Increased complexity, increased opportunity

Streamline and simplify engineering requirements

Introduction: AI is changing requirements management

Developing intelligent products requires a more intelligent approach

2 min read

01

The current landscape: You are here

You are in an expanding space, in a time of unfettered change

3 min read

02

AI is altering engineering practices

Engineers who need to transform digitally will require new methods and approaches

2 min read

03

The future of requirements management

Comprehensive tools that help eliminate risk and errors

4 min read

04

IBM solutions for managing engineering complexity

IBM Engineering Lifecycle Management solutions are designed for today’s engineering complexity

5 min read

05

Conclusion: The future is yours

Take the next step toward flawless requirements management

2 min read

06

Next steps

Watch the video

Watch the video

Requirements Quality Assistant Brings Watson® AI to Requirements Management

Leverage AI from Watson

Leverage AI from Watson to optimize requirements management, reduce rework and avoid delays

Reduce costs and time to market while improving quality and client satisfaction

IBM Engineering Requirements Management

IBM Engineering Requirements Management

A requirements management solution that helps you capture, trace, analyze and manage systems and software development

Watch the webcast

Watch the webcast

Learn from IBM's team of engineering requirements experts about how Watson AI is injecting intelligence into the requirements writing process

Increased complexity, increased opportunity

01

Introduction: Product complexity is changing requirements management

2 min read

Ordinary products are becoming more complex every day. As products become more connected by the Internet of Things (IoT) their available features and functions correspondingly grow, driven by their reliance on software.

A wrist watch used to be a purely mechanical device, powered by gears, springs and levers. As microprocessors became small and inexpensive, consumers could buy wrist watches that were also calendars, schedulers and alarms – all functions still related to time. But as wrist watches become connected, entirely new markets have emerged: GPS devices, health-monitoring devices, and even cell phones.

This growing product complexity has introduced challenges in how engineering teams manage the development process. Product connectivity added one level of complexity, but that same connectivity has mushroomed the functions and features these products can offer. This connectivity enablement increases the width and breath of product requirements, the interaction between these requirements, and the number and scope of tests that must be executed to deliver the product quality that customers demand.

Each successive generation of products offers more features and functions, exponentially increasing their requirements, design, and testing effort. Therefore, engineering teams need to adopt tools that can help improve efficiency, seamlessly manage relationships between development processes, and scale as product complexity increases.

By 2025, it is predicted that there will be 75-billion internet-connected things, and that they will outnumber humans by nearly 9-11.

More software is required for more products2

Large Hadron Collider

Large Hadron Collider

3,500,000

lines of code

Mars Curiosity Rover

Mars Curiosity Rover

5,000,000

lines of code

Cell phone

Cell phone

12,000,000

lines of code

F-35 fighter jet

F-35 fighter jet

24,000,000

lines of code

Modern car

Modern car

100,000,000

lines of code

Fortunately, we can find the solution to this growing development challenge by examining business processes that have been optimized within many organizations. Several of these organizations have adopted a digital transformation initiative that leverages analytics and AI to help manage important but tedious processes. It also enables them to explore and discover unseen patterns.

We propose leveraging the same AI technology that is finding its way into products to assist with the growing complexity of development.

This document explores how AI is affecting product design. We’ll present the challenges that lie ahead, and then advise you on how a more intelligent approach can ensure the development and deployment of high-quality software and products.

02 The current landscape: You are here

Increased complexity, increased opportunity

02

The current landscape: You are here

3 min read

You are here

You’re in a place you’ve never been before. No one else has ever been here, either. Because we’re at a tipping point that will change the way we work and live. We’re entering the Era of Engineered Intelligence.

We’re already seeing autonomous vehicles and manufacturing facilities powered by smart buildings and robotic assembly. Engineering teams are handing over the mundane, repetitive tasks to be performed by highly sophisticated machines, using the power of AI. Today’s connected products are required to perform in unprecedented ways, and AI is being used to help manage the volumes of data required to run these products. So companies can innovate faster. The future of engineering looks very different than it did just a few years ago. Does this future sound exciting to you? It should. Because you’re the one who’s expected to create it.

Complexity is inversely related to time

In recent years, the engineering of complex systems has become increasingly complicated, across nearly every industry. The fusion of the IoT, 5G networks and increased consumer expectations has created unrelenting demand for smart, connected products. These new products generate data that must be collected, stored, analyzed and acted upon. Whether it’s a fighter jet or a washing machine, meeting the expectation of flawless performance is the responsibility of everyone involved in the development process.

Organizations everywhere are feeling unprecedented pressure to deliver high quality products. More quickly. More economically. Without compromising quality. Ever.

Quality is everything; time and budget are everything else

When you’re developing products that require millions upon millions of lines of code, engineering lifecycle management becomes critical. Systems engineers know that. And they’re quickly learning that this digital revolution won’t be successful unless they’re successful at integrating their processes, from requirements to modeling and testing. This is a critical step in digital transformation, which allows global teams of teams to collaborate and have shared access to a single source of truth.

Traditional methods that use documents, emails, spreadsheets and white boards to capture requirements and manage changes simply aren’t going to cut it. What’s needed is a streamlined, collaborative process that diminishes cycle times and reduces error.

There are more demands on the engineering and development teams, and old tools and engineering processes aren’t sufficient. Teams need to improve their performance to cope with and indeed win competitive advantage in their industries.

Integrated, end-to-end engineering lifecycle management solutions make it possible for engineering teams to focus on their engineering – not on managing their tools or depending on over-burdened internal IT groups.

Let’s look at the numbers

39%

of organizations cite poor requirements management for project failure3

53.1 million recalls

Vehicles recalled in 2016, up 26% over 2015, largely due to failures in supplier parts4

200X

Defects in a launched project cost up to 200x more to correct than defects found during requirements5

80%

of rework and 50% of project defects can be traced to requirement errors6

37%

of project failures have inaccurate requirements gathering as their primary cause7

NASA performed a study on the relative cost of fixing engineering errors during the various phases of a project development cycle. They discovered that an error that is carried through to development and production becomes exponentially more expensive to correct than one found at the requirements stage. Recalls for products are especially costly to manufacturers. This still holds true today, even more so, given the advanced technology and connectivity of today’s products.

03 AI is altering engineering practices

Increased complexity, increased opportunity

03

AI is altering engineering practices

2 min read

Features and behaviors in today’s products are forcing engineering teams to fundamentally change the way they approach product design and development. Companies cannot afford to hire, nor can they find, qualified engineers at the rate products are growing in complexity. Using artificial intelligence (AI) can help bridge the gap and enable existing engineers to do more. AI is being introduced into engineering processes to aid in the analysis of data, and perhaps more importantly, to identify which data adds value. By injecting intelligence early into the process, teams can improve decision making with increased confidence. The industry disrupters already know that AI in engineering will soon become standard.

Before we delve into how AI can help, it may help to define what we mean by AI. Artificial intelligence is not a replacement for engineers. It’s technology being intelligently used to augment their capabilities. There are two defining characteristics that make AI-based algorithms fundamentally different from traditionally programmed algorithms:

  1. Learning: The system learns to recognize patterns from data and can be refined based on what it discovers. We use AI to help us know more than we do.
  2. Self-direction: We use AI to automate tasks that allow us to focus on the more complex engineering tasks.

Artificial intelligence is the challenge and the solution

While to some it may seem that AI complicates the design and development of software and products, it is also a solution to its own complexity. When AI is added to requirements management, it helps the requirements process in a way that improves quality, decreases cycle time, and reduces risk.

The evolution of requirements management leads to knowledge driven requirements

The ever-increasing complexity of products increases the need for rigor and quality in the engineering process. Certainly, engineering and tool techniques for strategic re-use have helped organizations keep up with this complexity explosion, but it is not enough. We need AI techniques to help manage the exponential growth of complexity and volume.

04 The future of requirements management

Increased complexity, increased opportunity

04

The future of requirements management

4 min read

Requirements management is critical to the success of any project. Poor requirements definition at the beginning of an initiative can result in delays, cost overruns and poor product quality. The introduction of AI is bringing the power of intelligence to the development of today’s complex products. Better requirements help those in regulated industries achieve higher standards of compliance more easily, with more traceability and visibility into requirements tied to test cases and designs.

Organizations are re-thinking traditional methods of requirements management. They’re seeking new processes and tools to help them develop faster, better products, rather than the old solutions that don’t meet today’s needs:

Live collaboration

Collaboration

Collaboration on a single source of truth is impossible with systems that rely on documents, emails, spreadsheets and other materials that must be collated and distributed to distributed teams.

Consistency

Consistency

To be fully useful, data needs to be consistent across tools as changes are applied to a system.

Traceability

Traceability

When you cannot trace a change in a requirement tied to a test case, you’re exposed to safety-critical errors.

Insights into change

Insights into change

Using traditional requirements management methods, you cannot easily understand the relationships between pieces of information. Tracking changes via spreadsheets and office documents limits visibility by the teams of teams collaborating in today’s engineering environments.

Requirements re-use

Requirements re-use

Products are becoming too complex to build in a one-off manner. Companies are building products as models with variations suited to different markets as a way to create higher levels of re-use.

Compliance

Compliance

New regulations and standards are being introduced every day to improve safety, accountability and process control. Regulated industries have particularly stringent standards for global configuration management.

Peer reviews

Peer reviews

It is extremely difficult to manage the tedious, manual review process, and to coordinate and consolidate annotations across several teams in different locations.

Making data work for version and variant analysis

Making data work for version and variant analysis

Store information in a central location and present it in document format.

The next generation of requirements management begins with an ecosystem of qualified, collaborative participants

Successful requirements management in today’s complex environment demands the ability to capture relationships and manage dependencies. The most successful initiatives engage more people during the initial stages so that requirements are complete, accurate and better defined. Therefore, systems engineers need to expand their requirements ecosystem to include:

Users: Who better than the user to know how a product should work and what the customer experience should be? This essential constituency is often overlooked by requirements managers.

Business managers: These are the people who understand the business goals and how product performance will impact them. They know their markets and their preferences. Break down the siloes and urge your business managers to participate right from the outset.

Retiring staff: The gray-washing of industries is becoming a problem as senior employees retire and take valuable information and experiences with them. They should be included in the requirements process so the next generation of requirements authors can benefit from their expertise. This is a unique value of AI, allowing senior engineers to translate their expertise for the next generation.

Today, systems engineers need a comprehensive requirements management solution that enables continuous collaboration

In a recent study, 89% of CIOs indicated they want software released faster8

Most Chief Information Officers expect projects to be completed quickly, on budget and without problems. To satisfy that expectation, and to create complete, accurate requirements, systems engineers need a sophisticated requirements management program that provides advanced features and functions:

Live collaboration

Live collaboration

Keep stakeholders informed and engaged in real time is critical.

Consistency

Consistency

Keep data organized logically and consistently. The more consistent requirements are, the fewer opportunities there are for errors.

Traceability

Traceability

Capture all annotations, maintain them and make them easily accessible.

Insights into change

Insights into change

For every change, you must:

  • Understand the impact of the change before it is made.
  • Ensure that all impacted areas are changed as necessary.
  • Collaborate in real time to handle the crucial tasks of versioning and change management.

Requirements re-use

Requirements re-use

Save time and effort by repeatedly re-using requirements rather than creating one-offs.

Compliance

Compliance

Incorporate regulations and standards into requirements. Requirements that adhere to INCOSE guidelines save time and help prevent violations.

Rules engines

Rules engines

Unambiguous rules engines prevent misdirection.

Peer reviews

Peer reviews

All annotations and approvals are recorded.

Complicated checklists

Complicated checklists

Built-in checklists and processes prevent lost or incomplete steps.

Making data work for version and variant analysis

Making data work for version and variant analysis

Store information in a central location and present it in document format.

Requirements Quality Assistant (RQA)

Requirements Quality Assistant (RQA)

Employ a sophisticated requirements management tool with AI, such as RQA to ensure utmost quality and value.

Systems engineers are demanding new engineering lifecycle management solutions to deliver innovative products in a timely manner while ensuring industry compliance

Cloud-based systems engineering tools can have a positive impact on an organization’s technology, process and culture:

  • Expanded product development and services ecosystems
  • Real-time collaboration across global user networks
  • A holistic approach to using data and tapping all internal expertise

Innovative products

Innovative products

Companies can pursue a competitive advantage by becoming increasingly software-centric.

Timely manner

Timely manner

Meeting increased time-to-market demands creates market differentiation.

Industry compliance

Industry compliance

Meet safety-critical regulations with confidence, at both a project and business level.

A solid, high-performance requirements management solution can help:

  • Reduce failures
  • Reduce risk
  • Improve predictability
  • Increase speed
  • Improve decision making
  • Satisfy customers

05 IBM Engineering Lifecycle Management solutions for managing complexity

Increased complexity, increased opportunity

05

IBM Engineering Lifecycle Management

5 min read

At IBM, we understand the challenges faced by software and systems engineers, because we are engineers ourselves. And we’re committed to improving the engineering lifecycle with enhanced product development tools and services.

We know that an exceptional requirements management program will help organizations do much more than reduce failures. So we examined the current and future needs of engineers, identified the deficiencies of existing requirements management systems, and created solutions that help ensure a wholly better outcome. With our methods, innovative, digitally-driven products can be designed, developed and quickly taken to market to meet increased consumer demand and pre-empt the competition.

Requirements management will also help:

  • Reduce risk
  • Improve predictability
  • Satisfy customers
  • Improve decision-making

IBM Engineering Requirements Management solutions allow engineers to do what cannot be achieved through traditional methods, which rely upon documents, emails and spreadsheets. Our solution emphasizes collaboration, accessibility, accuracy and consistency. Several people can easily collaborate on the same data at the same time regardless of where they’re located. The entire team has access to the latest, most accurate information, in the format best suited to their needs. There is always a single, reliable point of truth.

Requirements Quality Assistant, the latest IBM AI offering for requirements management, embeds Watson® into the heart of its requirements management tool. Watson AI enables users to improve the quality of requirements based on the INCOSE guidelines for writing good requirements.

RQA

 

Our requirements management tools help you build the bedrock of your project, integrating everything in one seamless, end-to-end toolkit. It’s our commitment to better engineering. We will continue to make enhancements, and to offer new features and functions, so systems engineers will always have the tools they need to forge the complex new future that is impacting lives today.

IBM Engineering Requirements Management addresses the challenges engineers face in developing software for connected products:

Collaboration

Users are automatically kept in the loop with email notifications and customizable dashboards. These dashboards provide at-a-glance details regarding team members, project timelines, changes that have been made, and any ongoing reviews and comments. The IBM requirements management solution is a single source of truth that ties requirements to every stage of the development cycle.

Consistency

Information is stored in a central location where users can add attributes to individual statements without changing the original structure, and filter and sort information based on the supporting characteristics. When a document is ready for review, stakeholders can make comments directly in the tool. This allows important decisions and discussions to occur easily and be shared across the team.

Traceability

IBM Engineering Requirements Management allows users to link as they think. These relationships can be displayed, along with requirements and annotations, increasing the visibility of the project status. Views can be saved, enabling the team to quickly change the perspective of the data to fit stakeholder needs. Additionally, dynamic traceability means that as soon as a change is made, the requirements management tool automatically creates an update. If a downstream requirement changes, it is automatically reflected for the upstream requirements and test cases. Users can easily see the impact of changes via live dashboard. This helps teams see a reduction in errors, improved quality outcomes, and better project management.

Understanding change

IBM requirements management tools help your whole team assess the impact of change before it happens, creating a strategy for change, and then alert users to review a change and act on it accordingly. With a minimum level of effort, changes propagate down all levels of linked data in the project.

Requirements re-use

IBM engineering solutions support requirements re-use by allowing the same requirement to be used across multiple projects. To help reduce the chance of errors during re-use, IBM offers a sophisticated configuration management mechanism that allows you to create versions and variants of products, systems, and subsystems while maintaining relationships between the original and its versions and variants. This adds efficiency to the process, helping you deliver faster.

Compliance

When you’re developing on a cloud-based platform that integrates stages of a project for complete traceability, achieving compliance becomes less complex. All activity and changes in requirements can be viewed at any time, showing linkages throughout a project. The documentation is built-in to help teams conduct reviews and audits more easily.

Making your data work for you

Whether a stakeholder is interested in compliance, gap analysis, cost, test outcomes, or other information, IBM engineering tools can automatically create customized views to meet their individual needs. These views are dynamic and current, changing as the project changes, and can be viewed from the dashboard or printed. IBM makes your data work for you, so you can spend time being an engineer.

Toward a more knowledgeable ecosystem

In addition to improving workflow, integrating IBM Engineering Lifecycle Management has a beneficial effect on people. It builds confidence in the teams doing the work, showing them the value of their efforts in real time. By bringing Watson AI into the mix, senior engineers can dedicate some of their time to training Watson with best practices from their tenure experience. Not only does this facilitate the creation of a shared and retained knowledge base, it helps mitigate the risk of losing valuable existing knowledge as a result of a retiring workforce.

IBM Requirements Quality Assistant (RQA)

IBM delivers the next generation of requirements management through the power of IBM Watson artificial intelligence.

In a single-tool environment that extends IBM Engineering Requirements Management DOORS® Next, Watson AI helps mitigate risk and ambiguity early in the authoring phase using rapidly integrated AI functionality.

The Watson AI capability of IBM Requirements Quality Assistant includes several features that improve the process by helping improve requirements quality and accelerating the requirements review process:

1. Data management: IBM RQA provides a knowledge-driven requirements process that sorts through data to extract key insights, accelerating data management and improving requirements quality.

2. Writing guidelines: IBM RQA is designed to be consistent with industry best practices, and is pre-trained to detect a number of quality issues based on the INCOSE Guidelines for Writing Good Requirements.

3. Machine learning: The more your teams use IBM RQA the smarter it becomes. Users can provide direct feedback to teach Watson and continually improve the model over time.

4. Natural Language Processing (NLP): IBM RQA removes risk and ambiguity in the requirements authoring phase out-of-the-box. It finds and pinpoints problems and provides expert guidance for correcting them.

IBM Requirements Management solutions enable you to maintain complete control of your projects from beginning to end. IBM clients have used our knowledge driven requirements management tools to:

1. Achieve significant reduction in defect costs

2. Reduce review time and costs

3. Share engineering expertise

Following the deployment of the IBM Requirements Management solution with RQA, some IBM clients have reported:

Up to

Mars Curiosity Rover

reduction in the cost of defects

Up to

Mars Curiosity Rover

reduction in the cost of manual reviews

Up to

Mars Curiosity Rover

reduction in development costs

Up to

Mars Curiosity Rover

Acceleration in time to market

06 Conclusion: The future is yours

Increased complexity, increased opportunity

06

Conclusion: The future is yours

2 min read

We’re in the midst of a convergence of ingenuity and expectation. Throughout the world, consumers have set us on a trajectory toward the domination of innovative, digitally connected products. But there’s a caveat: these products must meet the performance expectations of a highly demanding marketplace.

Engineers are under greater and greater pressure to develop more complex designs, and to get them to market more quickly. And they must do so with economic efficiency. The market demands it. And thus these companies are forced to embrace a digital transformation. Seventy-one percent of organizations cite consumer experience as a competitive differentiator9, and we can safely assume that 100 percent of organizations want a competitive advantage.

IBM can help you improve your engineering lifecycle management processes. Our solutions are integrated, intuitive and powerful. They give you total control. And the addition of Watson AI through our Requirements Quality Assistant offering gives you increased confidence to move swiftly into the next chapter of engineering innovation.

Surprisingly, moving from your traditional methods of documents and spreadsheets will be easier than you think. And IBM is here to help get you there.

To learn more about IBM Engineering solutions, contact your IBM representative or IBM Business Partner.
Or visit us at: https://www.ibm.com/products/systems-engineering

Next steps

Accelerates

Watch the video

Requirements Quality Assistant Brings Watson® AI to Requirements Management

Leverage AI from Watson

Leverage AI from Watson to optimize requirements management, reduce rework and avoid delays

Reduce costs and time to market while improving quality and client satisfaction

IBM Engineering Requirements Management

IBM Engineering Requirements Management

A requirements management solution that helps you capture, trace, analyze and manage systems and software development

Watch the webcast

Watch the webcast

Learn from IBM's team of engineering requirements experts about how Watson AI is injecting intelligence into the requirements writing process