Introduction

Today, I had some time to think about the contents of my upcoming Software Analytics workshop series. I came up with a Maturity Model to give students some hints to what extent they’ve adopted Software Analytics already in their environment. It’s a first draft that I want to share with you. So, here are the stages of my very first maturity model:

 

Stages of the Software Analytics Maturity Model

1. Known

Characteristics:

  • You are aware that it is possible to gain insights into software development by using situation-specific data analysis on software data
  • You are familiar with possible sources of software data that you have at hand

Preconditions to advance to the next stage:

  • Produce clean software data: Create atomic changes, use unique identifiers across different data sources, structure your software development process
  • Establish data-driven, problem-oriented thinking: Speak about the problems you have, identify the root causes and think about how you could measure the pain points

2. Used

Characteristics:

  • You made use of software data to show a problem
  • You ran a script for gathering the data and/or executing the analysis

Preconditions to advance to the next stage:

  • Document your analysis: Create a readable script that other developers can understand
  • Show analysis: Share your raw data, your script and well as your results

3. Defined

Characteristics:

  • You use the same set of tools for data analysis across your teams
  • You know which data sources you have at hand and how to access those

Preconditions to advance to the next stage:

  • Automate analysis: Find ways that allow you to run your data analysis automatically
  • Share analysis: Commit your analysis to a repository so that others can reproduce or adapt your analysis

4. Repeatable

Characteristics:

  • You use the same set of data analysis tools across your teams
  • You know which data sources you have at hand and how to access those

Preconditions to advance to the next stage:

  • Gain budget: Maintain a program that thrives on continuous improvement based on data analysis
  • Share insights: Create a community of software development analysts that discuss their findings and share their experiences

5. Integrated

Characteristics:

  • You take the use of data analysis tools to analyze problems for granted
  • You deploy measurement facilities in your environment to gather additional data

Usage

The Software Analytics Maturity Model should give you some orientation and a rough roadmap on how you could leverage data analysis to improve software development.

Discussion

How much have you adopted Software Analytics? What do you think about the model?

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Software Analytics Maturity Model
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