20 December 2010 | Editor
Companies often turn to market research studies, focus groups, surveys, ethnography, and other methods for gaining insight into people’s desires and needs. Because if you know people, you: Know your customers. Know what buyers are more likely to adopt. Know what users want and how they act, so you can differentiate your offerings from those of competitors.
While “ethnography” has become a catchall term for categorizing any and all methods for gaining insights into people, true ethnography reveals not just what people say they do, but what they actually do. Ethnography can thus provide a more complete, nuanced, and valid picture of people’s practices, processes, and product use in context.
It’s a powerful tool that can provide actionable insight and reduce corporate R&D risk.
The pioneering use of social scientists in technology corporations — often referred to as corporate ethnography — has largely been attributed to, well, us. But this isn’t intended to be a who-begat-whom post. We’re just trying to set the record straight on the popular tale of ethnography at PARC, because the way the story unfolds reveals how powerful a tool it can be…
The popular story is that Lucy Suchman – one of our earliest social scientists – helped create the green button we see on copy machines today. The story goes more or less like this:
Much of the above did actually happen:
So the ethnographic study didn’t actually reveal the idea for the button. What it did reveal is much more profound:
Suchman’s analysis showed that the popular, AI-centric idea behind the copy machine’s user interface – that the machine could “know” what its users were up to based on sensory input and a predefined user model — was fundamentally flawed.
The video showed how people (not the supposedly intelligent machine) were actually the ones trying to understand how the system responded to their actions (as opposed to the machine trying to respond to the user’s actions). Drawing on ethnomethodology and conversation analysis, Suchman argued that this AI model of “plan” and then “act” is not really how people work.
Ultimately, what the machine sees/knows/is aware of is NOT the same as what the user sees/knows/is aware of. The trouble arises when “design” is unaware of that divergence. And while easy-to-use is a popular value for technologists or UXperts or design houses – executing on this value is not so easy-to-do.
Suchman’s observations and approach were profoundly influential in helping inform the above nuances – not just at PARC, but across the entire field of human-computer interaction. (Among her other honors, Suchman won ACM SIGCHI’s Lifetime Research Award in 2010.)
Today, companies engage us for this expertise – which has continued to evolve at PARC – because ethnography reveals the underlying assumptions or tacit practices behind processes and products (especially ones in novel categories where conventions have not yet been established). Furthermore, skilled ethnographers go beyond observation to tailor their recommendations to specific contexts and business problems, delivering value not just for users but for the company too.
So now you know the story behind the story. If you’re interested in more, you can see Suchman’s book Plans and Situated Actions or its sequel Human-Machine Reconfigurations, where she tells her version of the story in chapter one.
augmented reality big data business models cloud computing contextual intelligence DARPA disruptive innovation electric vehicles ethnography future of maufacturing government ideation and beyond information overload intellectual property intelligent automation location-based long tail malware manufacturing MVP (minimum viable product) open innovation PARC Forum portfolio management printed electronics reading list real options recommendation systems social search startups Steve Jobs twitter Wikipedia Xerox
enter email to choose newsletters: