Information architecture has been used improve UX for around thirty years. The focus has been on structuring information so it can be more easily found, understood, and acted upon, primarily via website and app navigation systems. I think of this as UX-oriented IA or ‘IA classic.’

While valuable, IA classic’s scope is limited. Websites and apps are downstream from higher-level business decisions that have greater impact on the organization. For example,

  • Should we build the product at all?
  • Who will it serve?
  • Where will it be available?
  • How will it make money?
  • Who will support it?

These are strategic questions. (See Martin & Lafley’s Playing to Win for a definitive set.) These questions are answered — explicitly or not — well in advance of deciding which options to include in nav menus.

That is, you can’t effectively design IA classic if you don’t understand its underlying drivers. This assumes the strategy has been thought through. Few organizations actually do; all have a strategy but often it’s unintentional. (Plans, goals, roadmaps, and visions are not strategies.)

Ultimately, strategy is as the org does.

Intriguingly, the research that informs IA classic serves as a catalyst for strategic discussions. The process uncovers latent directions about how the org wants to show up in the world.

Put differently: IA classic is a great MacGuffin for strategic discussions. I’ve seen stakeholders use IA deliverables (e.g., conceptual models) to explain how the organization works and what it aims to do. It’s obvious proof of value beyond improved findability.

But IA can create even more value if applied upstream. An organization with considered information structures has a significant advantage over one that’s making things up as it goes along. (This is true for established orgs rather than startups. Early stage companies need more leeway.)

What if organizations could use the proven tools and processes of IA classic to make better decisions? I believe they can and should. There’s a need for what I call strategic information architecture (SIA): explicitly structuring information to support the organization’s strategic directions.

Core Axioms

Before we unpack this, let’s acknowledge a few axioms.

  • Leadership’s primary focus is ensuring the business remains a going concern. “A going concern” means surviving. Of course, this is necessary but not sufficient. There’s little point in scraping by; the business must return a profit.

  • Free markets are highly competitive. The business won’t remain a going concern if it’s not constantly improving — i.e., looking for an edge. Innovation, optimization, and evolution are good for everyone, including customers.

  • Leadership’s decisions affect the business’ chances. Decisions happen at all levels. A salesperson decides whether to offer a discount. A product manager decides on a product’s features. The CEO decides to spin up a new business. The higher-level decisions have greater impact.

  • Data are central to the business’ operations. Everything the business does uses and generates data. When a customer buys something, that is data. When the customer passes up an offer, that is data. Data are important signals.

  • Data are not enough. Data points are useless (or worse, distracting) on their own. To aid in decision-making, data must be contextualized and structured — i.e., they must be turned into information. (More on what this means below.)

  • Better information leads to better decisions. When structured correctly, information helps leadership make better decisions. This means

  1. decisions support the organization’s strategic directions, and
  2. they’re made in a timely manner.

A decision that seems good for a department in the near term might be disastrous for the company in the long term. The right decision might come too late to matter. You need both coherence and timeliness.

“Better information” also means two things:

  1. information is relevant to the decision being made, and
  2. the underlying data are factual — i.e., they correspond to reality.

Leadership might have access to lots of information but not what’s needed to make a particular decision. Worse, leaders may think they have the information they need, but the underlying data doesn’t reflect reality.

Good information offers both, and both are essential for good decision-making.

What is Information?

Information is anything that allows someone to make better decisions. Take “no dog poop” signs on front lawns: they allow you to predict the likely outcome of getting caught while letting your dog go on that yard.

Dog poop sign courtesy of https://www.dogpoopsigns.com/

Dog poop sign courtesy of https://www.dogpoopsigns.com/

A customer choosing a bottle of wine needs to know its price, varietal, origin, and vintage. A rating or review might also help. These attributes allow customers to pick the right bottle for them.

The specifics of a particular bottle — the fact it’s a 2021 Californian Syrah at $89 a pop — are data. They only make sense as a set and when understood in the context of other comparable data.

Data become information when they inform someone — i.e., when they aid their decision-making. This could be choosing which yard to let your dog to poop on, which bottle to buy, which menu item to click on, or whether to invest in a new facility.

Decisions have consequences: some are small, others quite large. Pooping on the wrong yard, buying the wrong wine, or clicking on the wrong menu item have low stakes. Investing in the wrong project has very high stakes. In that case, choosing poorly can be ruinous.

Much of what goes by ‘information technology’ is about capturing, transmitting, and storing data. Data only become useful and valuable when turned into information — i.e., when they’re structured, contextualized, and presented in ways that generate insights and lead to better decisions.

Data are essential, but businesses need information. In particular, they need information structured to support their efforts to win. That’s where strategic IA comes in.

Strategic IA Offerings

Strategic information architecture uses the methodologies and tools of IA to structure information so it supports an organization’s strategic directions. What does that look like? It depends on what the organization needs and level of maturity.

Many ‘digitally native’ businesses (i.e., those who primarily create value online) understand their information environments. But most organizations don’t fit this description. These orgs approach the structure of their information environments as an IT problem.

Most IT departments focus on data storage, transmission, processing, and security. All are necessary but insufficient. The information latent in these systems must support the organization’s strategic goals and approaches. This means:

  • Enhancing decision-making by giving leadership the right information at the right time,
  • Supporting business objectives by ensuring cohesion and alignment across the business, and
  • Improving efficiency and effectiveness by optimizing and scaling relevant processes while ensuring compliance with policies and regulations.

Again, these all inform traditional IA projects. But in those cases, the scope is limited to the system’s UX. The same methodologies used in structuring websites and products can be applied toward

  1. understanding the organization’s current information environment, and
  2. specifying structures for an improved information environment.

Rather than site maps and navigation structures, SIA produces maps, models, metadata structures, and taxonomies. An engagement might start with an assessment, resulting in a map of the current information environment, before moving on to prescriptive model-making.

These are abstractions, but highly practical ones. These diagrams and models enable organizations (even those that aren’t digitally native) to create value for customers and win in the marketplace by using information more intentionally. They inform on-the-ground information systems, including product UX and marketing materials.

Creating More Value Through IA

Does adopting SIA mean abandoning IA classic? Far from it: SIA is an evolution of the discipline, focusing on initiatives with greater leverage and potential. Better end-user experiences are downstream from better strategic decisions.

I see it as the obvious next step in my professional journey. As I’ve done throughout my career, I circle back to Wurman’s definition of an information architect:

1) the individual who organizes the patterns inherent in data, making the complex clear. 2) a person who creates the structure or map of information which allows others to find their personal map to knowledge. 3) the emerging 21st century professional occupation addressing the needs of the age focused upon clarity, human understanding and the science of the organization of information.

Nothing in this definition constrains the discipline to a particular medium. Better organized information is needed everywhere. Clarity is needed everywhere. Why not focus IA efforts on higher-impact challenges?

I’m excited to use IA to create more value. Coupled with generative AI, SIA will help orgs better understand their information environments and make more cohesive — and coherent — decisions. The results will benefit everyone.