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Improve Flow.
Be Predictable.

Understand how work really moves through your process so you can ask the right questions, drive meaningful improvement, and accurately forecast outcomes in uncertain situations.

Cycle Time Scatterplot

Set Service Level Expectations (SLEs)

By looking at how quickly you finish work in the past, you can understand how long it may to take you to complete future work. SLEs help the team know what they are capable of!

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Aging Work in Progress Chart

Secret weapon to improve predictability.

Know exactly how old your current work is and compare it to past data for context. Begin to control aging and maintain or improve your current level of predictability.

Monte Carlo Simulations

Forecast in uncertainty with probabilities

Our Monte Carlo simulations help you get an idea of how likely any forecast is for any set of work. We use the variation in your historical data to run more than 10,000 trials! We have simulations for both fixed dates and fixed scope.

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Purchasing Options

All free trials are 30 days or more!

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Import your data from Jira, Trello using our built-in wizards, or any external app via file upload

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Get the power of ActionableAgile without leaving Jira. Available for Cloud, Server and Data Center

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Analyze flow directly in Azure DevOps Cloud. For single users or whole organizations

Don't take our word for it, listen to our customers

ActionableAgile helped us improve our ability to anticipate delivery outcomes by using probabilistic forecasting and flow metrics. Our throughput almost doubled, and the team got better at splitting and sizing work into meaningful, valuable chunks. Our cycle times were reduced by almost 50% or more for 85% of our completed work items. Our WIP significantly reduced, so we had teams that were not overwhelmed or overburdened. As a result, we reduced context switching and enabled the teams to experiment with pairing and swarming to get things done.

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Haroon Khalil, Executive Agility Coach

By regularly forecasting with ActionableAgile, we could clearly show when circumstances impacted our delivery timescales; previously, these would have been recognized as affecting our delivery. Monte Carlo simulation's what-if scenario planning function has enabled us to discuss what is happening and if trends are changing with stakeholders and teams. This allowed us to take meaningful action at the soonest possible opportunity and put the decisions with the right people.

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Julie Starling, Agile Delivery CoP Manager

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