Tuesday, January 27, 2009
Blue Ocean Strategy in Web 2.0
From the article:
38. Design your product to build a strong network effect. The concept of the network effect is something I've covered here extensively before and it's one of the most important items in this list. At their most basic, Web 2.0 applications are successful because they explicitly leverage network effects successfully. This is the underlying reason why most of the leading Internet companies got so big, so fast. Measuring network effects and driving them remains one of the most poorly understood yet critical aspects of competing successfully online. The short version: It's extremely hard to fight an established network effect (particularly because research has shown them to be highly exponential). Instead, find a class of data or a blue ocean market segment for your product and its data to serve.
http://web2.socialcomputingmagazine.com/50_essential_strategies_for_creating_a_successful_web_20_pr.htm
Sunday, January 18, 2009
Takeaways from Barry et al (2006)
Second dimension: "whether the service must be produced and consumed simultaneously: - services can be produced and consumed on the internet anytime or anywhere
Market-Creating Innovations: A scalable business model, comprehensive customer experience management, investment in employee performance, continuous operational innovation, brand differentiation, an innovation champion, a superior customer benefit, affordability, continuous strategic innnovation
Takeaways from Kim and Mauborgne (2004)
In blue oceans, demand is created rather than fought over. There is ample opportunity for growth that is both profitable and rapid.
Red ocean | Blue ocean
Compete in existing market space | Create uncontested market space
Beat the competiton | Make the competition irrelevant
Exploit existing demand | Create and capture new demand
Make the value cost trade off | Break the value cost tradeoff
Align the whole system of a company's activities with its strategic choice of differentiation or low cost | Align the whole system of a company's activities in pursuit of differentiation and low cost
Friday, January 16, 2009
10 Info Viz Projects for inspiration
Scraped blogs for sentences that start with “I feel” and shows aggregate metrics - http://www.ted.com/index.php/talks/jonathan_harris_tells_the_web_s_secret_stories.html
http://wefeelfine.org
3-D graphs of astronomy
http://www.ted.com/index.php/talks/george_smoot_on_the_design_of_the_universe.html
Last.fm listening history
http://www.leebyron.com/what/lastfm/
Who’s Buying What? (Good Magazine)
http://awesome.goodmagazine.com/transparency/014/014-buying-whos-buying-what.html
Edits to openstreetmap.org
http://www.vimeo.com/2598878
Facebook friend networks
http://www.visualcomplexity.com/vc/project.cfm?id=639
Visualization of personality characteristics (quiz takes 10 minutes, registration)
http://beta.signalpatterns.com/personality_survey
Social network analysis
http://www.fas-research.com/visualizations.shtml
Digg Labs (Swarm) -
http://labs.digg.com/swarm
TweetWheel
http://www.visualcomplexity.com/vc/project.cfm?id=587
Tuesday, January 13, 2009
BIT 678 - IT-Mediated Service Observation
Monday, January 12, 2009
Takeaways from Leonard (1997)
Observers saw people combining beepers and cell phones not to answer calls but to screen them.
Empathic design techniques can't replace market research; rather, they contribute to the flow of ideas that need further testing.
Learning from observation: triggers of use, interactions with the user's life, User customization, intangible invisible product assets, unarticulated user needs
Step 1: Observation - Step 2: capturing data media types - Step 3: Reflection and analysis, Step 4: Brainstorming for Solutions, Step 5: Developing Prototypes of Possible solutions
Takeaways from Thomke (2003)
Evaluate Ideas --> Plan and Design --> Implement --> Test --> Recommend
Learning through Experiements: Factor / Definition
Fidelity = The degree to which a model and its testing conditions represent a final product, process, or service under conditions of actual use
Cost = The total cost of designing, building, running, and analyzing an experiment, including expenses for prototypes, laboratory use, and so on.
Iteration time = The time from the initial planning of an experiment to when the analyzed results are available and used for planning another iteration
Capacity = The number of experiments that can be carried out with some fidelity during a given time period.
Sequence = The extent to which experiments are run in parallel or series
Signal to noise ratio = The extent to which the variable of interest is obscured by other variables.
Type = The degree to which a variable is manipulated from incremental change to radical change.
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In a lab, expeirments are routinely undertaken with the expectation that they'll fail but still produce value. In the real world, there is pressure to avoid failure.
Takeaways from Melville et al
Development - ideation and visualization - concept development, and iteration and refinement. tangible representation. "the goal of prototyping isn't to finish. it is to learn about the strengths and weaknesses of the diea and o identify new directions that further prototypes might take." - tim brown ideo
Implementation - final prototype, business case, pilot, launch