EnjoyTech

A framework that I use to think about problems disruptive technology could help solve is based on what Donald Rumsfeld wrote in his memoir, Known and Unknown : Reports that say that something hasn't happened are always interesting to me, because as we know, there are known knowns; there are things we know we know. We also know there are known unknowns; that is to say we know there are some things we do not know. But there are also unknown unknowns -- the ones we don't know we don't know. And if one looks throughout the history of our country and other free countries, it is the latter category that tend to be the difficult ones. A couple of decades ago technology was seen as means to automate manual processes and bring efficiency. While largely automation is a prerequisite in the modern economy the role of technology has significantly changed to create unique differentiation and competitive advantage against peers in an industry. Many people are working on making things bett...

I have worked with many product managers on a product vision exercise. In my observation the place where the product managers get hung up the most is when they confuse product vision for product definition. To use an analogy, product vision is a trailer and product definition is a movie. When you're watching a movie trailer it excites you even though you fully don't know how good or bad the movie will be. Abstract and unfinished A trailer is a sequence of shots that are abstract enough not to reveal too much details about the movie but clear enough to give you the dots that your imagination could start connecting. Some of the best visions are also abstract and unfinished that leave plenty of opportunities for imagination. Product visions should focus on "why" and "what" and not on "how" and most importantly should have a narrative to excite people to buy into it and refine it later on. Vision should inspire the definition of a product and not defin...

For an ISV (Independent Software Vendor) it is everyone's job to ensure customer success but it is no one person's job. This is changing. I see more and more companies realizing this challenge and want to do something about it. Sales is interested in maintaining relationship with customers for revenue purposes and support works with customers in case of product issues and escalations. Product teams behave more like silos when they approach their customers because of their restricted scope and vision. Most chief technology officers are fairly technical and internal facing. Most of them also lack the business context—empathy for true business challenges—of their customers. They are quite passionate about what they do but they invariably end up spending a lot of time in making key product and technical decisions for the company losing sight of much bigger issues that customers might be facing. Most chief strategy officers focus on company's vision as well as strategy across li...

Being a passionate design thinker I am a big believer in failing fast and failing often . I have taken this one step further; I celebrate one failure every week. Here's why: You get more comfortable looking for failures, analyzing them, and learn from it I have sat through numerous post-mortem workshops and concluded that the root causes of failures are usually the same: abstract concepts such as lack of communication, unrealistic scope, insufficient training, and so on. If that’s true, why do we repeat the same mistakes, causing failure to remain a common situation? Primarily because many people find it hard to imagine and react to abstractions, but can relate much better when these concepts are contextualized into their own situation. Post-mortem of a project would tell you what you already suspected; it's hindsight and it's a little too late. I have always advocated a "pre-mortem workshop" to prepare for a failure in the beginning. Visualize all the things that...

Jake Porway who was a data scientist at the New York Times R&D labs has a great perspective on why multi-disciplinary teams are important to avoid bias and bring in different perspective in data analysis. He discusses a story where data gathered by Über in Oakland suggested that prostitution arrests increased in Oakland on Wednesdays but increased arrests necessarily didn't imply increased crime. He also outlines the data analysis done by Grameen Foundation where the analysis of Ugandan farm workers could result into the farmers being "good" or "bad" depending on which perspective you would consider. This story validates one more attribute of my point of view regarding data scientists - data scientists should be design thinkers . Working in a multi-disciplinary team to let people champion their perspective is one of the core tenants of design thinking. One of the viewpoints of Jake that I don't agree with: "Any data scientist worth their salary wil...

I recently came across this interview (thanks Dharini for the link!) with Nick Chamandy, a statistician a.k.a a data scientist at Google. I would encourage you to read it; it does have some great points. I found the following snippets interesting: Recruiting data scientists: When posting job opportunities, we are cognizant that people from different academic fields tend to use different language, and we don’t want to miss out on a great candidate because he or she comes from a non-statistics background and doesn’t search for the right keyword. On my team alone, we have had successful “statisticians” with degrees in statistics, electrical engineering, econometrics, mathematics, computer science, and even physics. All are passionate about data and about tackling challenging inference problems. I share the same view. The best scientists I have met are not statisticians by academic training. They are domain experts and design thinkers and they all share one common trait: they love data!...

My ongoing conversations with several people continue to reaffirm my belief that Data Science is still perceived to be a sacred discipline and data scientists are perceived to be highly skilled statisticians who walk around wearing white lab coats. The best data scientists are not the ones who know the most about data but they are the ones who are flexible enough to take on any domain with their curiosity to unearth insights. Apparently this is not well-understood. There are two parts to data science: domain and algorithms or in other words knowledge about the problem and knowledge about how to solve it. One of the main aspects of Big Data that I get excited about is an opportunity to commoditize this data science—the how—by making it mainstream. The rise of interest in Big Data platform—disruptive technology and desire to do something interesting about data—opens up opportunities to write some of these known algorithms that are easy to execute without any performance penalty. Run K Me...

Many enterprise software vendors sympathize. "We know it's a bad experience" or "We will fix the usability." One of the reasons the software is not usable is because the makers never had any empathy for the end users who would use it. In many cases the makers didn't even know who their end users were; they only knew who would buy the software. As far as enterprise software is concerned people who write checks don't use the software and people who use software don't write checks and have a little or no influence in what gets bought. Though the dynamics are now changing. Usability is the last step; it's about making software usable for the tasks that it is designed for. It's not useful at all when the software is designed to solve a wrong problem. Perfectly usable software could be completely useless. It's the job of a product manager, designer, and a developer to assess the end user needs—have empathy for them—and then design software that...

During his recent visit to the office of 37 Signals, Jeff Bezos said, "to be consistently objective, one has to be objectively inconsistent." I find this perspective very refreshing that is applicable to all things and all disciplines in life beyond just product design. As a product designer you need to have a series of point of views (POV) that would be inconsistent when seen together but each POV at any given time will be consistently objective. This is what design thinking, especially prototyping is all about. It shifts a subjective conversation between people to an objective conversation about a design artifact. As I have blogged before I see data scientists as design thinkers . Most data scientists that I know of have knowledge-curse. I would like them to be  consistently objective by going through the journey of analyzing data without any pre-conceived bias. The knowledge-curse makes people commit more mistakes . It also makes them defend their POV instead of looking f...

World Airline Routes Every company is looking for that cool data scientist who will come equipped with all the knowledge of data, domain expertise, and algorithms to turn around their business. The inconvenient truth is there are no such data scientists. Mike Loukides discusses the overfocus on tech skills and cites DJ Patil : But as DJ Patil said in “Building Data Science Teams,” the best data scientists are not statisticians; they come from a wide range of scientific disciplines, including (but not limited to) physics, biology, medicine, and meteorology. Data science teams are full of physicists. The chief scientist of Kaggle, Jeremy Howard, has a degree in philosophy. The key job requirement in data science (as it is in many technical fields) isn’t demonstrated expertise in some narrow set of tools, but curiousity, flexibility, and willingness to learn. And the key obligation of the employer is to give its new hires the tools they need to succeed. I do agree there's a skill ga...

A few months back, I was helping a very large customer of ours to help simplify as well as automate their process of trading financial instruments. During one of my many visits to their office, I met a person who was trying to explain to me his job in supporting the people that are involved in this super complex process. I always ask a lot of questions — until they're totally annoyed and ready to kick me out of the room — to get a complete understanding of the business rationale behind whatever they're thriving for and their personal motivation behind it. Something unusual happened at this meeting. Instead of getting into the gory technical details of how they get things done, he chose to tell me a short and simple story. "You know, um.. there's this early morning meeting everyday that Peter goes to with a bunch of other people. They all gather around a large table in a dimly lit conference room with a bunch of printed spreadsheets, a laptop, and a large calculator. Pe...

Photo credit: String Theory by Michael Krigsman The endless succession of failed projects forces one to question why success is elusive, with an extraordinary number of projects tangling themselves in knots. These projects are like a child’s string game run amok: a large, tangled mess that becomes more convoluted and complex by the minute. IT projects fail all the time. Business blames IT, IT blames the system integrator (SI), who then blames the software vendor. After all this blaming and shaming, everyone goes back to work on another project without examining the project management methods and processes that caused the failure. And, so, they fail again. There’s no one definition of design thinking. It’s a mindset and set of values that applies both analytical and creative thinking towards solving a specific problem. Design thinking is about how you think and not what you know; it is about the journey and not the destination. Having followed Michael Krigsman ’s analysis of IT project ...

Bruce Nussbaum, a design thinking thought leader and a professor of Innovation and Design at Parsons The New School of Design, recently wrote that Design Thinking Is A Failed Experiment . He claims that: "Design Thinking has given the design profession and society at large all the benefits it has to offer and is beginning to ossify and actually do harm." Rubbish. I would argue otherwise. Design thinking is not a catchphrase anymore, and that perhaps is an issue for someone like Bruce who wants to invent a new catchphrase to sell his book. When I tweeted his post, Enric Gili - a friend, co-worker, and a design thinker whom I respect - had to say this: I couldn't agree anymore. I have learned, practiced, and taught design thinking, for living. I have worked with folks from IDEO , closely, very closely. I have mentored students at Stanford d.school and I live and breathe design thinking. I don't think of it as a method that goes out of fashion. For me, it's a relig...

The large scale software companies often deal with the tension between incremental and revolutionary innovation. They know that if they only keep listening to their customers' requests the very same customers will put them out of the business. Clayton Christensen has captured this phenomenon in The Innovator's Dilemma . Over a period of time these companies have managed to execute the incremental innovation really well to deliver the same software release after release and occasionally introduce new products. However most of these companies struggle to incubate revolutionary innovation inside the company since it is fundamentally a different beast. The executives are often torn between funding the revolutionary initiatives to ride the next big wave and funding the incremental innovation that the current customers and the market expects. It is absolutely imperative for the executive management to differentiate between these two equally important but very different types of inno...

I was at the Web 2.0 expo in San Francisco last week. It was not very different from the previous year except that I could see the impact of slow economy - shrinking attendance, less crowded booths, and "Hire Me" ribbons . Tim O'Reilly's keynote was interesting. He said that Web 2.0 was never about the version number (read, he does not like people calling Web 3.0 a successor of Web 2.0). He had the equation Web 2.0 + World = Web Squared. I changed it to Web 2.0 + Cloud = Web 2 . The cloud seems more appropriate and the superscript is much cooler. If this catches on, remember, you read it here first! The biggest shift that I have observed in Web 2.0 is the exponential growth of social media. This was evident at the Web 2.0 expo by looking at the number of participating social computing companies. Web 2.0 is certainly taking the direction of social computing. Tim mentioned in his keynote that the immense data gathered by the sensors and other means have hidden meanin...

The designers have been designing tools, processes, and methods to support and not to change people's behavior. In contrast designing for sustainability would fundamentally require changing people's behavior. The behavior change to achieve the sustainability goals would mean offering different alternatives, encourage reduced consumption, make people conscious of their behavior, and leverage peer pressure and competition. The design that maintains status quo will not help to achieve sustainability goals. The design will have to be provocative and challenge user's assumptions in many ways. Design Thinking is about how you think and not what you know; it is about the journey and not the destination. For a problem of massive scale such as sustainability where we still know a little and the desired outcome may take years, following are some elements of design thinking that could help make world a better place to live for the generations to come. Ambidextrous-thinking: Sustainab...

Steve Portigal sent me an article that he wrote in the Interactions magazine asking for my feedback. Unfortunately the magazine is behind a walled garden and would require a subscription but if you reach out to Steve he should be able to share the article with you. In the absence of the original article I will take liberty to summarize it. Steve has described how companies generally go about making stuff in his “incomplete” framework: Be a Genius and Get It Right: One-person show to get it right such as a vacuum cleaner by James Dyson. Be a Genius and Get It Wrong: One-person show to get it wrong such as Dean Kamen’s Segway. Don’t Ask Customers If This Is What They Want: NBA changing the basketball design from leather to synthetic microfiber without asking the players Do Whatever Any Customer Asks: Implementing the changes as requested by the customers exactly as is without understanding the real needs. Understand Needs and Design to Them: Discovery of the fact that women shove...