Better Estimation with Favro: A Throughput Metric Approach Using Control Charts for Accurate Project Timelines
Estimating project timelines accurately is a major challenge for teams, often resulting in misjudged timelines and pressure to meet unrealistic deadlines. Traditional tools and methods, such as JIRA, Monday, or Asana, rely on breaking down projects into numerous small tasks and having team members estimate each one. While this might provide a detailed estimate, it often gives a false sense of precision, as these individual estimations are rarely accurate.
By shifting from a task-based approach to a flow-based method, using control charts and throughput metrics, teams can develop empirical estimates grounded in actual data, providing a more reliable and efficient estimation method.
The Problem with Traditional Estimation Methods
In most traditional estimation workflows:
Tasks are broken down into smaller subtasks or tickets.
Estimates are assigned to each subtask by individual team members.
Estimates are aggregated to create a project timeline.
However, this approach often results in three key issues:
Inaccuracy: Teams tend to underestimate the time required, leading to missed deadlines.
High effort: Estimation meetings and adjustments take time away from actual project work.
False Scope View: Often, tasks that are estimated are not always pushed to completion and may stay in the backlog indefinitely. This can skew the overall project scope, creating an inaccurate view of progress and workload.
Throughput Metrics: A Flow-Based Approach in Favro
Throughput metrics offer an alternative by measuring the actual flow of work items completed over time, rather than attempting to predict the time needed for each individual task. In Favro, this flow-based approach allows teams to:
Track the rate at which tasks move from start to completion.
Use historical data to project future timelines with more confidence.
With throughput metrics, teams can focus on consistently completing work items, leading to more reliable estimates and a smoother, more predictable workflow.
Favro Control Chart widget
How Control Charts Improve Estimation Accuracy
Control charts are a powerful tool in Favro that visualize the workflow and time taken by each task or card as it progresses. These charts provide insight into the entire work process, highlighting stages and bottlenecks that impact timing.
Here’s how to set up and use a control chart in Favro:
Set up your team’s workflow stages:
For example: "To Do," "Doing," "Review," "Ready for Launch," and "Done."
Visualize progress:
Control charts display bubbles representing individual tasks and how long each has taken in a given stage.
They also show a rolling average and standard deviation, helping teams track the typical completion time and variations over time.
Focus on specific workflow segments:
Control charts can filter stages (e.g., time from “Doing” to “Ready for Launch”) to give more granular insights into particular areas.
With this approach, teams can derive the median completion time for each task or process segment, using these numbers as benchmarks for future estimates.
Bubble representing "Card3" with it's metrics
Practical Example: Using Control Charts and Throughput Metrics for Estimation
Let’s look at how to use these tools in practice:
Set a Median Baseline:
Suppose a control chart shows a median time of 4 days for tasks to go from start to finish. For tasks that need to move from “Doing” to “Ready for Launch,” the median time is 2 days.
This median value can be used as a straightforward estimate for similar future tasks.
Update the Backlog with Empirical Data:
Instead of guessing, teams can use the median throughput value (e.g., 4 days) directly in the backlog. This saves time and reduces guesswork, allowing estimates to be based on past performance.
Enhanced Accuracy:
Empirical data replaces speculation, allowing the team to avoid frequent adjustments. Over time, this approach leads to much more accurate project timelines and helps maintain consistency across projects.
Advantages of Control Charts and Throughput Metrics for Estimation
Time Efficiency: Teams spend less time on speculative estimation sessions, allowing members to focus on actual work.
Team Autonomy: Empirical estimates reduce micromanagement and give team members greater agency.
Improved Accuracy: By basing estimates on historical completion times rather than projections, timelines reflect actual past performance and are inherently more reliable.
Workflow Transparency: Control charts help identify workflow bottlenecks, so teams can adjust processes to improve flow, not just for individual tasks but for the entire workflow.
Control charts and throughput metrics in Favro offer a data-backed approach to project estimation, making predictions that are more accurate and efficient than traditional methods. By focusing on the actual flow of work items, teams can create timelines that are achievable and grounded in reality, allowing for smoother project management and more productive team collaboration.
To learn more check out the video about More Accurate Estimates With Favro Control Charts:
