Our Analytics tool works by taking your own date-driven process data to turn it into meaninful Analytics. Your data can come in the form of a specially formatted CSV, MS Excel (see an what an example data file looks like here), or JSON file, or can be automatically imported from Jira using our wizard. Please visit our Quick Start page for more information on getting started.
Absolutely not. Your data is yours and it should stay that way. You never transmit your data to us, so we never get a chance to store it. The whole application runs completely within your browser on your local machine.
You can sign up for a 14-day free trial of the full version of ActionableAgile Analytics (no credit card required) by visiting https://analytics.actionableagile.com. To learn how to get started with your own data, visit our Quick Start page. When you’re ready to buy, you can find our Purchasing Options here.
We integrate with Jira and Azure DevOps Services (formerly VSTS). You can also load your data directly via a CSV or XLSX (MS Excel) file (see how here here). Bottom line is, if you have access to your data, then you can use our tool. For more information about importing data, and to try the full version of ActionableAgile Analytics with your own data, visit our Quick Start page. If you use a tool that we don't support yet, Contact Us for information about custom integration.
We first require that in your process you have a well-defined workflow stage that you consider an item to have started and you have a well-defined workflow stage that you consider an item to have finished. From the workflow data that you upload, then (see above), we take the last workflow stage's date and subtract the first workflow stage's date and add 1 (the 1 makes the calculation inclusive and prevents Cycle Times of 0).
Analytics, however, provides you with more granular control over which workflow stages you want to count as started and finished. As you may have noticed, there is a control called Workflow Stages on our right sidebar which you can use to disable (or enable) workflow stages. We will always calculate Cycle Time from first workflow stage selected on the sidebar to the last workflow stage selected on the sidebar.
You can see the workflow data that is being imported into Analytics via our Source Data "chart," which can be found in the dropdown menu at the top center of the plugin. The first line shows the column names, and every line after that is a work item and the dates it enters each workflow stage. When you enable workflow stages with the Workflow Stages control, you can use this page to see how your data changes.
After loading your data into Analytics, there is a section on the right sidebar titled "Workflow Stages" that lists all of the imported workflow stages. There, you can check and uncheck workflow stages to change which workflow stage counts as started and which workflow stage counts as finished. The first selected workflow stage is when Cycle Time begins and the last selected workflow stage is when Cycle Time ends.
In short, no. We recommend leaving the work item in the column where it is blocked and then adding a “Blocked” attribute or tag to the item. This allows you to measure total time blocked without disrupting your workflow. Additionally, the Flow Efficiency Chart uses this information and can tell you how much time items spend waiting versus actually being worked on.
If you have a well-defined workflow, Analytics can help you regardless of your methodology. The most important thing is deciding when work starts and when it finishes--that’s all we need to determine the key metrics of WIP, Cycle Time, Throughput, and Age. We’ll load other information about your work and workflow from the data you give us, but starting and finishing work is by far the most important thing.
After your data is loaded into Analytics, you can use the Workflow Stages control to select the parts of your workflow you want to use. Work is considered to be started when it enters the first enabled workflow stage, and it’s done when it enters the last selected stage, so checking and unchecking boxes will change all your metrics. Since the data is already loaded, it’s fast, so feel free to play around with different settings and filters.
It can work well with Scrum, but it really matters when you start and finish your work items. If your Scrum Team pulls all Sprint Backlog PBIs into progress at the beginning of the Sprint, and then closes all of those PBIs at the end of the Sprint (Scrum does not necessarily recommend doing this, by the way), then you may not get the results you are looking for. For more on how to use flow metrics in your Scrum-based process, please see Scrum.org's Professional Scrum with Kanban (PSK) class.
No. There are many complicating factors at work here, including allowing for exceptions, handling holidays, and dealing with work that was completed on excluded day. In most cases it causes more problems than it solves, without improving the accuracy of the results.
Our co-founder and CEO, Daniel Vacanti, writes about this extensively in his books, which we highly recommend. You can read about this topic and more in those books, which you can find here.