| Stage| Maturity | | — | — | | Manage | Minimal |
Thank you for visiting the category strategy page for Value Stream Management and Analytics. This page belongs to Virjinia Alexieva (E-Mail, Twitter).
This strategy is a work in progress and everyone can contribute by sharing their feedback directly on GitLab.com, via e-mail, or Twitter.
Over the years, software has become more powerful and specialized, while the teams who create, build, deliver and analyze the performance of products more disconnected, despite the increasing time spent on updates and status reports. In order to scale and speed up the delivery of quality products, silos have to be broken but the business, product managers and engineers still use different tools glued together by imperfect integrations. We strongly believe that having a single application for the entire software development lifecycle is already a huge step forward, but we are only just starting to explore ways to surface valuable insights and recommendations, which will help organizations increase transparency and productivity across teams and connect the business with engineering.
Value Stream Mapping focuses on understanding and measuring the value added by the flow of activities in the software development lifecycle. In the time of technological disruption we are in, success will be largely dependent on the ability of enterprises to define, connect and manage software and business value streams. Often times, this will coincide with a culture shift requiring many enterprises to adapt the way they work. At GitLab, we are making a small step towards connecting the business with engineering by using issues and MRs with labels associated with OKRs, for example.
Our first attempt at helping organizations get a better understanding of their flow was the introduction of Cycle Analytics for all customers that follow the GitLab Flow. Cycle Analytics got a lot of attention and we quickly understood that while we are striving to define best practices, different organizations have different value streams and workflows and we need to support the ability to define and measure these customized workflows in GitLab in order to move the industry forward and serve our customers better. As of June 2019, Cycle Analytics is officially part of our VSM solution.
We want to provide consistent visibility of the end-to-end flow of how software value is created (what we define as a value stream), so that it can be managed, optimized and further automated. For that we would like to provide dashboards that show value streams at a high level and encourage consistent language and definitions but also allow drill-down in order to identify bottlenecks or drivers for positive or negative patterns and behavior. Some of the questions we want to answer are:
There are important drivers to efficiency and quality that don't necessarily revolve around people such as the complexity of our code, the state of code hotspots and test coverage. While we strive to provide recommendations and checks around code quality on merge requests, we believe there is a lot more that can be done on the repository as whole, which we will cover under Code Analytics. We view Code Analytics as complementary to VSM, but all analyses will be done from the point of view of the code, rather than value stream.
During the minimal and viable state of the category, we aim to cater to the needs of Product Managers and Development Team Leads in their efforts to improve velocity and predictability of their value streams. As we build out the category, we hope that Department Leads and Senior Executives will have one place where they could oversee the progress of their teams and identify best practices and negaitve pattens that inspire improvements across their organizations.
Since many organizations are just starting to explore analytics in order to increase efficiency and predictability in the software development cycle, we expect the category to change quickly in response to feedback.
In our next releases, we will:
This category is currently at the Minimal maturity level and our next maturity target is Viable by October 2019. Please see our definitions of maturity levels and related epics.
TaskTop is exclusively focused on Value Stream Management and allows users to connect more than 50 tools together, including Atlassian's JIRA, GitLab, GitHub, JamaSoftware, CollabNet VersionOne, Xebia Labs, and TargetProcess to name a few. Tasktop serves as an integration layer on top of all the software development tools that a team uses and allows for mapping of processes and people in order to achieve a common data model across the toolchain. End users can visualize the flows between the different tools and the data can be exported to a database for visualization through BI tools.
While we understand that not all users of GitLab utilize all of our stages, we believe that there is already a lot of information across planing, source code management and continuous integration and deployment, which can be used to deliver valuable insights.
We are starting to build dashboards, which can help end users visualize a custom-defined value stream flow at a high level and drill down and filter to a specific line of code or MR.
CollabNet VersionOne provides users with the ability to input a lot of information, which is a double edged sword as it can lead to duplication of effort and stale information when feeds are not automated. It does however, allow a company to visualize project streams from a top level with all their dependencies. End users can also create customizable reports and dashboards that can be shared with senior management.
Plutora Analytics seem to target mainly the release managers with their Time to Value Dashboard. The company also integrates with JIRA, Jenkins, GitLab, CollabNet VersionOne, etc but there is still a lot of configuration that seems to be left to the user.
Targetprocess tries to provide full overview over the delivery process and integrates with Jenkins, GitHub and JIRA. The company also provides customizable dashboards that can give an overview over the process from ideation to delivery.
Although GitPrime doesn't try to provide a value stream management solution, it focuses on productivity metrics and cycle time by looking at the productivity of a team. It exclusively uses only git data.
Naturally, Azure is working on adding analytics that can help engineering teams become more effective but it's still in very early stages. It has also recently acquired PullPanda.
Similarly to GitPrime, Code Climate focuses on the team and uses git data only.
Similarly to GitPrime, Gitalytics focuses on the team and uses git data only.
XebiaLabs' analytics are predominantly focused on the Release Manager and give useful overviews of deployments, issue throughput and stages. The company integrates with JIRA, Jenkins, etc and end users can see in which stage of the release process they are.
CloudBees DevOptics is focused on giving visibility and insights to measure, manage and optimize the software delivery value stream. It allows comparisons across teams and integrates with Jenkins and Jira and SVM /VCS solutions.
Forrester's New Wave: Value Stream Management Tools, Q3 2018 uncovered an emerging market with no leaders. However, vendors from different niches of the development pipeline are converging to value stream management in response to customers seeking greater transparency into their processes.
Forrester’s vision for VSM includes:
Additional functionality, requested by clients includes:
We are just getting started, but senior management from the development organization has expressed interest in what we are building and we are looking for their feedback. Every single issue in the space we create should be something that the Engineering Executives find helpful. An initial list of issues includes:
Relevant links: Development Metrics Working Group, Development Metrics Agenda
