Improve your Software Delivery Performance with Behavior analytics

Reach your development project's value delivery by getting higher code quality, better performance, and shorter cycle time.

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Engineering Intelligence Tool

How do you measure your software development?

There are no universally accepted software development KPIs in the industry.​ There are a lot of challenges caused by the lack of obejctive metrics. Are you facing any of them?

Low Transparency

Difficult to measure performance objectively, especially, at larger organizations and lower trust environments, like outsourcing companies.​

Lack of Visibility

How can I improve my visibility on an oversized team without losing quality insight? How can I scale my team without loosing visibility on their performance?

Low Level of Collaboration

How much does poor teamwork cost me? Is there synergy in my team?

Difficult to Benchmark

Development is subjective and a creative process. It is difficult to compare team members with different skill sets, or projects in different phases.

Lost Project Momentum

How can I intervene faster and prevent problems from spiraling out of control?

Unnecessary Costs

How much do I spend unnecessarily on bad habits?

How does Gitential help you achieve more value?

The engineering intelligence tool provides software teams the best analytics and recommendations to build better and more sustainable code and products. We analyze the source code and its evolution in git repositories using unique language diagnostic algorithms, and other statistical models.

Cost-Effective Project Deliveries

On-Time Software Release

Improved Code Quality

More Collaborative Teams

By Analyzing Delivery teams' Activities

Gitential Provides
Insights On

  • How much development has been done recently?
  • Do our developers work efficiently?
  • What is our team’s code writing velocity?
  • Is our code getting dramatically more complex?
  • Are we increasing our automated testing?
  • Do our developers effectively collaborate?
  • Who are my silent heroes?
  • What is my team’s coding behavior?
  • Do we have any technology knowledge gap within the company?
  • Are we using best practices that supports smooth operations?

These are just a few examples of what you can understand by using Gitential. For more examples, please check out our use cases here:

Discover Gitential insights

Quickly identify if any of your programs are at risk

The efficiency of one of the programs has declined dramatically together with the implemented work. What happened?

Be ready to ask the right questions on your monthly / quarterly meetings with your team to understand how you can help resolving program delivery risks.

Gitential Analytics
Gitential Analytics

Identify issues of poor project performance and create plan to improve it

The CTO asks why the Microsoft project is at risk.

More developers (Contributors) are added to the team and they are working longer hours (Coding Hours), but still the effectiveness (Code Volume) and the code quality is not improved compared to last month.

Checking the repositories’ analytics, the finding is that working on one of the repositories has dropped the developer’s efficiency.

While checking the performance driver metrics, it’s visible that this project’s code complexity has risen dramatically in the last month.

Instead of adding more and more headcount to the dev team, it is better to discuss with the software engineering leads what specific skillset they are missing from the team that makes the implementation more difficult.

Keep your team together

Junior developers became part of the team. How should we improve their performance?

Moritz is a newbie and while his code writing efficiency is improving (less of his code needs to be re-written) he is getting slower writing code.

Checking out the team’s collaboration mapping we can see that Moritz is only collaborating with Ioki, who is a new joiner too.

Find a high-performer mentor to Moritz in the team so he can grow into a better performer though internal guidance.

Find knowledge gaps for developers to grow

The efficiency of one of the best software engineers just decreased dramatically. He committed less code but with higher error rate. What happened?

Let’s look at Martin’s performance

  • He is a very good performer, but he didn’t really collaborate with the team.
  • Whenever he committed in the last month, quite high percentage of the code must have been rewritten.

  • He didn’t implement any test lines in his commits.

  • His committed code complexity even dropped in the last month.

Talk to Martin and try to figure out the reason behind his performance drop. It could loss of motivation or signs of burn-out, which can be prevented when noticed in time.

Highlight the items you found so he understands he needs to use testing to improve his code quality and work more closely with his co-workers to use best practices to be able to commit more.

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