We're working in a time where the digital divide is widening between innovators and everyone else. Digital transformation is no longer a luxury but a necessity for staying relevant and competitive. Value stream management (VSM) is essential to accelerating your digital transformation, ensuring you're on the right side of this divide.
A value stream is just a set of actions that delivers value to your end customers. VSM is the strategic oversight and optimisation of this set of actions, from idea to delivery, ensuring innovation, adoption, and acceleration at an unprecedented pace.
VSM enhances, rather than replaces, DevOps to help you understand which changes will deliver the most value for your customers and what changes you can make to resource allocation to deliver the greatest returns. This way, you can focus on delivering meaningful outcomes more efficiently.
Value stream mapping is a crucial component of VSM, visually representing how products and services are delivered. It helps identify inefficiencies, reduce waste, and foster collaboration among teams. And VSM tools enable real-time monitoring and decision-making, supporting continuous improvement and strategic alignment.
How AI can help improve a value stream
AI is transforming all areas of business, and there's a powerful case for incorporating it into VSM, too. AI tools can more efficiently process and analyse data from your software development life cycle (SDLC), identifying patterns and anomalies and making predictions.
AI can take measurements and recognise metrics specific to a product's value or functionality on top of typical DevOps metrics like MTTR, change failure rate, and deployment frequency. It can also analyse the impact of tweaking a process or resource allocation to find the optimum outcomes.
All this information gives you a much deeper insight into your value stream and can help you make more informed decisions. Here are some of the ways AI can make a difference:
- Delivering data-driven insights—unlike humans, AI can analyse a vast amount of data with speed and accuracy from various sources—from production systems to customer feedback. All this data-crunching gives you insights into where bottlenecks and waste lie, and where you can make improvements.
- Predicting your process—being able to identify patterns and trends over time, AI can predict when demand will change, supply chain disruptions, and the likelihood of production delays. That means you can adjust your processes to fix problems before they even happen.
- Supporting continuous improvement—AI tools can monitor and analyse what's happening in real time to ensure your value stream is always aligned with your goals. It can even alert you when things go awry so your people can take action immediately.
- Managing risk—real-time data can help predict and flag potential risk factors, as outlined above, and AI can also improve risk management by streamlining identity verification processes, resolving fraud issues, and implementing end-to-end security protocols.
- Understanding the problem—fixing a problem is pointless if you don't understand why it's happened in the first place. AI can identify the underlying factors contributing to recurring problems so you can address the root causes immediately.
Introducing GitLab Flow with GitLab Duo
GitLab's DevSecOps platform has already embraced AI with GitLab Duo—a set of powerful capabilities that can help organisations develop code, improve operations, and secure software more efficiently. But how can these AI tools support VSM?
Meet GitLab Flow: the platform's prescribed and opinionated end-to-end workflow for an application's development life cycle (essentially, its VSM mapping process). It includes an inner feedback loop for specific update reviews and an outer feedback loop for application-wide improvements.
When combined, GitLab Flow and GitLab Duo can help organisations achieve significant improvements in end-to-end workflow efficiency—from planning to deployment and monitoring—leading to even higher levels of productivity, deployment frequency, code quality and overall security, and production resiliency and availability.
Here are some of the things GitLab Duo can add to your basic workflow to enhance and improve the process for everyone:
Speed things up with summaries
Not only can you save time defining product problems or new features when you create an issue using GitLab Duo's 'generate issue description' capability, but you can then use the 'issue comments summary' to summarise comments from all collaborators into one concise paragraph that distils all that information for you.
The same is possible for merge requests. When you're faced with a long list of updates to a feature made by a large number of stakeholders and need to get up to speed quickly, the 'summarise merge request changes' capability is invaluable. It lets the author of a merge request generate a natural-language comment to summarise what they're updating.
Get clarity with code explanation
If code is complex, unfamiliar to you, or poorly documented, it can take time to understand. GitLab Duo has an 'explain this source code' capability that explains what the code is for in natural language. You can also use GitLab Duo Chat to better understand the code in the IDE, giving the chatbot instructions focused on something specific, for example, the code's algorithm, why a static variable is used, or the performance gains or losses of using the code.
Take the stress out of testing
GitLab Duo's test generator capability lets you automate repetitive testing tasks to speed up testing, boost productivity, and catch bugs early. Using special commands, you can generate a testing suggestion for a piece of code in your editor and add your own instructions, such as using a specific test framework, focusing on extreme cases, or focusing on performance. You can also generate unit tests for new code added via a merge request.
Understand vulnerabilities and how to fix them
With GitLab Flow shifting security left in your pipeline, you'll be able to detect vulnerabilities much earlier in your SDLC. GitLab's built-in security scanners, analysers, dashboards, and reports have already streamlined this process, but GitLab Duo takes it further with its 'explain this vulnerability' capability. This helps devs and security engineers to understand a vulnerability by explaining what it is, how it can be exploited, and how to fix it.
Seamless review code
Alongside the 'summarise merge request changes' mentioned above, 'summarise my merge request review' helps to further ease the handoff of merge requests between authors and reviewers. This generates a summary of the reviewer's feedback for the update's author. It can be edited and refined before it's submitted. If you don't generate one, it happens automatically and is made available on the merge request page, the dialogue, the to-do list, and via email notifications.
Make the intelligent choice
At Adaptavist, we harness the power of the latest technologies to transform how organisations work—AI has become a big part of that. But we always put people first when it comes to people, processes, and technology.
That means working with you to understand your DevSecOps maturity, helping you develop practices that leverage the best that AI advancements have to offer, implementing new solutions that streamline your workflows, and training your teams to make the most of these new tools. Yes, an AI evolution is happening in software development, but you still need the right people and expertise to make it work for you.
Get in touch to learn more about how you can leverage tools like GitLab and AI technology to improve end-to-end workflow efficiency—increasing productivity, deployment frequency, code quality, and overall security, resilience, and availability for your software.
