Avoiding Vapor Research

Last month I had the opportunity to speak at the IA Conference. It was a great conference and amazing experience overall (thank you to the IAC19 committee and volunteers). If you were able to attend my presentation…thank you! If you were not able to make it, no worries. I’ll be sharing my thoughts on the topic in upcoming articles, with this overview of vapor research being the first of many to come.

Here’s a quick overview:

The first wave and the next…

The needs and goals we are designing for live in life moments…where work, play, and technology intersect.

In the first wave of technology, we were fixated on the “thing” and all of it’s new capabilities. Which was easy to do, since the user interfaces were the “what” we were focused on designing with a goal to make it easy to use.

But having a product or capability first mentality has been forcing humans to understand the product. It also meant that we were often focused on spending our time testing and optimizing.

The second wave of technology we are experiencing now is going to challenge us even more…

and we are off to a scary start with stock photography already embracing the “potential” of this new technology.

Which leaves me feeling like this guy…asking “why” after the fact.

Surface Data and Deep Data

To date we’ve been focused on Big Data or quantitative data to make data driven decisions. It’s helpful to identify and measure paths, patterns and amounts. It helps us to understand users in a broad and wide context, at scale.

Quantitative data is great at helping us determine what’s working and what’s not. But quantitative data alone has limited context, leaving us only to infer the intent behind the actions we track at best.

Which is why I like to call quantitative data “Surface Data.”

But to get to meaningful insights, we need to go deeper – below the surface to get to the “Why.” Qualitative research, involving humans talking to humans to understand and clarify their goals, needs and reasoning is what I like to call “Deep Data.”

This “Deep Data” is the crucial element of meaningful “Insights.” It’s critical for insights to have traceable evidence to give context to the insights and lend credibility.

But it’s not to say one is better than the other. They are both needed and can complement each other well when they are used for the right purpose and for the appropriate kinds of decisions.

Human understanding first…

But to be successful, we need to take time to understand and define the problem space. One of the best methods to accomplish this is qualitative research – talking with and observing people to learn the “why” – to shape and inform the product.

The more technology is integrated in our life, the more we need to make it truly meaningful to those involved…so we need to understand the humans involved.

The super power of “why”…

Being able to identify the true needs and user goals can re-frame a lot of conversations in the design process and the business as a whole.

So if the “why” is the Super hero in the story…who is the archenemy, the kryptonite of the why?

The enemy…

Vapor Research

  1. Research that lacks credibility or value.
  2. Research that vanishes.

Top 5 Causes of Vapor Research

  1.  Ineffective sharing and socializing
  2.  Research is lost or misplaced
  3.  Lack of supporting evidence
  4.  Inappropriate timing
  5.  Bias in the organization

Fundamentals to avoid vapor research

Build Trust  “Develop Org Empathy”

Collaborate  “Meaningful Involvement”

Rigor, Transparency, and Consistency “Rigor, Transparency, and Consistency”

Research “Backbone”

Plan: “A goal without a plan is a wish”

Collect: “Collect moments not things”

Analyze & Synthesize: “Break it down and take it to the bridge”

Store & Share: “You can’t use what you can’t find”

Framework for building a research practice

There’s a lot to share on this topic, but I think the visual gives you a pretty good overview of the model I’ve been thinking about. You’ll notice it’s focused on the concept of a research “practice”, not on specific “roles” or “departments,” and wrapped around the Research “backbone”.

More coming soon…

There is a lot more I’ll be adding soon to fill out the depth these topics, but hopefully this gives you a good overview. If you have thoughts or feedback to share, please don’t hesitate to drop me a note. We’ll be sure to announce updates to the series on twitter, so be sure to follow us @handrailux.com.

Until next time!

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