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| Category | Value Stream Management |
|---|---|
| Stage | Plan |
| Group | Optimize |
| Maturity | Viable |
| Content Last Reviewed | 2024-07-14 |
Thanks for visiting the Value Stream Management direction page. This page is actively maintained by the Optimize group.
You can contribute or provide feedback by sharing your feedback about your Value Stream Management experience in this survey, or posting questions and comments in the public epic.
Built as a single application with a unified data store GitLab Value Stream Management (VSM) allows all stakeholders from Executives to individual contributors to have visibility to the entire software delivery lifecycle - enabling teams and managers to understand all aspects of productivity, quality and delivery without the “toolchain tax”.
Value Stream Management helps organizations understand and optimize the impact of their activities across the DevOps lifecycle by:
To achieve this, users can map Value Streams and finds bottlenecks in their process. Value Stream Analytics provide a high-level overview of end-to-end cycle and stage times and is the starting point for drilling down into each stage of a value stream to identify opportunities for improvements.
Value streams in the context of DevSecOps workflows refer to the series of actions that take place to add value to a customer, starting from the initial request through to the realization of that value by the customer. Organizations typically have several value streams, catering to both external and internal customers.
By defining DevSecOps workflows as value streams, you can bridge the gap between business and technical teams. The starting point for this optimization is to focus on business outcomes and the creation of customer value, ensuring that each step in the workflow contributes to delivering meaningful results to the customer.
See it in action with this live VSA example—test it out yourself!
In order to accelerate customer value, it is not enough to streamline the work in a single area. We need to optimize delivery across multiple stages to improve enterprise lead times. Therefore in addition to the Value Streams Dashboard and Analytics as part of Gitlab's Value Stream Management (VSM) solution the Optimize group maintains a variety of actionable reports with different levels of insight into Gitlab's DevOps stages. Here is a summary of what’s available today:
As the place where work happens, GitLab can also unite visualization with action, allowing users to jump from learning to doing at any time, without losing context.
DORA metrics are in a separate category, however in the context of Value Stream Management, measuring DORA provides valuable insights into the speed, quality, and reliability of software delivery.
The DORA metrics will continue to be the core measurements for engineering work in the value stream, and remain embedded in the VSM optimization flow.
GitLab will be the tool of choice for the data-driven DevOps organization — enabling teams and managers to understand all aspects of productivity, quality, security and delivery without any complex configurations or data scientists.
Demonstrate the value of GitLab AI features, by adding "AI Impact" analytics to the Value Stream Dashboard and Value stream forecasting.
Expanded Value Stream Dashboard to enables organizations with a comprehensive overview of the value they deliver to customers and optimize their software development processes to deliver better software faster. To achieve this, we will focus on:
Enhance usability: Deliver excellent "out-of-the-box" experience for ~"Category:Value Stream Management" to visualize for everyone the unique power of measuring software delivery value in a single DevSecOps platform. To achieve this, we will focus on:
Leverage GitLab Duo suite AI capabilities for boosting productivity when using VSM and DORA.To achieve this, we will focus on:
Expanded "AI Impact" analytics to the Value Stream Dashboard, to provide more holistic view of the ROI from the investments in AI features. This include adding tiles with Duo Pro seats: Assigned and used, Acceptance Rate % and Duo Chat: Unique Users and adding sparklines into the AI Impact table.
Adding a new stage events for custom Value Stream Analytics - "MR first reviewer assigned" - With this new event teams can identify where delays occur in the review process, find opportunities to improve collaboration, and encourage a culture of responsiveness and accountability among team members.
Mature Value Streams Dashboard for Executives to enable decision-makers to identify trends, patterns, and opportunities for digital transformation improvements.In the next 1-3 milestones, we will focus on the following:
Executive-level summary of key metrics related to software performance and flow of value across the organization. These views will visualize the highest level of data about health of the software organization, and the DORA Performers score top to bottom. Adding "Usage overview" panel, to help the executive understand how the team is utilizing the platform.
Adding VSD Scheduled Reports as a CI/CD component - tool which allows you to periodically schedule a report with the most recent metrics from the Value Streams Dashboard feature. This will help decision-makers to focus on analyzing insights rather than spending time looking for the right dashboard with the relevant data.
Customizable widgets to show data that is relevant to user's goals and needs. Adding the "Product Analytics section" customizable UI capabilities. Integrate the Value streams dashboard page into the product analytics schema driven UI.
Value Streams Dashboard - Adding AI forecasting to optimize planning in real-time. Forecasting will help software leaders and PMO plan for the future by predicting upcoming trends and identifying potential opportunities and challenges. This can help organizations be more proactive in their decision-making and planning processes.
Adding VSA settings with label filters configuration. In a similar way to boards, teams want to use saved filtered labels with value streams.
Improving Issues Analytics to optimize the VSM lifecycle - Add total issues completed ("issues In/Out - Open vs Closed").
Enhanced VSA stage time investigation to help users quickly understand what has happened in the specific stage by visualizing the performance of the stage with the context of the work item (issues or MRs).
Adding the first phase of the "AI Impact" analytics to the Value Stream Dashboard. Using this MVC users can observe how changes in "Code Suggestions usage rate" metric correlate with changes in others software development life cycle (SDLC) metrics.
Adding a new usage overview panel in the Value Streams Dashboard. This new visualization gives a clear picture of GitLab usage in the context of software development life cycle (SDLC).
Introducing a new median time to merge metric and a new "Contributor Count" metric in the Value Streams dashboard, to enable software leaders to gain insights into the relationship between team velocity, DevOps performance, software stability, security exposures, and team productivity.
Simplified the configuration file schema for Value Streams Dashboard. In the new format, the fields provide more flexibility of displaying the data and laying out the dashboard panels. With the new framework, administrators can track changes to the dashboard over time.
Simplified configuration file schema for Value Streams Dashboard
Introducing the New ClickHouse-Based Contribution Analytics and the Contribution Analytics on GitLab.com will now run through the ClickHouse Cloud cluster.
Adding filters inherit to the link between VSA "Lead time" and "Issue Analytics". Value stream analytics now applies the same filters when drilling down from the Lead time tile to the Issue Analytics report.
New stage events - iteration event. This improve the tracking of development workflows in GitLab, we added the Value Stream Analytics has been extended with a new stage event: "Issue first associated with an iteration".
Adding new metric - "Issues closed" to the "Issues Analytics" report to help software leaders to track the total number of resolved issues over a specific period. With this addition, Gitlab users can now gain insights into trends associated with their projects and improve the overall turn-around time and value delivered to their customers.
Introduce group-level landing page for "Analytics Dashboard" menu item. This enhancement ensures a more consistent and user-friendly navigation experience to the Value Streams Dashboard.
New drill-down view from Insights report charts. New drill-down capability added to the Insights reports allows you to drill down to the Issue analytics report for deeper analysis.
Adding predefined date range for value stream analytics - making it more efficient and user-friendly to understand where time is spent during the development lifecycle.
Releasing the Value Stream Dashboard - this first release is focused on measuring software development (DORA4), understanding security exposure and the flow of value delivery (Value Stream Analytics) across projects and groups.
Measuring SPACE framework metrics in GitLab
Top 3 Competitors:
Based on our analysis, we've identified Planview-Tasktop as the Best In Class (BIC) competitor over Digital.ai and Plutora.
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.
Based on our analysis, we've identified these gaps against Tasktop:
| Gap | Roadmap to close this gap |
|---|---|
| Limited Analytics & Visualization capabilities | Adding Value Stream Dashboard - Comparison page, Overview page, Schema-driven customizable UI |
| limited flow analysis | Add VSA Overview cumulative flow diagram, Add Stage time - scatterplot, Add SAFe Flow Metrcis, Usability improvements to "tasks by type" chart |
| limited number of integrations | VSA API |
| Missing value delivery metrics | Adding business value metrics, Adding OKR Health status |
Digital.ai AI-Powered DevOps platform. Digital.ai has been on a multiyear, multiacquisition journey that includes Arxan, CollabNet VersionOne, Experitest, Numerify, and XebiaLabs. Its plan to be a front-runner in AI-driven software delivery for Global 5000 enterprises.
XebiaLabs' analytics (acquired by Digital.ai) 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.
Plutora Analytics Plutora is a privately held global software (SaaS) company, providing Value Stream Management solutions for enterprise IT in the areas of Release Management and Orchestration, Test Environment Management, Deployment Management, and Analytics.. Plutora 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.
Key Features for Comparison:
GitLab vs the Top 3 Competitors - Planview-Tasktop/Digital.ai/Plutora:
| Feature | GitLab | Planview-Tasktop |
|---|---|---|
| Data Analytics | 🟨 | 🟩 |
| Capturing Data, Metrics and KPIs | 🟨 | 🟩 |
| Common Data Model | 🟩 | 🟩 |
| Integrations | ⬜️ | 🟩 |
| Value Measurement | ⬜️ | 🟩 |
| Governance and Compliance | 🟩 | 🟩 |
| AI/ML | ⬜️ | 🟨 |
| Feature | GitLab | Digital.ai |
|---|---|---|
| Data Analytics | 🟨 | 🟩 |
| Capturing Data, Metrics and KPIs | 🟨 | 🟩 |
| Common Data Model | 🟩 | 🟩 |
| Integrations | ⬜️ | 🟩 |
| Value Measurement | ⬜️ | 🟩 |
| Governance and Compliance | 🟩 | 🟨 |
| AI/ML | ⬜️ | 🟩 |
| Feature | GitLab | Plutora |
|---|---|---|
| Data Analytics | 🟨 | 🟩 |
| Capturing Data, Metrics and KPIs | 🟨 | 🟩 |
| Common Data Model | 🟩 | 🟩 |
| Integrations | ⬜️ | 🟩 |
| Value Measurement | ⬜️ | 🟨 |
| Governance and Compliance | 🟩 | 🟨 |
| AI/ML | ⬜️ | ⬜️ |
More competitors in our Landscape:
Targetprocess tries to provide a full overview of 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.
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.
CA Agile Central combines data across the planning process in a single integrated page with custom applications available to CA Agile Central users. The applications can be installed in custom pages within CA Agile Central or on a dashboard.
Gartner Market Guide for DevOps Value Stream Delivery Platforms. It is also possible to utilize GitLab's Value Stream Management as a Software Engineering Intelligence Platform.
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:
Other Analysts have highlighted that Gitlab data gathering has much to offer and much more to mine and enable the insight generation. We have an immediate opportunity i to extend the insight generation based on the data gathered in the delivery pipelines. Once this is achieved we will integrate additional data sources beyond the DevOps toolchains.
We have the ability to reach the decision makers that are onsuming the insights generated from the Gitlab platform, and one of the key elements here is getting beyond the DORA 4 metrics into those that are more specifically targeted: security, compliance, financial, product, but also enterprise architecture, AI/ML delivery teams and the like.
Additional functionality, requested by clients includes:
When I am new to value stream practices; I want to learn what’s important, why it’s important and how to use it, so that I can use the tool effectively and adapt to my organisation’s needs.
| Job statements | Maturity | Confidence | Source |
|---|---|---|---|
| When I am new to value stream practices; I want to learn what’s important, why it’s important and how to use it, so that I can use the tool effectively and adapt to my organisation’s needs. |
|
Not validated | Issue |
When I am establishing practices to measure my value stream, I want to define the flow of work required to ship value to my end users so that we can visualize how efficiently and reliably value is delivered.
| Job statements | Maturity | Confidence | Source |
|---|---|---|---|
| When I am establishing practices to measure my value stream, I want to define the flow of work required to ship value to my end users so that we can visualize how efficiently and reliably value is delivered. |
|
Not validated | Issue |
When I track my value stream I want to quickly understand the software delivery status so we can improve our performance in near real-time and enforce DevOps best practices and governance.
| Job statements | Maturity | Confidence | Source |
|---|---|---|---|
| When I track my value stream I want to quickly understand the software delivery status so we can improve our performance in near real-time and enforce DevOps best practices and governance. |
|
Not validated | Issue |
When I am optimizing my value stream, I want to identify opportunities for improvement, or detect risks in the delivery of value to customers.
| Job statements | Maturity | Confidence | Source |
|---|---|---|---|
| When I am optimizing my value stream, I want to identify opportunities for improvement, or detect risks in the delivery of value to customers. |
|
Not validated | Issue |
When evaluating my value stream, I want to link software delivery metrics to value metrics so that I can understand the value of the software workstream.
| Job statements | Maturity | Confidence | Source |
|---|---|---|---|
| When evaluating my value stream, I want to link software delivery metrics to value metrics so that I can understand the value of the software workstream. |
|
Not validated | Issue |
This category is currently Viable. Our next step is Complete (see epic). You can read more about GitLab's maturity framework here.
