What is Industrial DevOps?

This post is an excerpt from Industrial DevOps: Build Better Systems Faster by Dr. Suzette Johnson and Robin Yeman.

Agile and DevOps have been implemented in software for over a decade. This is not a new phenomenon, but adoption in different environments beyond software is still evolving, as we have explored here and in the Introduction. The solution for wider adoption of Agile/DevOps in cyber-­physical systems requires a unique set of principles, which we have coined Industrial DevOps.

Industrial DevOps is the application of Lean, Agile, and DevOps principles to the planning, development, manufacturing, deployment, and serviceability of significant cyber-physical systems. The practice of Industrial DevOps pulls from multiple bodies of knowledge, including Agile, Lean, DevOps, and systems thinking, as well as from our own personal experience delivering cyber-physical systems in the new technological revolution.

Industrial DevOps bridges the principles and practices of Agile, Lean, and DevOps with the unique needs and challenges of cyber-physical systems through nine principles. By doing so, Industrial DevOps enables organizations building cyber-physical systems to be more responsive to changing priorities and market needs while also reducing lead times and costs. Through research and experience, we have found that the combined use of these nine principles is effective in successfully delivering cyber-physical systems across industries.

1. Organize for the Flow of Value: Organizing for flow provides guidance on how to align your multiple product teams for regular demonstration and delivery of value.
2. Apply Multiple Horizons of Planning: Apply multiple horizons of planning to address scaling and complexity while leveraging ongoing experimentation and learning.
3. Implement Data-Driven Decisions: Data-driven decisions use current observations and metrics to determine the state, manage the flow of work across systems of systems, and continuously improve with real-time data.
4. Architect for Change and Speed: Architecting for change and speed provides information on multiple architecture considerations, which can reduce dependencies and improve the speed of change.
5. Iterate, Manage Queues, Create Flow: Iterate, manage queues, and create flow to emphasize the importance of fast feedback, experimentation, and continuous learning.
6. Establish Cadence and Synchronization for Flow: Establishing cadence and synchronization discusses how these two concepts complement each other to reduce variability and improve predictability.
7. Integrate Early and Often: Integrating early and often covers different levels and types of integration points across large, complex systems.
8. Shift Left: Shifting left emphasizes a “test-first” mindset encompassing the multiple levels of testing across cyber-physical systems.
9. Apply a Growth Mindset: Applying a growth mindset expresses the need to continuously learn, innovate, and adapt to the changes around us in order to stay competitive.

Let’s take a look at Industrial DevOps in action through a brief glimpse into each of the nine principles. We will take a deeper look into each principle in Part II of this book.

1. Organize for the Flow of Value

The first step in adopting Industrial DevOps is to visualize and organize around the flow of value instead of around functions. This may sound obvious, but many companies are organized around functional activities, such as systems engineering, hardware engineering, software engineering, test engineering, etc. This type of organization creates multiple hand-offs and lots of documentation. Instead, teams should be organized around value streams, and the teams building the systems within the value stream include people with all the skills needed to improve the flow of value and shorten delivery cycle.

2. Apply Multiple Horizons of Planning

Predictive planning with phase gates has been the most popular approach to building cyber-physical systems. The belief has been that short-term empirical planning, which allows software systems to design and iterate at speed, won’t work for cyber-physical systems, with their longer lead times for hardware, dependencies across systems and systems of systems, regulatory controls, and more. 

Industrial DevOps employs multiple horizons of planning to address this unique challenge. This helps move organizations away from long predictive planning to the short-term planning common with Agile. This approach allows teams to obtain empirical data quickly from planning horizons and apply the knowledge to the next planning horizon, always adjusting the planning based on empirical data.

3. Implement Data-Driven Decisions

The third principle of Industrial DevOps focuses on using empirical data and leading indicators to better understand the progress and state of the product we are building. The data is then used as input into the decision-making process as the next cycle of work is planned and prioritized. Using data to drive decisions also provides the ability to measure the results of those decisions.

4. Architect for Change and Speed

Architecture is a critical element in the ability to deliver products and services at speed. Concurrent development is much faster than synchronous development. In Principle 3, we decomposed our systems into smaller components and threads that can be validated and verified, allowing us to learn faster. In Principle 4, we apply a modular architecture to address speed and change, as it enables small teams to build and deliver faster with reduced dependencies between other teams who may be working on the same system module. 

Through modularity, a team can change part of the design without impacting the other parts of the system. Architecting the system for serviceability means considering how the system components are updated or enhanced during the ongoing development of the system, whether before or after deployment. This approach makes change easier and increases the speed of delivery.

5. Iterate, Manage Queues, Create Flow

In Principle 1, we organized our teams for flow. Now, in Principle 5, we create and maintain that flow using iterative and incremental approaches to build out complex solutions. This principle couples Agile’s approach of iterative and incremental development with Lean’s commitment to reducing batch size to increase flow.

6. Establish Cadence and Synchronization for Flow

In Principle 6, cadence and synchronization come together to improve flow and establish predictability, which is critical when building cyber-physical systems. A lack of predictability is one of the leading detractors for organizations to adopt more Agile ways of working. 

Large cyber-physical systems typically have multiple teams designing, implementing, and deploying multiple interconnected subsystems and components over long periods of time. All of this results in unknowns and variability. 

In product development, our goal is to exploit good variability and remove bad variability. The trick is knowing which is good and which is bad. Cadence and synchronization are two tools that aid in removing bad variability while providing the opportunity to exploit good variability.

7. Iterate, Manage Queues, Create Flow

The more frequently we integrate, the faster we learn and the better our product. However, continuous integration may not be possible for every system. As we scale beyond software, we must consider constraints associated with physical products. For cyber-physical systems, our goal is to integrate as frequently as possible to evolve the system to meet customer needs and get feedback on what is working and where improvements can be made. Some considerations that impact integration are investment of automation, lead times in hardware, expensive test equipment, regulatory compliance rules, and training of employees on the tools and processes.

8. Shift Left

We must begin with a clear idea of how we are going to test so we can build quality into our products and services. This means thinking first about how we will test so that we have achieved the desired outcome before we start the development of products and services. The importance of early integration and iterative testing is not uncommon in the hardware domain. Models, prototypes, and simulations have been adopted for years. We now align these practices with being test-driven, developing iteratively, and organizing around the flow and delivery of value.

9. Apply a Growth Mindset

Finally, whenever we undertake dramatic change, we must ensure that we approach that change with a growth mindset. Without this final principle in place, none of the other eight matter. This is the principle that glues all the others together. We will discuss what a growth mindset is, why a growth mindset is important, and how to build a growth mindset both individually and as an organization. In addition, we describe the relationship to successfully driving toward Industrial DevOps principles by leveraging the power of a growth mindset.

The principles of Industrial DevOps have been built from the integration of existing principles. Just like all the innovators before us, we have taken some good ideas and applied them in new ways that we have found to work successfully for our unique needs. Our goal is to provide you with some insights to help you jump-start your approach to delivering products and services better. In an upcoming post, we will look at the key benefits and misconceptions of applying Industrial DevOps to the development and production of cyber-physical systems.

- About The Authors

Suzette Johnson

Dr. Suzette Johnson is an award-winning author who has spent most of her career in the aerospace defense industry working for Northrop Grumman Corporation. Suzette was the enterprise Lean/Agile transformation lead. In this role, she launched the Northrop Grumman Agile Community of Practice and the Lean/Agile Center of Excellence. She has supported over a hundred enterprise, government, and DoD transitions to and the maturation of Lean-Agile principles and engineering development practices. She has also trained and coached over four thousand individuals on Lean/Agile principles and practices and delivered more than one hundred presentations on Lean/Agile at conferences both nationally and abroad. Her current role is as Northrop Grumman Fellow and Technical Fellow Emeritus, where she continues to actively drive the adoption of Lean/Agile principles with leadership at the portfolio levels and within cyber-physical solutions, specifically within the space sector. As a mentor, coach, and leader, she launched the Women in Computing, Johns Hopkins University Chapter; the Women in Leadership Development program; the Northrop Grumman Lean-Agile Center of Excellence; and the NDIA ADAPT (Agile Delivery for Agencies, Programs, and Teams) working group. She received a Doctorate of Management at the University of Maryland with a dissertation focused on investigating the impact of leadership styles on software project outcomes in traditional and Agile engineering environments. She am also a Certified Agile Enterprise Coach and Scaled Agile Program Consultant/SPCT

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Robin Yeman

Robin Yeman is an award-winning author who has spent twenty-six years working at Lockheed Martin in various roles leading up to senior technical fellow building large systems including everything from submarines to satellites. She led the Agile community of practice supporting a workforce of 120,000 people. Her initial experience with Lean practices began in the late ’90s. In 2002, she had the opportunity to lead my first Agile program with multiple Scrum teams. After just a couple months of experience, she was hooked and never turned back. She both led and supported Agile transformations for intelligence, federal, and Department of Defense organizations over the next two decades, and each one was more exciting and challenging than the last. In 2012, She had the opportunity to extend our Agile practices into DevOps, which added extensive automation and tightened our feedback loops, providing even larger results. Currently, she is the Carnegie Mellon Space Domain Lead at the Software Engineering Institute at Carnegie Mellon. She is also currently pursuing a PhD in Systems Engineering at Colorado State University, where she is working on my contribution to demonstrate empirical data of the benefits of implementing Agile and DevOps for safety-critical cyber-physical systems.

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