About Productivity, Social Networks and everything else I'm interested in

Month: January, 2013

John Roderick on String Art Owls, Copper Pipe, and…

Article Complet : http://www.kungfugrippe.com/post/39811125367/string-art-owls
via Pocket

Jeff Bezos on Leading for the Long-Term at Amazon


An interview with Jeff Bezos, CEO of Amazon.com. For more, see The 100 Best-Performing CEOs in the World.

Download this podcast

A written transcript will be available by January 10.

via HBR.org http://blogs.hbr.org/ideacast/2013/01/jeff-bezos-on-leading-for-the.html?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+harvardbusiness+%28HBR.org%29

How to make a change last

How to make a change that last

The answer lies in something we call Energy Rituals — highly specific behaviors or regimes that you do at the same time every day (or on the specific days you select). By setting a sacrosanct time for your routine, you don't have to spend energy thinking about when to get it done. Willpower is a highly finite and limited resource in each of us, so the goal is to use less of it wherever possible, by making more behaviors in our lives automatic.

A new “Introduction to SNA” short course soon!


Peru2008_BorrowersI am going to give another one-day workshop on Introduction to Social Network Analysis  in a couple of weeks time -more precisely on Monday, 14th January, at the University of Greenwich, London, as part of a Winter School for researchers and PhD students in social science, management and economics, dedicated to Analytical Software.

The rationale is pretty much the same as usual. I have stressed many times how the recent rise of online social networking services (Facebook, LinkedIn, Twitter etc.) has drawn massive attention to the field of study of social network analysis (SNA). Yet social networks have always existed and are in fact a constant of human experience  – whether in the family, with friends, at school or on the workplace, to name but a few examples. Likewise, SNA already has a respectable history and has been successfully applied to study a wide variety of social contexts.

The workshop is aimed at those who are new to the field, and would like to betterIndia2009_Borrowers understand whether and how they can use it to enhance their own scholarly practice (whether it is research, teaching or consultancy). All social science backgrounds are welcome, and participants are assumed not to have any previous  knowledge of SNA (or statistics or software use, programming etc.). The goal of the workshop is to provide attendees with basic insight into what social network analysis is, and how it can be used in social science research, together with some hands-on experience of how to use network data and how to graphically represent networks, calculate key metrics, and perform some elementary analyses with Gephi, a powerful, though user-friendly, open-source software for visualizing and analyzing networks graphs.

More specifically, I will start with the fundamental principles of social network analysis and their grounding in social theories – including social science classics – moving then on to the broad range of their possible applications, with examples drawn from the literature. I will particularly insist on the substantial change of mindset that the network perspective requires with respect to standard social science approaches, due to its emphasis on relationships rather than attributes. I will also highlight uses of network-based reasoning to draw business and social policy recommendations.

India2009_LendersI will then present network data, distinguishing type (ego and whole networks), format (edgelist, matrix), collection method (name generators and name interpreters, rosters, archives), and properties (one-mode, two-mode). I will focus on similarities and differences with respect to standard social science data, and discuss some of the opportunities and challenges arising from increasing availability of social network data from the web. I will illustrate the use of visualisation tools, showing how they can support network data interpretation, but also pointing to the limitations of graphs for analytical (rather than just descriptive) purposes.

I will then introduce basic measures of network composition and structure (density, centrality etc.), how they can be used to uncover important aspects of the social phenomenon under study, and how they can be represented graphically. I will briefly mention (but not detail) more complex statistical models of networks (ERGM, Siena).

I will use abundant examples from the literature, and will use my own research as an example, to enable participants to get a concrete sense of how SNA can be fruitfully integrated into social science research.Throughout the workshop, we will do exercises with test data sets in Gephi so that participants get a secure sense of their ability to handle data and derive conclusions from them. I will also provide references to key books, articles, software, websites and other resources for future use. There will be ample opportunities for questions and answers.

More information and registration forms are available from the Workshop website.

via Paola Tubaro's Blog http://paolatubaro.wordpress.com/2013/01/02/introduction-to-sna-short-course-2/

How to Innovate with an Executive Sponsor


Meaningful innovation requires sponsorship. It always has.

In 1959, one of the most important economists you’ve never heard of — Edith Penrose — pointed out as much by chronicling the nature of firm evolution. Penrose explained that all things equal, a firm’s history determines its future. We seed our organizations with resources — people, capital, and equipment — and those resources have productive value in certain areas. Maximizing their value will naturally lead us to make the next decision and the next decision and so on.

At its core, Penrose’s idea is the reason innovation requires sponsorship. Without the foresight and intervention of senior leadership, the firm will simply concentrate on the opportunities that it was destined to concentrate on. Middle managers with limited resources and set evaluation metrics will simply operate in a predictable fashion. It’s why Christensen’s Innovator’s Dilemma is so difficult to overcome. Firms naturally preserve their margins and satisfy their existing customers, steering away from disruptive opportunities. It’s why Howard Yu’s Deep Dive concept is so sensible. Without a senior executive taking an active role in a project to overcome organizational antibodies, even the most thought-through plans can fail.

Unfortunately, while we in the field of innovation are happy to acknowledge the need for executive sponsorship, we rarely talk about when that sponsorship is needed. We rarely talk about how that sponsorship should occur. And we almost never talk about the consequences of bringing too much sponsorship on, too early.

The difficult truth is that sponsorship as it’s traditionally considered inside of large organizations is a double-edged sword. Sponsorship overcomes organizational roadblocks but often comes with a set of inherent limitations. Senior executives focus on big issues every day, when they turn to innovation they need their novel solutions to be equally as large. That’s because nominally, the execs that matter inside of large organizations are used to moving the needle. So when it comes to innovation, executives are trained to value acquisitions, high profile product launches, and anything else they might use to surprise their analysts; without such surprises they can’t generate unforeseen growth and placate investors.

The problem with this is that many of the most meaningful innovations — the disruptive products, the step-out innovations, the discontinuous changes — have their seeds in very small experiments, rather than large initiatives. As Eric Ries and Steve Blank are so quick to point out, innovation requires iteration. In the process of experimentation and iteration, companies will expose how products and services can come together more effectively. They can develop a better understanding of their value proposition and tailor the business models of innovative offerings before wide-scale launches. Small victories point us in the right direction, and small failures tell us how to change.

But small victories are just that — they’re small. No one notices them initially. They’re generally difficult to explain to investors. They’re often not even statistically significant. So even though small victories are necessary, even though big organizations need small victories (and failures) to get to the large ones, they’re just not interesting to the people who would need to sponsor them.

So the challenge becomes, how can you make your small victories interesting? How can you garner sponsorship but avoid being steered toward experimenting in such a large, public, fashion that failure results in shuttering the innovation effort?

1) Have a grand vision, but a simple plan.
In any situation, getting sponsorship requires the potential to move the organization. What it doesn’t always require is the immediate promise of results. Too often, innovators will try to solicit sponsorship through the promise of a grand vision alone. Executives think they’re buying into that future, and don’t always see the long, arduous path to get there. That’s not the sponsor’s fault.

Innovators hoping to solicit sponsorship and still allow themselves room to pursue small victories need to come forward with a simple way to articulate how their small experiments fit into the larger puzzle. Innovators need a step-by-step plan, in simple language. Playing ‘hide the ball’ does no good for anyone. It simply backs innovators into a corner, forced to pursue the large wins when they’re not quite certain about the opportunity.

2) Don’t pilot, “mini-test.”
When I was at BCG, a mentor of mine used to call small experiments mini-tests. He was adamant that in all materials, we referred to any sort of experimental initiative as mini-tests and nothing else. For years this confused me. Everything we were doing was equivalent to traditional pilot endeavors. We would roll out an experimental system, measure, iterate, and experiment again. But we would never say we were piloting or prototyping anything, we were only mini-testing.

It’s taken me six years and a sustained study of innovation to understand Brian’s genius. By changing the jargon, Brian changed people’s preconceived notions about the test. By mini-testing and not prototyping, releasing betas, or piloting, people didn’t know what to expect. He could experiment and fail and change scale and that was okay.

Managers not only need a simple, manageable plan to get to their grand vision, they also need a way of changing reference points so the types of failures that would normally draw unhelpful attention draw none.

Oh, it also keeps innovators from sticking their feet in their mouths when their hypotheses are wrong. If you end up being incorrect in your assumptions, the small experiments aren’t so public that everyone in the organization realizes it. It adds a bit of humility to the process.

3) Measure, validate, repeat.
Small victories are important in informing innovators how to move forward. But inside of large organizations they’re also vital in getting key stakeholders on board. For intrapreneurs, the information gleaned from small victories can serve as the ammunition for the uphill battle that comes as any group tries to scale a new product inside of a large organization.

The key is understanding what matters to key stakeholders. What information is likely to get them interested in your project? If innovators know what that is, they can experiment, measure results, validate the importance of the initiative, and repeat. That way, when the group tries to scale, it has irrefutable evidence of its importance — protecting the executive sponsor and helping to garner additional sponsors.

These are by no means comprehensive. But hopefully they are helpful.

What do you think? Have any ideas we should include on harnessing the power of small victories inside of large organizations?

via HBR.org http://blogs.hbr.org/cs/2013/01/how_to_innovate_with_an_execut.html?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+harvardbusiness+%28HBR.org%29

How Deloitte Made Learning a Game


“Training is a funny thing,” James Sanders, Manager of Innovation at Deloitte Consulting, told me recently. “No matter how easy you make it to access, or how brilliant the learning programs are, training is simply not the first thing people think of doing when they have some free time. Let’s face it, for most people, on a typical Sunday morning, if given the choice between ‘Am I gonna watch ESPN, or am I gonna do some training?’ training will not win out.”

And yet, by using gamification principles, Deloitte has seen use of its Deloitte Leadership Academy (DLA) training program increase. Participants, who are spending increased amounts of time on the site and completing programs in increasing numbers, show almost addictive behavior. Since the integration of gamification in to Deloitte Leadership Academy, there has been a 37 percent increase in the number of users returning to the site each week.

Gamification takes the essence of games — attributes such as fun, play, transparency, design and competition — and applies these to a range of real-world processes inside an organization, including learning & development. The technology research firm Gartner, Inc. predicts gamification will be used in 25 percent of redesigned business processes by 2015, this will grow to more than a $2.8 billion business by 2016, and 70 percent of Global 2000 businesses will be managing at least one “gamified” application or system by 2014.

Deloitte is well on its way to staying ahead of the trend. DLA is an online program for training its own employees as well as its clients. DLA found that by embedding missions, badges, and leaderboards into a user-friendly platform alongside video lectures, in-depth courses, tests and quizzes, users have become engaged and more likely to complete the online training programs. The Academy has had over 20,000 executive users since its inception in 2008.

DLA uses content from such top tier business schools as Harvard Business Publishing, IMD, Melbourne Business School, and Stanford Graduate School of Business. The content on the site falls into three categories: videos, “in-depth content,” and self-assessments (tests and quizzes). Some are interactive forms and others are PDFs, but all offer a section for learners to interact with each other or to leave questions or comments. To help solidify the community, each learner’s home screen receives news feed updates from the users they follow. They can then interact with each other’s status updates, in a format similar to that on Facebook.

Before learners even begin the online learning programs they must complete their first mission, dubbed the on-boarding mission. They do this by watching a 3-minute video, which explains how to use the website, and in the process of watching the video, they are instructed how to personalize the site to their individual learning priorities. Upon completion, learners receive a badge for their on-boarding mission and then have the option to connect to their personal networks on Linkedin and Twitter so they can easily upload a profile and photo. This level of customization is important, because it breeds a higher level of engagement.

As learners complete each online learning program, they receive a badge to mark their achievement. Most of those badges are won upon completion of straightforward competencies, but some are ‘secret’ badges, dubbed “Snowflake” badges. These are created to surprise and delight learners and are unlocked only by achieving certain goals. For example, if all members of one department watch the same video during the same week, they all receive a snowflake badge. “This is an unpredictable reward, which is a surprise and a delight for our learners,” says Sanders. The average user completes enough online learning programs to earn three badges.

DLA’s design of its leaderboard is also instructive. Instead of displaying one standard list of the top ten scorers overall, each general “level” of user has its own top-ten leaderboard, so that each user’s competition for top-ten is limited to other users on that same level. That board resets every seven days. “Traditional leaderboards are, in fact, counter-productive,” Sanders says. “The same consistent top users, with astronomic scores, turn off everyone who knows they have no chance of beating them.” Instead, with Deloitte’s model, “Every week you have a new chance to be the best learner on the site,” he says. This seven-day reset also means that executives won’t be discouraged from using the site just because they missed a few weeks — and fell behind in scores — while on vacation or traveling for work.”

Getting Started: Using Gamification For Learning & Development

Executives interested in implementing this popular new tool should think of gamification as a business improvement initiative, and start by asking business-related questions such as:

What are your business goals? Define the business problem that gamification is trying to address as clearly as possible. Determine if gamification is something that can contribute to solving this problem or if it will supplement existing plans. Benchmark what your peers in similar organizations are doing with gamification and understand what works and what does not work.

For example, do you want to add gamification for learning as a way to have more learners complete their certifications or compliance programs? Or are you appealing to a growing segment of Millennials who express a desire for learning to be fun, engaging and highly collaborative?

Who is your audience? Will this be directed to internal employees or external stakeholders such as dealers or distributors? Do you want to design prescriptive missions or create more open experiences? View the game from the learner’s point of view. No one wants to perpetually be at the bottom of a leaderboard. Instead demonstrate to users how they can progress toward higher levels of mastery.

The goal is not to “game” or manipulate target audiences, but rather to mesh behavioral science with social technologies to increase collaboration and engagement levels among your users.

How will you track success? Have a plan in place for measuring the effectiveness of your gamification efforts. It’s not enough to capture data; you need to analyze it as well. Some measures to think about include: level of engagement among users, number of power users on the site, learning completion rates among users, satisfaction rates among users and the relationship between engagement and achievement levels on the site and individual promotions, and other external career progressions among your users.

via HBR.org http://blogs.hbr.org/cs/2013/01/how_deloitte_made_learning_a_g.html?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+harvardbusiness+%28HBR.org%29