Making the Case for Requirements Analysis Software
The Importance of Requirements Analysis and Management
Clear, complete, and concise requirements are the foundation of every engineering project. They establish a common understanding of the project that provides the basis of the final design, as well as a clear project roadmap that can affect every stage of development. Requirements quality correlates to project success – that is why more than half of project failures can be traced back to poor requirements.
The writing and review of a good requirements document can be complicated and time-consuming. That has been compounded by increased pressure on companies to accelerate the development of increasingly complex products. As a result, reliance on manual processes for the management and analysis of requirements documents has become too complicated, challenging, and time-consuming to remain sustainable.
Manual requirements review is an unreliable process. There are simply too many elements to confirm against industry standards and best practices (as well as internal best practices) for these manual checks to be fully accurate. Poor requirements analysis can lead to costly corrections in later development phases that would otherwise be easier and less expensive to correct when requirements are first written.
New software tools and other technology have helped automate and accelerate nearly every phase of product development, from design to simulation and rendering. The same is true of requirements analysis. Software tools that leverage natural language processing (NLP) technology can help improve requirements development and review, accelerate the generation of requirements documents, and eliminate errors that can lead to design problems further along in the workflow.
How Requirements Analysis Automation Works
There are a number of key steps to developing a clear, accurate requirements document, and many of these rely on establishing well-defined policies and procedures before the document is even written. Organizations need processes in place to ensure accurate stakeholder mapping and involvement in product development; ensure collaborative requirement building; properly iterating those requirements based on feedback; and then freezing those requirements before additional development work begins.
Once there is agreement on the requirements, it is critical that the final document be clearly written and fully checked for completeness and compliance with industry best practices (such as INCOSE rules for requirements writing), partner specifications, and internal best practices. Because of this complexity, it is nearly impossible to fully evaluate a requirements document via manual review. That is where an automated analysis tool can be invaluable.
A requirements analysis tool such as QVscribe applies standards, principles and preferred structures to requirements writing. The software automatically checks requirements against industry rules, standards, and company best practices, eliminating the risk of human error in the initial review process.
Natural Language Processing tools can automatically check requirements against INCOSE rules (or other rules), and then highlight potential errors for review and correction. This makes it easier for users to write requirements following standard formats that are clear, unambiguous, and easy to understand.
QVscribe
.
QVscribe software from QRA Corp helps companies establish a direct and repeatable requirements process via standardization and automation. As an add-in tool for Microsoft Word and Microsoft Excel, as well as popular management tools like IMB DOORS Next, Polarion and Jama, QVscribe analyzes the quality and consistency of requirements inside those applications. By integrating with existing tools and presenting results directly within them, QVscribe reduces ambiguity and improves clarity at the earliest stages of development.
QVscribe can also be configured for custom analysis based on company- and department-specific standards. In this way, companies can use QVscribe to align teams on the lagnuage they use when writing requirements documents, and tailor the rules within the tool to match specific development stages and specific projects. This ensures consistency of documents and reviews across teams and departments, if they are using different software products to write and manageme requirements. The QVscribe software is built on accepted best practices for writing requirements, using Natural Language Processing to provide real-time and pertinent feedback. The software removes the complexities of requirements writing by applying industry standards, writing principles, and preferred structure, and is fully customizable.The software automatically checks for compliance with standards such as the INCOSE Guide for Writing Requirements, as well as proper use of imperatives, clear language, and other industry best practices.
QVscribe proactively identifies potential issues and removes the liability of failing to identify problems early in the requirements process.
Key features include
- Automated compliance with industry best practices
- Color-coded error detection • Customizable configurations to fit each company’s review processes
- Detection, enumeration and classification of all measurement units and noun phrases to verify correct use and location
- Detection of missing information, duplicate requirements, and potential contradictions
Benefits of Requirements Analysis Automation
By automating requirements writing and analysis, organizations not only improve the entire documentgeneration process, but also create benefits across the entire design and development cycle. Those benefits include:
Accelerated requirements processes and documentation. By eliminating lengthy manual compliance checks, reviews and additional copy editing, companies can more quickly create an accurate final requirements document.
Improved quality. Requirements are written more clearly, so that all stakeholders can understand them. With the ability to automatically highlight ambiguous or unclear language as requirements are being created, companies will generate documentation that is much easier for staff, engineers, managers, customers, and other partners to understand, regardless of their role or any potential language barriers.
Elimination of errors. Automated analysis and review will catch potential errors or compliance problems that might be missed in a manual review. That means the team can proceed with the project with confidence in the documentation.
Reduced manual reviews and rework. Because the automated analysis generates a more accurate document in the initial draft, there will be fewer manual reviews and potential rework during the requirements creation process.
bWhen mistakes are caught and corrected at the earliest stages of product development, the team can avoid making critical and costly design errors later in the process. The later in the process an error emerges, the more expensive it is to correct.
A 2004 NASA paper, Error Cost Escalation Through the Project Life Cycle, found that the relative cost of correcting an error discovered during the design phase versus during the requirements phase increased between 3 to 8 times. In the build phase, costs could be as much as 16 times higher, while during testing the costs were between 21 to 78 times greater. Correcting errors in the operations phase resulted in costs that were anywhere from 29 to 1,500 times higher compared to fixing the problem in the requirements phase.
Reduced risk of cost overruns and missed deadlines. By addressing any errors or questions in the requirements phase, the project is more likely to stay on-budget and on schedule during the design, prototyping, and testing phases.
Reduced reputational risk. A more efficient and accurate requirements process leads to faster and more productive development cycles. Missed deadlines and design errors can be catastrophic for both specific projects and the reputation of the engineering organization. Automated analysis makes it easier for firms to deliver excellent designs with fewer hiccups.
In short, automating the requirements analysis and review process reduces the man hours required to complete the process, accelerates the approval process, improves standards compliance, eliminates ambiguity, and can reduce the time and cost needed to correct errors – in some cases, by as much as 75%.
Case Study Examples
To further illuminate the benefits of a requirements analysis tool, it will be beneficial to examine two real-world use case scenariosI am text block. Click edit button to change this text. Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.
Defense Procurement Process
In this example, ambiguous and vague requirements were introducing unnecessary risk to the defense procurement process involving expensive assets.
Previously, the organization used a time-consuming, lineby-line review of every statement of requirement (SOR) document, which in some cases could run to hundreds of pages. This process was not only tedious, but also prone to errors and bogged down the requirements development cycle. Because this was a defense application, ambiguous requirements or incorrect documents also posed a security risk.
The organization decided to evaluate the QVscribe tool to automatically analyze the SOR documentation. Over the course of four months, the organization evaluated the tool for its impact on analysis speed, reporting clarity and ease of error correction. In the course of this evaluation, the end user was able to identify a number of poor formatting practices that were further complicating its SOR development.
With formatting adjustments, the organization was able to deploy QVscribe to help improve best practices in its requirement writing. Those included:
The addition of unique alphanumeric identifiers for each requirement
- Individual requirements were isolated in separate paragraphs
- Requirements were separate from explanatory context
- Unified rules were imposed across groups on the use of imperatives and other language
With automated analysis, the organization was able to cut review times by 50% to 75%. Staff are also crafting better requirements up front thanks to enforcement of best practices. The organization reduced procurement risk, reduced re-work, and accelerated the entire process significantly.
Technology Manufacturing
In this use case, a supplier of high-tech solutions wanted to standardize requirements authoring practices, reduce time spent correcting vague requirements, and minimize risk earlier in the bidding process.
The company had to derive detailed requirements for its developers and suppliers from lengthy, complex customer RFPs. Accuracy and clarity were critical, so any tools that could improve this process would provide an immediate value to the company.
The company struggled to standardize requirements writing practices across large, multidisciplinary teams. Because multiple engineers typically wrote requirements simultaneously, the company wanted to ensure consistent use of best practices and company standards.
The company also spent a substantial amount of time on review and approval of requirements, which added cost to each program. In addition, they wanted to identify and mitigate any potential program risks due to vague requirements.
The organization evaluated QVscribe software, and decided to move forward with the deployment because of the potential improvements, and the fact that the software would easily integrate with their existing tools and workflows. The solution also met their need for an ISO 9001-compliant requirements development process based on INCOSE-recommended practices.
The company deployed the QVscribe software and was able to reduce time and cost to correct requirements errors by 75%. The organization also streamlined requirement engineering workflows, unified application of best practices across teams, and improved quality assurance procedures.
Conclusion
Clear, accurate requirements documents serve as a critical part of the foundation for a successful product development process. Developing reliable requirements documentation, however, has only grown more challenging as standards, regulations, technology, and end-use products become more complex. Manually creating, reviewing and editing requirements documentation adds time and cost to the early stages of development, while also introducing multiple opportunities for expensive errors. Because these documents are largely written in natural language, applying automation to the process has traditionally been difficult, but that has changed with the development of advanced natural language processing tools. Automating the document review process using requirements analysis software based on industry standards and NLP allows companies to focus on creating accurate, high-quality requirements documentation. Interested in learning more about automated requirements analysis and QVscribe? Check out the resources below:
Automating the INCOSE Guide for Writing Requirements
Mastering the Requirements Review Process
