Organizations of all stripes are looking to master software at scale so they can thrive in the digital age. Yet for many years, traceability has held them back from becoming software innovators. For those companies in heavily regulated industries, end-to-end traceability—from ideation to operation—is not a choice but a critical business driver.
The enterprise software delivery process is a spiraling spaghetti bowl of cross-team work that comprises multiple disciplines, tools and processes, where much of the knowledge work is invisible, existing as manual handoffs between key stages. Obtaining one source of truth in a product lifecycle, therefore, has historically been a huge time- and labor-intensive undertaking. One that acts as quicksand for the acceleration efforts for healthcare, finance, medical and government initiatives.
Automating handoffs, however, can make the work visible, traceable and actionable, and the reporting process becomes dramatically faster and easier. The benefits are cross-organizational, helping:
- The teams that build and support the product portfolio.
- The management and optimization of the IT pipeline.
- The executives who want to reduce time and costs, and have increased confidence that their organization is creating value through software safely and securely.
Tracking the Product Lifecycle
Traceability in software delivery is about tracking where work originates right through to delivery (and back through the customer feedback loop). You may need traceability for several reasons:
- Your organization is heavily regulated and audited, requiring strongly documented proof of why any work is being done.
- The world’s simplest ask (or you’d think): automated release notes.
While the need for traceability is clear and the theory of building out end-to-end traceability is sound, it’s much harder in practice. Unlike the tech giants whose businesses are built around their Agile toolchains—making consolidating data for any reports a breeze—things aren’t so simple for traditional enterprises.
Data related to the planning, developing, testing, delivery and support of a product is stored in many different tools used by tens of thousands of IT professionals. Your toolchain, for instance, may use Planview for high-level strategic planning and allocations, Jira and Azure DevOps for development, MicroFocus QC for quality and test activities, Jenkins to automate releases and ServiceNow for support end users.
Without the means to automatically share information between these disparate systems, tracking the lifecycle of a requirement and its related design elements as it traverses downstream is exacting work. Traditional approaches, such as a requirements traceability matrix (RTM), are too slow to keep up sheer volume and velocity of modern software delivery work.
Manually finding all the key fragments of data across the toolchain for even a single iteration of a requirement can take weeks. The findings in these reports, for compliance or performance, will be out of date and inaccurate by time of publication. Worse still, the data lacks the nuance and sophistication required for a continuous iterative process.
Typically, a single product has many requirements and hierarchical relationships, dependencies and other linked information that travel through multiple systems. A single view of work in real time is essential and only possible by ensuring a continuous flow across the teams in the toolchain.
Visualizing Your Value Stream
Before you begin connecting your systems through integration, ask yourself the following to begin understanding your entire workflow:
- Where does work originate from? Typically, work arrives as business requests or service tickets and maybe even security vulnerabilities.
- Where does it go? How does it get to developers to be worked on?
- What is the release process, how are features released?
A value stream architecture diagram is a very effective way of sketching an overview of how work flows through the organization. It’s a very simple view but extremely powerful when it comes to having deeper conversations about the process at hand.
Once you have a good understanding of where you are at, you can begin introducing the two core elements that help you to achieve traceability:
- Collecting data from every stage of the process (ideate, create, release, operate) from disparate tools.
- Linking the separate data between tools to determine the relationship between stages.
Automating Value Stream Flow
By using third-party integration tools, you can automate handoffs between the teams across all key stages. At each step, you automatically collect information about the work items as teams work on them across the ideate, create, release and operation stages. For instance, when a developer submits code, you can use automation to link that code to a previous step in the process, as well as forward, to ensure that code once active can be traced directly back to a core business requirement.
Cross-organizational Benefits
Automated traceability provides end-to-end visibility that was previously not achievable without a herculean effort. Now you can answer those key questions from before: Where does work originate and how does it flow throughout the process?
For larger enterprises, scaling traceability manually simply isn’t feasible. The benefits of automated traceability can be felt at various levels of large organizations, both IT and business sides, including the following:
For practitioners:
- Remove manual duplicate data entry: Eradicate manual handoffs between teams, such a duplicate entry, email threads.
- Faster approvals: End-to-end traceability enables managers to review builds from the night before to accelerate the process.
For managers:
- Cross-system visibility: View release and build health across multiple systems in one place.
- Cross-tool reporting: No need to manually collect and merge multiple data sources; remove risk of manual error.
For executives:
- Time, cost savings from automating previously manual processes: Enable your teams to work on true value-add features for the business rather than manual work e.g., duplicate data entry.
- Reliable traceability reports: Increase confidence that the quality of the traceability reports will actually stand up to an audit or a compliance check. Traceability, along with bureaucracy, in regulated industries has long tethered the dogs of innovation, giving tech giants an open field to compete. With automation, enterprises can level the playing field.
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