Team reporting is great, but for larger organizations especially those that adopted SAFe, it’s essential to be able to get visibility and do planning on program level. SAFe prescribes several reports and metrics to track against (see here and here). Starting with Agile Reports for Jira 4.1.0, you can ensure that “SAFe” is not just a fancy word any more.

For this purpose, Program Predictability Measure Reports is exclusively for companies that live and abide by the SAFe doctrine recommendations. This gadget provides visibility into how the business value is delivered by your Agile Release Trains for the selected program increments.

This report is a key indicator of program performance and reliability, and helps you get more visibility on the above-the-team level, analyze delivery rates by different ARTs and ultimately – ensure for better program planning.

 

 

THE PROBLEM – ARE YOU TRULY SAFe?

SAFe depends on different scopes of short-term commitments from Agile teams, and trains to them to bridge business planning and outcomes. As a result, there’s enhanced integrity and collaboration between development and business.

However, PI objectives shouldn’t be seen as set of flat, inflexible, long-term deliverables.

For a business to do any sort of fruitful planning, it depends on their teams to provide some amount of reliable, predictable forecasting.

One day is too little, and it’s “those ARTs can’t commit to anything meaningful.”

Another day is too much, and it’s “those ARTs never do what they say they will.”

Neither situation is good! Both instances drive a wedge between business stakeholders and development which ultimately deteriorates trust and productivity.

 

In addition, a company can also alter its success measures to influence behavior.

For example:

  • Are we on time? If not, when can we deliver the committed scope?
  • Are we on scope? If not, what we will not deliver on due date?
  • Are we on top of quality?
  • Are we on flow? Any bottlenecks?
  • Backlog readiness for the next PI?
  • What is the average cycle time?
  • Can we predict well?

Putting that all into one equation, quantitative measurement is extremely important as it enables discussion on data and trends, analyze and identify potential issues, assess the results that are summarized on the Program Level, and make adjustments accordingly to the next committed scope.

So, how do you solve that? Program Predictability Measure reports! It provides visibility on how teams achieve their PI objectives against what’s planned by the Product Owners / Stake Holders.

 

USE CASES

To say the Program Predictability Measure report is the “Most Valuable Player” would be an understatement. This chart shares the program level metrics, and is essential for SAFe reporting:

  • Provides understanding of the bigger picture of how current business objectives are / are not fulfilled, and if the business value is achieved
  • Presents delivery rates across the PIs, and the tendency of how a certain ART is performing from one PI to another
  • Helps in setting realistic objectives
  • Reinforces the processes to avoid too much ‘work in progress’; to review and adjust scope, and compromise as necessary
  • Gives insights for significant external commitments and dependencies, and expose dependencies that require coordination
  • Communicates and highlights each team’s contribution to business value
  • Facilitates a common language between business and technology stakeholders
  • Creates the near-term vision, which teams should follow up to succeed
  • Drives velocity and support for the team’s legitimate technical challenges to deliver the maximum possible business benefit

 

THE REMEDY

PPM utilization and analysis provides several clear benefits in your SAFe process:

1. Reduced time-to-market – more reliable planning = faster production and release

2. Improved predictability – increased flexibility for changes in scope with minimal cost and enhanced client satisfaction

3. Expedited feature speed – feature cycle time is significantly decreased

4. Elevated efficiency – the cost per feature decreased from one PI to the next

5. Fewer defects – improved early detection of defects led to fewer escaped defects

6. Reinforced processes – dissolving silos in communication and collaboration between the teams

 

We’ll be adding more features soon. If you would like to request a feature – let us know!

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