Taking a look at DITA Metrics 101

DITA Metrics 101 - CoverMetrics. It’s a word that can strike fear into the heart of even the most hardened technical communicator. We sometimes need to prove the merits (in terms of dollars and cents, or whatever your local currency is) of adopting a new technique or technology. Especially if that technique or technology has an impact on the content of the entire organization.

On top of that, it can be difficult to know what metrics matter. Without a roadmap, it can be a lot more work than you need to put in. And you might not be able to impress upon the powers that control the purse strings how effective a new approach will be.

That’s all well and good, but to be honest I’ve never been much of one for metrics. Ask Aaron to tell you a story about that from our days at The Company That Shall Not Be Named. But my tune changed a few years ago. I met Mark Lewis (content strategist and DITA educator at Quark) at a conference around that time. Mark and I kept in touch over intervening years, and during that period he shared with me the first of a few whitepapers that he wrote about DITA metrics.

A few whitepapers later, and Lewis has come out with the book DITA Metrics 101. The book demonstrates that gathering and presenting metrics about the adoption of DITA (or topic-based authoring) doesn’t have to be a scary or difficult proposition. DITA Metrics 101 (as the title suggests) is a solid introduction to the subject, and it provides a practical roadmap for gathering the metrics that you need to justify the adoption of DITA in your enterprise.

Let’s take a closer look at it.

No frills, and that’s not a bad thing

The book follows the pattern of what I consider to be good documentation: it outlines what you need to know and shows you how to do the job, with just enough adornment to make things clearer.

DITA Metrics 101 is no nonsense and no frills. It immediately gets down to the task of introducing you to gathering, analyzing, and presenting metrics to support the use of DITA in your organization. Of course, there are a number of examples in the book (which I’ll go into soon).

The book is more like an intensive course in metrics than an introductory tome. And its practical, not merely theoretical.

Examples, examples

Each chapter of DITA Metrics 101 focuses on gathering metrics for:

  • Topics
  • Projects
  • Translation
  • Content filtering
  • Structured authoring
  • Production

And, as I mentioned a few paragraphs ago, the information is practical. Each chapter has several sample spreadsheets that detail how to present and calculate cost metrics. But you’re not simply given a spreadsheet and expected to figure out how to use it on your own.

For example, let’s dig briefly into the chapter titled “Translation Metrics 101″. In the example for determining translation hours, Lewis breaks down the calculations for the number of hours translation of various content types takes, then uses that to calculate the total cost of translating those topic types.

But it’s not just a bunch of numbers on a page. Lewis gives detailed explanations of the inputs for the spreadsheets and how the calculations work. That’s where the book’s main strength lies, in my opinion. Once you’ve absorbed the lessons of the book, you should be able to use those lessons to come up with models of your own.

More than just metrics

DITA Metrics 101 isn’t dry treatise that focuses on gathering metrics. Even if that was the sole focus on the book, the content is anything but dry. However, there’s more to it than that. Most chapters offer a solid introduction to developing strategies around the topic of the chapter. For example, the chapter on content reuse looks at building a strategy for reusing content and from there how to use what Lewis calls warehouse topics, which are a:

type of topic that is created when the content for all products is similar at the topic level. Within the topic, some components (steps, paragraphs, etc.) are identical for all products, and some are unique.

While I was familiar with content reuse, and have some familiarity with content warehousing, I learned a lot about building a strategy for reuse from that chapter. And I learned as much, if not more, from the other chapters of the book.

Anything else?

The last two chapters of the book are quite useful. One is an eleven-page summary of the book, which can offer you a quick when you need it.

The last chapter is a detailed glossary of terms related to DITA, XML, and structured authoring. If you’re not familiar with some of the terms that you encounter in DITA Metrics 101, you won’t find a better or more concise explanation.

Final thoughts

DITA Metrics 101 packs a lot of information into it’s 150 pages. Mark Lewis has crafted a book that’s definitely a worthwhile read if you’re planning a move to DITA and need to prove higher ups how DITA will save the organization money.

But the information in DITA Metrics 101 isn’t just limited to DITA. With a little tweaking, you can apply what you learn to a move to topic-based writing with tools like Madcap Flare or Author-IT.

If your organization is planning a move to DITA, and you need to gather information on potential cost savings, then you should read and absorb DITA Metrics 101 before you begin. On the other hand, if you’re familiar with DITA and with gathering metrics, this book is still a worthwhile read. You’ll undoubtedly learn something new, which you can apply to your work.

This work is licensed under a Creative Commons Attribution 4.0 International License.

  • Mark Lewis

    Scott, that’s a great point about how this model could be customized
    to predict the cost of content in Madcap Flare or Author-IT. After I wrote the
    first few whitepapers about DITA Metrics, some people said this model did not
    have to be DITA specific and could be designed for any XML schema or
    proprietary content model that supports reuse. Very true. And it also made me
    realize that this is not just for the software industry and techpubs. Anybody
    that authors content in chunks that is structured or predictable could design a
    metrics model for it. Education, Financial, Manufacturing, whatever.

  • http://www.thecontentwrangler.com/ Scott Abel

    Great review, Scott. Thanks for taking the time to share your thoughts.

    • Scott Nesbitt

      It was the least I could do, seeing as how Mark graciously sent the book to the bottom of the world :-)

      Seriously, though, it was a good learning opportunity. Especially in an area in which I have little or no knowledge.