helping stakeholders make plans and commitments with a higher degree of confidence
Agile Estimation Techniques to Improve Your Project Outcomes
Here are 10 powerful agile estimation techniques to equip your team for success:
1. Planning Poker
This is a gamified technique where team members anonymously estimate effort using cards with relative values. Through discussion and card reveals, they arrive at a consensus.
Planning Poker promotes collaborative engagement and open communication among team members as it brings together their collective expertise. This leads to more accurate estimations.
Using this efficient consensus-building process, you can prevent prolonged debates and help your team understand project complexity, ultimately contributing to improved planning and execution in agile development.
How Planning Poker works
- Step 1: Distribute a deck of Planning Poker cards to each team member. They typically include cards with values like 0, 1, 2, 3, 5, 8, 13, 20, 40, 100, and a “?” card. These values are relative and represent the complexity of the task
- Step 2: Instruct team members to privately select a card from the deck that reflects their estimate of effort required for the task
- Step 3: Simultaneously reveal the chosen cards and encourage team members to openly discuss the rationale behind their estimates. This discussion helps uncover different perspectives, assumptions, and potential risks associated with the task.
Example: If one team member chooses “5” and another chooses “13” for the same task, they can talk about the differences in estimates
- Step 4: Facilitate a collaborative discussion to address any significant discrepancies in estimates. Encourage the team to share insights, clarify uncertainties, and consider additional information. After discussion, have team members vote again by selecting a new card based on their refined understanding of the task.
Example: If the initial estimates were 5 and 13, the team might discuss and decide that the task is closer to level “8” after considering all perspectives. Team members then vote again till the estimates converge toward a consensus
Planning Poker use cases
- Ideal for small to medium-sized teams estimating user stories, tasks, or features
Tips and best practices for using Planning Poker
- Use a timer for each round
- Keep discussions focused on understanding the task
- Encourage active participation
- Pair Planning Poker with other techniques for deeper analysis
- Avoid getting bogged down in precise estimations
2. T-shirt sizing
T-shirt sizing in agile estimation involves assigning relative sizes (XS, S, M, L, XL) to tasks based on perceived effort, simplifying complex assessments. XS represents minimal effort, while XL denotes extremely high effort tasks.
This agile estimation technique promotes quick, collaborative estimation discussions during backlog grooming or sprint planning. It offers simplicity, speed, and flexibility, allowing teams to prioritize tasks efficiently.
T-shirt sizing includes team members with varying expertise levels.
How T-shirt sizing works
- Step 1: Determine the meaning of each size (e.g., XS = 1 day, S = 3 days, M = 5 days, etc.)
- Step 2: Have each team member silently choose the size that best represents the effort involved
- Step 3: Discuss the chosen sizes and adjust individual sizing, if needed, to reach a consensus
T-shirt sizing use cases
- Quick and easy estimation for familiar tasks, promoting relative sizing over precise numbers
Tips and best practices for using T-shirt sizing
- Define sizing criteria beforehand (e.g., time, complexity)
- Ensure everyone understands the size scale
3. Three-point estimation
The three-point method is an agile estimation technique that considers the most likely (M), optimistic (O), and pessimistic (P) scenarios to arrive at task estimates.
The estimation process involves assigning values to each scenario, where the most likely effort (M) is the best estimate based on realistic expectations, the optimistic effort (O) is the best-case scenario, and the pessimistic effort (P) is the worst-case scenario.
For example, if you’re estimating the time required to develop a feature, the most likely effort could be based on historical data and team expertise. The optimistic effort might account for an exceptionally smooth implementation, while the pessimistic effort would consider potential challenges or unforeseen issues.
The three-point method provides a more nuanced and probabilistic approach to task estimation. It allows teams to account for uncertainties and risks inherent in complex projects.
How three-point estimation works
- Step 1: Explain the concept of estimating: M (most likely), O (optimistic), and P (pessimistic) effort
- Step 2: Get each team member to estimate the M, O, and P effort for the task
- Step 3: Calculate the average effort by using the formula (M+O+P)/3.
Three-point estimation use cases
- Tracking historical data on M, O, and P estimates allows for continuous improvement and refinement of future estimations
Tips and best practices for using three-point estimation
- Encourage honest estimations
- Avoid bias toward overly optimistic or pessimistic scenarios
- Track historical data to adjust confidence intervals
- Use for complex tasks with high uncertainty
4. Affinity mapping
In this approach, team members collectively organize and categorize user stories or tasks into clusters with common characteristics.
For example, suppose your team is estimating the effort required for different features of a software project. In that case, they may group features related to user authentication into one cluster and data storage into another.
The visual representation of clusters helps gain a shared understanding of the components’ overall scope and relative sizes. It aids in identifying patterns and dependencies, allowing your team to prioritize and plan more effectively.
How affinity mapping works
- Step 1: List all tasks to be estimated
- Step 2: Organize the tasks into groups based on similarities or themes. Then, discuss and refine the groupings
- Step 3: Prioritize the identified themes or groups based on their estimated effort and importance
Affinity mapping use cases
- Great for prioritizing and categorizing a large number of user stories
Tips and best practices for using affinity mapping
- Use visual aids, such as sticky notes on a wall or a virtual whiteboard
5. Dot voting
In this agile estimation technique, team members use dot stickers to vote on specific items, revealing their preferences or priorities. Each team member is given a set number of dot stickers to allocate across the items under consideration.
For instance, if the team is prioritizing user stories, each member might have three dot votes to distribute among the stories based on their perceived importance. The items with the most dot votes are then ranked higher in priority or preference.
Dot voting is beneficial when you need to converge on a shared understanding of priorities quickly.
How dot voting works
- Step 1: Describe each task using cards or sticky notes
- Step 2: Give each team member a set of dot stickers to allocate based on their voting preferences for the tasks
- Step 3: Count the dot stickers on each card to determine the relative priority of the tasks
Dot voting use cases
- Prioritizes tasks based on perceived effort and team interest, encouraging democratic decision-making
Tips and best practices for using dot voting
- Clearly define the voting criteria (e.g., effort, complexity, importance)
- Combine with other techniques for deeper estimation
6. Bucket system estimation
In the bucket system estimation, you group items into buckets based on their relative size or complexity. It provides a structured way to assess and categorize tasks.
For example, if you’re estimating user stories, the buckets might range from ‘Low Complexity’ to ‘High Complexity,’ and your team members place each story into the corresponding bucket based on their assessment of its size.
One of the key advantages of the bucket system is its simplicity and ease of use. It provides a clear framework for categorizing items, making it accessible to experienced and new team members.
How the bucket system works
- Step 1: Establish clear criteria and effort ranges for each bucket (e.g., small = 1-3 days, medium = 4-7 days, etc.)
- Step 2: Have each team member place each task into the appropriate bucket based on its perceived effort
- Step 3: Discuss and adjust bucket placement to ensure an accurate representation of the project’s scope
Bucket system use cases
- Quick and efficient estimation for well-defined tasks, facilitating visual representation of the project’s scope
Tips and best practices for using the bucket system
- Use for smaller projects or well-defined components
- Track historical data to refine bucket sizes
7. Fibonacci sequence
This technique uses the Fibonacci sequence of numbers (1, 2, 3, 5, 8, 13, etc.) to represent increasing complexity. Team members assign these Fibonacci numbers to represent the relative size or effort required for tasks such as user stories or features.
For instance, if your team is estimating the complexity of coding tasks, they might assign a 3 to a relatively straightforward task, an 8 to a moderately complex one, and a 13 to a task with higher complexity.
The Fibonacci sequence acknowledges that estimating larger tasks comes with increased uncertainty, encouraging teams to focus on breaking down work into smaller, more clearly defined units.
How the Fibonacci sequence works
- Step 1: Explain the Fibonacci sequence and its use for estimation
- Step 2: Provide clear examples or descriptions of what each Fibonacci level represents in terms of effort
- Step 3: Get each team member to estimate the effort for the task using the Fibonacci sequence
- Step 4: Encourage discussion and refine estimation, if needed, to ensure relative sizing
Fibonacci sequence use cases
- Effective for relative sizing of tasks or user stories
Tips and best practices for using the Fibonacci sequence
- Maintain consistency in using the sequence to ensure accurate comparisons
- Avoid assigning values granularly; use broad values for large items
8. Analogy estimation
Analogy estimation is based on drawing parallels between the current task and similar completed tasks to estimate effort.
Team members compare the new task to similar past tasks and gauge the effort required based on the similarities or differences.
For example, to estimate the development effort for a new feature, the team may reference a similar feature implemented in a previous sprint.
This technique encourages the continuous improvement of estimation accuracy over time as the team gains more insights into the relationships between different tasks.
By identifying the connection between current and past work, analogy estimation enhances your team’s ability to plan and deliver outcomes more precisely.
How analogy estimation works
- Step 1: Discuss and identify past projects or tasks similar to the one being estimated
- Step 2: Recall the effort spent on the analogous project or task
- Step 3: Consider and adjust the effort based on any differences in context or complexity between the analogy and the current task
- Step 4: Use the adjusted effort from the analogy as the initial estimate for the current task and document the reasoning behind it
Analogy estimation use cases
- Useful when dealing with tasks that share similarities with previous work
Tips and best practices for using analogy estimation
- Ensure team members have a good understanding of past projects for accurate analogies
9. Top-down technique
In this method, the team initially assesses the overall scope or complexity of the project and assigns a broad estimate to represent the collective effort.
The team then decomposes the project into smaller tasks or user stories and refines the estimates for each component based on a more detailed understanding.
For example, to estimate a software development project, the team might first assign a high-level estimate for the entire project and then break it down into specific modules, assigning detailed estimates to each module as they delve deeper into the requirements.
By breaking down the project into smaller components after the initial high-level estimate, the team adapts to changing requirements and enhances the accuracy of their predictions.
How the top-down technique works
- Step 1: Break down the project into smaller, manageable components
- Step 2: Involve relevant experts to estimate the effort for each component individually
- Step 3: Sum up the individual component estimates to arrive at the overall project estimate
Top-down technique use cases
- Suitable for project managers or stakeholders in the early stages of project planning
Tips and best practices for using the top-down technique
- Consider adding a buffer to account for potential risks and unforeseen complexities
10. Bottom-up technique
The bottom-up approach is a suitable agile estimation technique for undertaking a detailed and comprehensive assessment of a project’s complexity.
In this method, the team initially breaks down the project into granular tasks or user stories, providing detailed estimates for each component.
For example, to estimate a software development project, the team identifies specific features or functionalities and assigns effort estimates to each. They then sum individual estimates to arrive at the overall project estimate.
You can use the bottom-up technique to enhance your team’s ability to adapt to project changes with a thorough understanding of the underlying complexities.
By focusing on detailed estimates for individual components, you can better account for specific requirements and potential challenges, resulting in a more realistic and informed project estimate.
How the bottom-up technique works
- Step 1: Break down the task into the smallest, well-defined units of work possible
- Step 2: Get each team member to estimate the effort for their assigned unit of work
- Step 3: Sum up the individual unit estimates to reach the estimate for the total effort required for the task
- Step 4: Compare the bottom-up estimate with any available top-down estimates and adjust, if needed, to ensure accuracy
Bottom-up technique use cases
- Best suited for detailed project planning with a well-defined scope
Tips and best practices for using the bottom-up technique
- Use historical data to validate and adjust estimates
ClickUp: Your Agile Estimation Ally
Looking for a tool to better implement agile across your organization?
ClickUp’s Agile Project Management elevates agile estimation from mere guesswork to a collaborative, data-driven process.
- ClickUp Time Estimates: Define clear timelines by setting estimated hours for each task within a user story, ensuring realistic workflow management
- ClickUp Time Tracking: ClickUp’s built-in time tracking functionality allows team members to record the actual time spent on tasks. Compare this data against estimated hours to understand variances and refine future estimations for similar tasks
- ClickUp Gantt view: Visualize the project timeline and dependencies, and quickly identify potential bottlenecks and adjust estimates to ensure smoother project flows
- Reports and dashboards: Generate personalized reports and dashboards to visualize estimated vs. actual effort for user stories and sprints. Identify areas for improvement and adjust future estimations based on data-driven insights
If you’re unsure where to start, let these handy project estimate templates show you the way!
Examples of how ClickUp enhances specific agile estimation techniques
Here’s how ClickUp’s features can smoothen the process of using the techniques we listed:
- Planning Poker and Fibonacci sequence: Integrate the relative values of task estimates into custom fields and use ClickUp’s Online Voting System Project Proposal Template to conduct virtual poker sessions
- T-shirt sizing: Create Custom Statuses in ClickUp for “Small,” “Medium,” and “Large” tasks and easily assign them to user stories based on discussions
- Three-point estimation: Use ClickUp’s Formula Fields feature to calculate the average effort for each story based on the M, O, and P values
- Affinity mapping: Organize user stories into ClickUp lists and visually group them based on similarities, facilitating effort estimation for each group
Mastering Agile Estimation Techniques
Estimating how long tasks take is crucial in software development. Agile estimation techniques, such as Planning Poker, T-shirt sizing, and the Fibonacci sequence, offer collaborative and adaptable approaches to navigate challenges and capitalize on advantages.
Estimation is a process of continuous learning, but agile teams using ClickUp can calibrate their judgment and get better at delivering predictable outcomes.
ClickUp enhances agile estimation techniques with features like time estimates, time tracking, Gantt view, and comprehensive reports and dashboards.