"human-centered design" entries

Trillions of things sending billions of messages

The O'Reilly Radar Podcast: Mickey McManus on preparing for an era of unbounded malignant complexity.

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In this week’s episode of the Radar Podcast, O’Reilly’s Mike Hendrickson talks with Autodesk research fellow Mickey McManus about engaging with extreme users and what’s going to happen when we have trillions of things sending billions of messages. McManus also talked about how we can prepare for the coming era of unbounded malignant complexity.

Unbounded malignant complexity

In talking about Trillions, a book McManus co-authored with Peter Lucas and Joe Ballay, McManus explained what exactly we’re up against in the next five years as our world becomes more and more permeated with computation:

We are probably five years away from trillions of computing devices, and that wouldn’t be bad, but then imagine a world saturated with computers. It’s almost like a super-saturated solution. They’re not all connected, so maybe we could cope with that. But, concurrently, connectivity is joining Moore’s law — people like Intel are working on Moore’s law radio that basically puts all the parts of a radio on silicon. Which means that, suddenly, the cost of connectivity drops to dirt, to nothing, to dust.

We’ll have this super-saturated solution where that seed hits it, and we’re going to turn the sock inside out. We’re going to go from information in computers, like your super computer in your pocket, to us being surrounded by information. … The next information age will be an era of unbounded malignant complexity. Because there’s a lot of stuff. We have to get ready for that.

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A human-centered approach to data-driven design

The O'Reilly Radar Podcast: Arianna McClain on humanizing data-driven design, and Dirk Knemeyer on design in emerging tech.

This week on the O’Reilly Radar Podcast, O’Reilly’s Roger Magoulas talks with Arianna McClain, a senior hybrid design researcher at IDEO, about storytelling through data; the interdependent nature of qualitative and quantitative data; and the human-centered, data-driven design approach at IDEO.

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In their interview, Magoulas noted that in our research at O’Reilly, we’ve been talking a lot about the importance of the social science design element in getting the most out of data. McClain emphasized the importance of storytelling through data at IDEO and described IDEO’s human-centered approach to data-driven design:

“IDEO really believes in staying and remaining human-centered throughout the data journey. Starting off with, how might we measure something, how might we measure a behavior. We don’t sit in a room and come up with an algorithm or come up with a question. We start by talking to people. … We’re trying to build measures and survey questions to understand at scale how people make decisions. … IDEO remains data-driven to how we analyze and synthesize our findings. When we’re given a large data set, we don’t analyze it and write a report and give it to people and say, ‘This is the direction we think you should go.’

“Instead, we look at segmentations in the data, and stories in the data, and how the data clusters. Then we go back, and we try to find people who are representative of that cluster or that segmentation. The segmentations, again, are not based on demographic variables. They are based on needs and insights that we heard in our qualitative research. … What we’ve recognized is that something that seems so clear in the analysis is often very nuanced, and it can inform our design.”

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DevOps keeps it cool with ICE

How inclusivity, complexity, and empathy are shaping DevOps.

ice

Over the next five years, three ideas will be central to DevOps: the need for the DevOps community to become more Inclusive; the realization that increasing Complexity of systems is the underlying reason for DevOps; and the critical role of Empathy in the growth and adoption of DevOps. Channeling John Willis, I’ll coin my own DevOps acronym, ICE, which is shorthand for Inclusivity, Complexity, Empathy.

Inclusivity

There is a major expansion of the DevOps community underway, and it’s taking DevOps far beyond its roots in agile systems administration at “unicorn” companies (e.g., Etsy or Netflix). For instance, a significant majority (80-90%) of participants at the Ghent conference were first-time attendees, and this was also the case for many of the devopsdays in 2014 (NYC, Chicago, Minneapolis, Pittsburgh, and others). Moreover, although areas outside development and operations were still underrepresented, there was a more even split between developers and operations folks than at previous events. It’s also not an accident that the DevOps Enterprise conference took place the week prior to the fifth anniversary devopsdays and included talks about the DevOps journeys at large “traditional” organizations like Blackboard, Disney, GE, Macy’s, Nordstrom, Raytheon, Target, UK.gov, US DHS, and many others.

The DevOps community has always been open and inclusive, and that’s one of the reasons why in the five years since the word “DevOps” was coined, no single, widely accepted definition or practice has emerged. The lack of definition is more of a blessing than a curse, as DevOps continues to be an open conversation about ways of making our organizations better. Within the DevOps community, old-time practitioners and “newbies” have much to learn from each other.

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How might we …

Human-centered design techniques from an ideation workshop.

By Bo Peng and Aaron Wolf of Datascope Analytics

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Bo Peng at a Datascope Analytics Ideation Workshop in Chicago

At Datascope Analytics, our ideation workshop combines elements from human-centered design principles to develop innovative and valuable ideas/solutions/strategies for our clients. From our workshop experience, we’ve developed a few key techniques that have enabled successful communication and collaboration. We complete certain milestones during the workshop: the departure point, the dream view, and curation with gold star voting, among others. These are just a few of the accomplishments that are achieved at various points during the workshop. In addition, we strive to support cultural goals throughout the workshop’s duration: creating an environment that spurs creativity and encourages wild ideas, and maintaining a mediator role. These techniques have thus far proven successful in providing innovative and actionable solutions for our clients.

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Design, Math, and Data

Lessons from the design community for developing data-driven applications

By Dean Malmgren

When you hear someone say, “that is a nice infographic” or “check out this sweet dashboard,” many people infer that they are “well-designed.” Creating accessible (or for the cynical, “pretty”) content is only part of what makes good design powerful. The design process is geared toward solving specific problems. This process has been formalized in many ways (e.g., IDEO’s Human Centered Design, Marc Hassenzahl’s User Experience Design, or Braden Kowitz’s Story-Centered Design), but the basic idea is that you have to explore the breadth of the possible before you can isolate truly innovative ideas. We, at Datascope Analytics, argue that the same is true of designing effective data science tools, dashboards, engines, etc — in order to design effective dashboards, you must know what is possible.

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Design thinking and data science

Solving problems with data necessitates a diversity of thought.

By Dean Malmgren and Jon Wettersten

JonWetterstenThere’s a lot of hype around “Big Data” these days. Don’t believe us? None other than the venerable Harvard Business Review named “data scientist” the “Sexiest Job of the 21st Century” only 13 years into it. Seriously. Some of these accolades are deserved. It’s decidedly cheaper to store data now than it is to analyze it, which is considerably different than 10 or 20 years ago. Other aspects, however, are less deserved.

In isolation, big data and data scientists don’t hold some magic formula that’s going to save the world, radically transform businesses, or eliminate poverty. The act of solving problems is decidedly different than amassing a data set the size of200 trillion Moby Dicks or setting a team of nerds loose on the data. Problem solving not only requires a high-level conceptual understanding of the challenge, but also a deep understanding of the nuances of a challenge, how those nuances affect businesses, governments, and societies, and—don’t forget—the creativity to address these challenges.

dean_DsA-237x300In our experience, solving problems with data necessitates a diversity of thought and an approach that balances number crunching with thoughtful design to solve targeted problems. Ironically, we don’t believe this means that it’s important to have an army of PhDs with deep knowledge on every topic under the sun.

Rather, we find it’s important to have multi-disciplinary teams of curious, thoughtful, and motivated learners with a broad range of interests who aren’t afraid to immerse themselves in a totally ambiguous topic. With this common vision, IDEO and Datascope Analytics decided to embark on an experiment and integrate our teams to collaborate on a few big data projects over the last year. We thought we’d share a few things here we’ve learned along the way.
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Data and human-centered design

Behind the scenes with Datascope Analytics.

filming at the ideation workshop

During a trip to Chicago for a conference on R, I had a chance to cowork at the Datascope Analytics (DsA) office. While I had worked with co-founders Mike and Dean before, this was my first time coworking at their office. It was an eye-opening experience. Why? The culture. I saw how this team of data scientists with different backgrounds connected with each other as they worked, collaborated, and joked around. I also observed how intensely present everyone was…whether they were joking or working. I completely understand how much work and commitment it takes to facilitate such a creative and collaborative environment.

Over the next few months, this initial coworking experience led to many conversations with Dean and Mike about building data science teams, Strata, design, and data both in Chicago and the SF Bay Area. I also got to know a few of the other team members such as Aaron, Bo, Gabe, and Irmak. Admittedly, the more I got to know the team, the more intensely curious I became about the human-centered design “ideation” workshops that they hold for clients. According to Aaron, the workshops “combine elements from human-centered design to diverge and converge on valuable and viable ideas, solutions, strategies for our clients. We start by creating an environment that spurs creativity and encourages wild ideas. After developing many different ideas, we cull them down and focus on the ones that are viable to add life and meaning.”

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