STC13: Alyson Riley about effective IA

In her session “Building Effective IA Teams in Resource-Challenged Times”, Alyson Riley from IBM offered her take on the recent theme that tech comm needs to “speak business” to prove its worth. (This is part of my coverage of the STC Summit 2013 in Atlanta.)

Alyson argued that “nice to have” initiatives are no longer compelling enough to get tech comm a budget or a mandate. To play a mission-critical role in a corporation, tech comm must plug into the corporate strategy. However, that strategy and its stakeholders usually isn’t waiting for us to put in our two cents. So we tech comm’ers must:

  1. Focus on corporate strategy as opposed to tactics.
  2. Play to the motivations behind the strategy, so we can come up with ways to support it with our unique skills and contributions.

The following moves can help with that second step:

  • Address the “buyer evaluates” and “buy” stages of the product. Usually, we speak to the “customer uses” stage of our product where there’s often more cost than income. The challenge is to make it compelling for buyers and sales to also use our content to their benefit in the more profitable stages. A good start is to ask sales: “What is the hardest part of your job?” and see if we can help them with the information we provide.
  • Influence social content to help leads along the marketing funnel from awareness to loyalty and advocacy. That doesn’t mean to “sell out” completely to marketing. It’s often as easy and sensible as including customer benefits in our content. Simply add the “why” to the “how” and give clients a chance to understand and promote your product.

Both moves boil down to the same principle: Don’t educate stakeholders in sales, marketing, product management, etc. about the product. Instead, imagine what the success of these respective stakeholders looks like and address that:

  1. Analyze opportunities your product can address in the terms of sales and marketing.
  2. Craft an effective story that centers on your content and how it can drive revenue, sales, customer satisfaction and loyalty.
  3. Prove it with metrics that speak to the stakeholders.

When it comes to metrics, page views of documentation usually don’t impress managers much. Instead, Alyson suggested “time-to-value” (TTV) which measures the customer’s time from buying or paying for the product to the moment they reap value from it. This is similar to “return-on-investment”, but TTV can be clearer to measure when investment consists of one-time payments plus maintenance fees. Also, it’s easier for tech comm to favorably influence TTV… 🙂

A. Ames & A. Riley on info experience models at STC12

Andrea Ames and Alyson Riley, both from IBM, presented a dense whirlwind tour on “Modelling Information Experiences” that combine four related models into a heavy-duty, corporate information architecture (IA).

While the proceedings don’t include a paper on this session, Andrea posted the slides, and the presenters published a related article (login required) “Helping Us Think: The Role of Abstract, Conceptual Models in Strategic Information Architecture” in the January 2012 issue of the STC’s intercom journal.

The session proceeded in six parts. First, Alison explained IA models in general and how they work. Then Andrea described each of the four model types that make up an IA specifically.

IA models as science and art

Information architecture relates to science as its models draw on insights and theories of cognition. And its models relate to art as they aim to create a meaningful experience. Both aspects are important. Only if IA models manage to blend science and art can they touch the head and the heart.

The session focuses on IA models instead of theories (which are too vague and abstract) or implementations (which are too specific and limited). Thanks to the in-between position of IA models, we can use them to

  • Ask the right questions to arrive at a suitable, feasible IA
  • Tolerate the ambiguities of “real life”

Models present descriptive patterns, not prescriptive rules. They don’t say how stuff must be, but how it can be represented. They differ from real life, but real life is still recognizable in them.

That means you cannot simply implement a model on autopilot and get it right. Instead, you have to

  • Think how to implement the model
  • Vary the model for your users’ benefit
  • Listen to the right knowledgeable people when implementing

Models help you think

To arrive at your concrete IA, you take the model’s abstract patterns and apply your project-specific details to them, the who, what, where and when.

This task is less mechanical and less copy-and-paste than it sounds. It’s not so much a question of following rules and recipes, but of making abstract patterns come to life in a coherent, flexible whole. (If you’ve ever tried to create meaningful concept or task topics by following an information model, you know it’s more than just filling in a DITA template. You need to use your own judgment about what goes where to achieve and maximize user benefit.)

Since there are four related models, you need to think carefully how each of these models should benefit your users. And the models help you think, they scale and adapt to:

  • How your business and its information requirements develop over time, how they grow and expand in desired directions
  • How your customers find, understand and apply the information they need

The four IA model types

The IA model that Andrea then explained consists of four related model types:

use model (content model + access model = information model)

Each of these model types needs to be developed and validated separately.

The use model defines how users interact with information. It describes standard scenarios for optimal user experience within the product or system context. It outlines what information users need and why and how they use it. It includes use scenarios for the entire product life cycle and user personas that outline different types of users. Fortunately for us technical communicators, Andrea pointed out, describing all this is part of our core skill set.

The content model defines how information is structured effectively. This could be DITA (in the case of the company I work for, this is what we call our DITA-derived “information model”). It includes the granular information units and their internal structure, for example, task topics and their standard sequence of contained information. It also describes how these granular units are combined into deliverables.

The access model defines how users access the information efficiently. It makes provided information useable, thanks to a navigation tree, a search function, a filtering function to increase the relevance of search results, an index, etc. Artefacts of this model type are wireframes, storyboards, a navigation tree and the like.

The information model defines how users get from one stage to the next. It uses the other three model types as input and fills in the gaps. It combines the content and access models which probably work fine during the installation and configuration processes, but may not yet carry a user persona from one stage to the next. As such, the information model is sort of the auxiliary topic that you sometimes need to insert between concept, task and reference topics to make a complete book out of them. At the same time, this model type is more detailed than the use model and closer to the other two types.

My takeaways

I was extremely grateful for this session and rank it among the top 3 I’ve seen at the summit – or any tech comm conference I’ve been to! Yes, it was fairly abstract and ran too long – my only complaint is that it left only 2 minutes for discussion at the end.

As abstract as much of the session was, it actually solved a couple of problems I couldn’t quite put into words. After designing and teaching our company’s DITA-derived information model (which is a “content model” by this session’s names), I thought our model was applicable and useful, but it had two problems:

  • Our model lacked context. – Now I know that’s because we haven’t mapped out our use model in the same detail and failed to connect the two.
  • Our model was baked into a template for less experienced writers to fill in – with varying results. – Now I know that’s because the models are not supposed to provide templates, but require writers to use their own judgment and keep in mind the big picture to deliver effective information.

Another lesson I learned is that many structured information paradigms seem to include a less rigid element that sweeps up much of the miscellaneous remnants. In DITA, there’s the general topic which is used for “under-defined” auxiliary topics to give structure, especially to print deliverables such as manuals. In this IA model, there’s the information model which fills the gaps and ensures a more seamless user experience than the other three models can ensure.

– For an alternative take, see Sarah Maddox’ post about this session.