Charles Betz is pleased to announce to readers of his TDAN.com column his forthcoming book, Digital Delivery: Concepts and Practices. The data management community was a big supporter of his previous work with the two editions of Architecture and Patterns for IT, and he thinks you’ll like this new material.
So, what exactly IS this book, anyhow?
* It is the first general, survey-level text on IT management with a specific Agile, Lean IT, and DevOps orientation.
* It has a unique and innovative learning progression based on the concept of organizational evolution and scaling.
* Because it is written with continuous integration and print-on-demand techniques, it can be continually updated to reflect current industry trends.
The book is intended for both the academic and industry training communities. There has been too much of a gap between academic theory and the day-to-day practices of managing digital products. Industry guidance has over the years become fragmented into many overlapping and sometimes conflicting bodies of knowledge, frameworks, and so forth. The emergence of Agile and DevOps as dominant delivery forms have thrown this already fractured ecosystem of industry guidance into chaos. This book provides guidance for both new entrants into the digital workforce, as well as experienced practitioners seeking to update their understanding on how all the various themes and components of IT management fit together in the new world.
The book covers:
- Digital and IT value
- IT infrastructure, including Cloud
- Modern application development, including Agile development and DevOps
- Digital product management
- Lean IT
- Operations management, including modern web-scale practices
- Coordination and process management
- Investment, finance, sourcing, and project management
- Organization and culture
- Governance of digital and IT organizations
- Information and data management
- Architecture and portfolio management
Using a unique scaling approach, “from startup to enterprise,” the book treats the user’s understanding itself as an evolving system, introducing concepts as they become necessary to an organization’s growth. Agile and Lean perspectives are woven throughout, with in-depth discussion of their impact on traditional IT management approaches.
Digital investments are critical for modern organizations and the economy as a whole. Delivering them (defined as both creating and managing for value) can provide prosperity for both individuals and communities. Now is an ideal time to re-assess and synthesize the bodies of knowledge and develop an industry consensus on how digital and IT professionals can and should approach their responsibilities. Extensively researched with over 270 citations and 250 figures, and including discussion questions and research topics, this book is intended for both classroom and professional use. Developed using the same continuous integration principles it describes, the book is an adaptive, evolving product that will grow with the digital profession.
In this column, I want to talk a little more about the “emergence model” that distinguishes the book. Data and information professionals in my experience are more sympathetic to conceptual and philosophical concerns. The problem I set out to solve when I was first conceiving the book was the question of overall learning progression, or narrative.
I teach a required semester-long survey class on IT management at the University of St. Thomas-Minnesota, in the largest software engineering program in the country. I had been trying to teach college students by walking them through architectural perspectives on the problem of IT management: the business, data, applications, and technical views many of us use regularly. Without going into detail, it wasn’t working well, and I started thinking about the problem. I noticed that there were two primary narratives being used to teach in computing:
- The “stack”
- The “lifecycle”
The “stack” is how the most rigorous topics are taught. Algebra is the foundation for trigonometry, is the foundation for calculus, for example. Logic is needed for discrete math, required for automata and compilers, and so forth. The stack is also how technology is described: physical, logical, and conceptual layers, for example. Architecture concepts are essentially a stack.
The “lifecycle,” on the other hand, is how we tend to structure guidance. We plan and design, we build, we run. COBIT, ITIL, even DMBOK show lifecycle influences, as do software engineering programs in colleges.
However, both the stack and the lifecycle have limitations. The stack can fall into what venture capitalist Anshu Sharma calls the “stack fallacy,” the “mistaken belief that it is trivial to build the layer above yours.” It’s also hard to know sometimes when you have covered the underlying foundation sufficiently, and the earlier, more theoretical topics can seem irrelevant to the student. (“In the beginning, the universe was created.”) The lifecycle narrative is far too prone to promoting waterfall thinking, anathema to the current Agile and Lean Product Development approaches redefining the IT industry.
Instead, the book’s emergence narrative draws on systems theory, in particular John Gall’s idea that “A complex system that works is invariably found to have evolved from a simple system that worked. A complex system designed from scratch never works and cannot be patched up to make it work. You have to start over, beginning with a working simple system.” What if we treated students’ understanding as such a system? What would be the simplest possible thing that could work? How would we iteratively evolve their understanding, based on practical topics? Scaling seemed to be orthogonal to the other narratives:
Reading books on organizational scaling inspired the idea that growth does not happen smoothly; instead, organizations tend to cluster at certain scales and struggle to grow to the next scale. Verne Harnish, in his book Scaling Up, shows it similarly to this:
Hence the overall structure of the book:
- Team of Teams
A key focus of the book is explaining what practices are formalized at which level of growth. (For example, startups don’t usually institute a formal Data Management practice with specialized staff and processes. But enterprises often need to.) I think this structure is working well for my students, and I hope that you will be interested in the book when it becomes available in the next few weeks.