Writing Technical Documents

I'm in the process of writing an Implementation Guide for deploying Digital Engineering solutions in a variety of High Technology Systems of Systems Domains.

Digital Engineering (DE) is an integrated digital approach that uses authoritative sources of systems data and models as a continuum across disciplines. It supports lifecycle activities from concept through disposal, enabling the Design, Development, Testing, Deployment, and Sustainment of Complex Systems (SoS).

The DE Ecosystem is an interconnected infrastructure, environment, and methodology enabling the exchange of digital artifacts from an Authoritative Source of Truth (ASoT).

Model-Based Systems Engineering (MBSE) is a subset of DE as the formalized application of modeling to support System Requirements, Design, Analysis, Verification, and Validation activities, starting with the conceptual design phase and continuing throughout development and later life cycle phases.

Modeling, simulation, and visualization enable complex systems to understand, anticipate, and verify solutions and their costs before building them. Understanding their emergent behavior due to increasingly complex software, extreme physical environments, net-centricity, and human interactions becomes essential for successful systems development as systems become more complex.

• Department of Defense Digital Engineering Strategy
• Capability Acquisition and Sustainment Group (CASG) Digital Engineering Strategy
• Canadian Digital Engineering Strategy

Let's Start with Some Background

Deploying a Digital Engineering strategy represents a fundamental transformation in how organizations approach complex system development and lifecycle management. At its core, digital engineering aims to create a seamless, model-based environment where all aspects of engineering, from initial concept to final deployment and maintenance, exist in an integrated digital ecosystem. This transformation is becoming increasingly critical as systems grow more complex and interconnected, making traditional document-based approaches insufficient for managing modern engineering challenges.

The primary motivation for implementing a digital engineering strategy is improving decision-making quality and speed while reducing costly errors and rework. Traditional engineering processes often suffer from information silos, where critical data becomes trapped in disconnected documents and systems. Organizations can maintain a single source of truth by creating a digital thread that connects all aspects of the engineering lifecycle, enabling real-time collaboration and more informed decision-making. For example, when engineers make design changes, the impacts of those changes become immediately visible across all related systems and stakeholders, allowing for faster iteration and more thorough impact analysis.

Implementing a digital engineering strategy requires careful planning and a phased approach to ensure successful adoption. Organizations should begin by assessing their current engineering maturity and identifying specific pain points that digital engineering can address. This assessment should consider existing tools, processes, and workforce capabilities to create a realistic transformation roadmap. The next step involves selecting appropriate tools and platforms to support model-based systems engineering (MBSE) practices while ensuring interoperability with existing systems. It's crucial to remember that digital engineering is not just about technology – it requires significant cultural change and new ways of thinking about engineering processes.

Training and workforce development play a crucial role in successful digital engineering deployment. Organizations must invest in developing their employees' skills in model-based approaches, new tools, and collaborative workflows. This training should be tailored to different organizational roles, from systems engineers who need deep expertise in modeling tools to stakeholders who need to understand how to interpret and use model-based information. Creating communities of practice can help facilitate knowledge sharing and accelerate the adoption of new methods. Additionally, organizations should identify and empower digital engineering champions who can help drive change and support their colleagues through the transformation.

Measuring the success of a digital engineering strategy requires establishing clear metrics and feedback mechanisms. Organizations should track technical metrics (such as model quality, reuse rates, and error reduction) and business metrics (including cycle time reduction, cost savings, and customer satisfaction). These measurements help justify the investment in digital engineering and identify areas for improvement. Celebrating early wins and demonstrating value is essential to maintain momentum and support for the transformation. For instance, organizations might start by digitizing a single product line or project to explain the benefits before expanding to broader implementation.

As organizations mature in their digital engineering capabilities, they can begin exploring more advanced applications such as digital twins, artificial intelligence-assisted design, and automated verification and validation. These capabilities build upon the foundation of model-based approaches to create even more powerful engineering environments. However, organizations should avoid trying to implement everything at once. Success in digital engineering comes from steady, deliberate progress that allows time for learning and adaptation. The goal is to create a sustainable transformation that improves engineering work, leading to better products, reduced costs, and increased innovation capacity. This long-term view helps ensure that digital engineering becomes deeply embedded in the organization's DNA rather than being seen as just another initiative.

The Current Edition of the Strategy

The current edition has 8 Chapters.

1. Introduction to the Digital Engineering Strategy
2. Applying Capabilities-Based Planning to System Acquisition
3. Formalizing Development and Integration with Model-Based Systems Engineering
4. Authoritative Source of and Digital Engineering Strategy
5. Applying Technical Innovations to Improve Digital Engineering Practices
6. Establishing a Support Infrastructure and Environment
7. Transformation of Digital Engineering Culture and Workforce
8. Managing the Deployment of the Digital Engineering Strategy

A Glossary and a References section with an ever-growing number - now 781 - set of journal, government and technical reports

The Challange of Technical Writing

I've been writing technical documents since undergrad and grad school. There are many tools for aiding the writing activities:

• Grammarly is the starting point. It suggests fixes to your current text. Invest in the Premium version; it will make you sound?really good.
• Use AIs to construct frameworks for your content. Gemini, Claude, and ChatGDP can all build frameworks of content. In our domain, the text must be in the future perfect tense;?for example, writing?the system can provide the following, but it?is replaced with?our system, which WILL give the following. No doubt, when you buy our system, it will do the job for you.
• Have references to support your advice. Read the references in the references. Treat the writing like a research project.