ALM Works

What Every Organization Wants to Know

As a project manager, you field questions all day. Leadership asks, “When will I see a return on our investments?” Stakeholders ask, “What can we do right now to help improve outcomes later?” When you manage portfolio-level projects, answering these questions accurately can easily eat up your week.

Structure for Jira helps by collecting all of your project data in one place – across all the contributing teams and backlogs in Jira. Now it can use that data to help you predict completion dates, per project and per team.

Structured Predictions Provides Answers

In the age of Agile, one of the major problems for large-scale project planning is that not all of the requirements (normally contained in user stories) are known ahead of time. Agile teams create user stories through the grooming process, just in time for the next sprint. Structured Predictions uses the data in a structure to develop team profiles that predicts how many additional stories a team is likely to generate before they are in Jira, anticipates team performance, and estimates target completion dates for each team.

Let’s see what that looks like. Imagine we have a structure that represents an initiative the organization is trying to deliver by a certain date. It has a bunch of epics per contributing team, and those epics may or may not be groomed into stories. Here’s a snippet of what that structure might look like:

All the data from all the teams are in one place for the initiative, but it doesn’t answer the question, “when will it be done?” To get that answer, let’s connect Structured Predictions to our structure. Here is what we get:

1. Historical Cumulative Flow Diagram

This section of the graph shows the historical cumulative flow diagram (CFD) of past workflow transitions and ticket inventory to the current day. The "Y" axis of the CFD shows the number of issues and the "X" axis shows the dates. The points on the graph show the date at which an issue was in a specific workflow state. Areas of the graph representing different states are color-coded.

• Blue—work that is still to do (in the backlog)
• Yellow—work that is in progress
• Green—work that is done

By plotting all of the issue transitions for the project, the graph shows a historical representation of project progress. The slope of each workflow state represents the rate at which work is being created and completed for a project. See the section "Reading Cumulative Flow Diagrams" below for more information on how to assess project history and health.

2. Predicted Stories

The steep cliff in the "To do" area of the graph at the line labeled "Today" (see 4) is the result of the Structured Predictions algorithm predicting the number of additional stories to be added to the project. The predicted stories are added to the known project scope (the scope that is defined in Jira) at the current date, "Today".

3. Estimated Completion Dates

The completion date is predicted by running the team's performance model (described above) against the remaining scope defined in Jira plus the additional scope predicted by the algorithm for the team.

4. Today and Target Lines

The Today line represents the transition point of the graph from a traditional, historical cumulative flow diagram to a predictive cumulative flow diagram. The portion of the graph to the right of the Today line represents the simulated future for each team working on the delivery. Teams that are predicted to finish after the Target date (which you provide during configuration) are flagged in red in the Metrics table to the right of the graph.

5. Team Metrics

The Metrics section breaks down the key stats by team. There are six columns of data for each team, which provide some visibility into the underlying data that informs the predictions. This includes throughput by team, estimated future scope creation, and predicted completion dates by team.

Selecting a team in the metrics table changes the graph to show the predicted cumulative flow diagram (PCFD) for that team only. Here we have selected Team T32, and the graph now shows only that team’s performance for the initiative managed by our structure:

Simulate Future Initiatives Using Your Historical Data

Structured Predictions uses the team performance data identified by the structure you’ve connected to it. But what if you are starting a new initiative and no stories have been defined and no work has been done yet? If you have an epic level scoping of the initiative, you can still use Structured Predictions to supply end dates, by team. It will then use historical data about those teams to simulate the completion of the new, planned initiative.

Let’s say you have a structure that contains only epic level requirement definitions for each contributing team:

None of these epics have any defined stories, and no team has done any work for the initiative yet. Using a historical structure to supply the team performance data, here is what a 100% simulated initiative looks like using Structured Predictions:

Here we see which teams are predicted to generate the majority of scope, what throughput each team is likely to achieve, and what date they might complete their work. We recommend using this data to inform the conversation about what targets dates they can realistically set. Once those target dates are set, Structured Predictions can be used to track against those dates and take action early in the SDLC to mitigate risks.

How Do I Get Structured Predictions?

Structured Predictions is a solution from ALM Works that includes software and expert consulting services. Our team’s expertise is essential to ensure your configuration and usage will deliver the best possible projected delivery dates. It’s available via the ALM Works solutions team.

Our solutions group will walk you through:

• Review and support to help you optimize your Jira configuration for the best possible predictions
• Training for your key users
• Process integration support specific to your SDLC

If you’re interested in Structured Predictions, contact the ALM Works solutions team via email at solutions@almworks.com. We’ll be happy to discuss your unique requirements and pricing.