archive for the ‘our culture & processes’ category

Ethnography in Industry: Methods for distributed & large data sets (part two)

30 August 2010 | Nick Yee

We believe that virtual worlds and similar Web 2.0 spaces hint at an emerging mixed or "hybrid" ethnographic methodology that depends on agile collaborations between quantitative researchers, qualitative researchers, and software engineers. This is not just an academic enterprise. The ability to glean this data has many implications for designing and scaffolding online communities, learning new aspects of personality and social behavior in online worlds, and mapping digital personas to physical needs. The ability to leverage this architecture for more tailored marketing is one commercial opportunity. In addition to inferring basic demographics, personality inferences may lead to more nuanced methods of targeted advertising. And the ability to infer demographics based on online interaction metrics helps fill in the gaps left from zip code segmentation alone -- after all, not everyone who lives in your neighborhood (or in your home!) is exactly like you...

Ethnography in industry: Objectives?

27 April 2010 | Victoria Bellotti

All of us have encountered a lot of confusion and misconceptions about ethnography, especially relative to the many methods that can be used to inform technology design. In my first post here, I’d really rather respond to the obvious and eminently reasonable question I often hear in my work as a researcher in the field of user-centered technology innovation: “What’s it good for, in my business?” In today’s hard-nosed and often economically trying times, ethnography can be seen as a tactical weapon enabling companies to gather new insights and thus gain advantage over their competition. Ethnographers’ data collection and analysis methods have therefore been condensed, recombined, adapted – both systematically and as-needed – to meet these business demands.

Innovation: defining, doing, measuring

31 March 2010 | Mark Bernstein

[The Economist invited us to contribute an abridged version of this post, "How do you define innovation?", for their blog.] Innovation is a sorely overused word. Yet we are constantly asked to define it. A number of theorists and practitioners have offered up their variations: product innovation, business model innovation, technology innovation, design innovation, radical innovation, incremental innovation, disruptive innovation, open innovation…and so the list goes on. All are useful; none are complete. I don't have a pat answer, catchy definition, or compelling metaphor for this. But here’s what I do know: however it is defined, innovation is a valuable change, unconstrained by the way things are. I think I can safely claim that we’re speaking from experience…

Shift Happens (at PARC)

3 March 2010 | Mark Bernstein

PARC hosted a fieldtrip for TTI/Vanguard attendees following their recent "Shifts Happen" conference in San Francisco. [Through private conferences that they describe as "part classroom, part think-tank, and part laboratory", TTI/Vanguard is a forum for senior-level executives that links strategic technology planning to business success.] Surprisingly, the questions I was asked before and after the demo-presentation tour weren’t that different. Basically, folks were looking for simple answers or replicable formulas to some pretty fundamental challenges: How do we do what we do? How do we do it differently than before? How do we make the right choices? There's no single formula, but...

Defining ubiquitous computing vs. augmented reality

2 March 2010 | Bo Begole

What's the difference between Ubiquitous Computing ("ubicomp") and Augmented Reality ("AR")? I hear this question often, and you could replace "augmented reality" in that question with any of the following buzzy paradigms for people-interacting-with-computers: Virtual Reality, Pervasive Computing, Mobile Computing, Wearable Computing, Multi-Device Interaction, Cloud Computing, Intelligent Systems, Ambient Intelligence, Context-Aware Computing, Adaptive Systems, Machine Perception, Social Computing, Smart Environments, Everyware, and so on. For the most part, I don’t find formal definitions useful; you can call it whatever suits your fancy. All that matters is that I understand what you mean when you use a term and that you understand what I mean when I use it. The attributes of a definition that carry lasting meaning are not technological properties (performance, cost, size, distribution, latency), but the core capabilities that the paradigm enables for usage.

On keeping U.S. innovation competitive

18 November 2009 | Tamara St. Claire

PARC today is no longer “Xerox PARC” but a commercial entity with multiple Fortune 500 and other clients. We're building our contemporary innovation model by positioning ourselves at the heart of industrial R&D, government contracts, and world-class university research. (For us, the last one is translated as bringing together the top minds from diverse fields: our talent is our primary asset.) To support the next waves of innovation, we need to examine how the rest of the U.S. and world will replicate Silicon Valley – with its access to top talent, multicultural citizens, venture infrastructure and corporate partners, universities, and inexhaustible energy. But here’s the thing: two-thirds of our commercial income comes from abroad. Asia, in particular, is aggressively probing for new engines of innovation.

Experts’ domain knowledge improves automated recommendations

9 November 2009 | Ellen Isaacs

It’s almost eerie how well the music website Pandora recommends music based on just one example of a favorite song. It does so by relying on human experts to characterize songs based on a large and musically sophisticated set of characteristics (melody, harmony, rhythm, orchestration, etc.). This approach -- of using human expertise to develop a rich set of attributes that deeply capture the essence of an item -- could be adapted to greatly improve the recommendations currently being offered in other domains, such as news, movies, hotels and so on. In our enthusiasm to develop automated recommendation systems, Pandora reminds us of the value of incorporating the intelligence of domain experts into the process.

Brainstorming for quality ideas: 10 tips

6 October 2009 | Jennifer Ernst

I've often heard "brainstorming" touted as a way to make an organizational culture more innovation-friendly. No argument there: brainstorms, if well-constructed, can be a great source of new ideas. But the problem for many companies isn't a lack of ideas. More often, it's a lack of high-quality ideas and poor practices for supporting the transformation from idea to innovation -- i.e., the implementation. In these cases, open-ended idea generation isn't likely to lead to organizational wins. These organizations need to focus on improving the quality of ideas and the mechanisms for selecting and supporting them going forward. Brainstorms are an interesting technique to look at, because they represent a microcosm of organizational behaviors... the behaviors that support or undermine innovation.

Augmented Reality: Increasing collective intelligence

23 July 2009 | Lawrence Lee

Search engines like Google have trained us to believe we can find the answer to any question. Now activity streams from Twitter, Facebook, and others are changing our expectations around information yet again. We now demand information in real-time that’s socially and contextually relevant. Contextual information transforms our interactions within our physical environment... This area of research is called Augmented Reality, and it spans a wide spectrum of applications...

Experimenting on Mechanical Turk: 5 How Tos

21 July 2009 | Markus Jakobsson

Performing human-subjects experiments on Amazon Mechanical Turk offers many benefits, including very low experiment costs, quick turn-around rates, and relatively simple approvals from human subjects boards. But you have to be careful to avoid bias and error...