Want attention? Make a prediction. The past, for most people, is static. It’s disempowering. Nobody likes a historian. And, in general, modern analytics produces artifacts that go to some data gulag. In many ways it’s worse than a museum. At least a museum has curation and it’s an exhibition of some aspect of the past. At least the material is architected to be engaged with and causes enlightenment. As much as the idea of a museum treatment to archival information is attractive from an operations optimization perspective, it’s the wrong direction. We belong to a forward-looking society. Tell me about the future. Predictions are powerful. They set expectations. High expectations are, rightly or wrongly, the fuel of choice for your[…]

In case you missed it, the NYT had a great article on the relationship between lines and complaints. Substituting occupied time with waiting time will increase satisfaction. Reducing uncertainty over the length of the wait will increase satisfaction. Reducing the perception of the length of the line, regardless of actual time spent in line, will increase satisfaction. It’s a great article, and worth the read. *** I’m Christopher Berry.Follow me @cjpberryI blog at christopherberry.ca

Special snowflakes are gleefully shouting ‘told you so’ about social media marketing. So brave. Gartner released their 2012 hype cycle a few days ago. Look at it below: You can see text analytics there, reaching the absolute bottom. Everybody, it seems, these days can say that text analytics sucks. Which is great, because being negative about an entire field is the surest way to demonstrate expertise in an otherwise crowded pack. They’re brave too. Predictive analytics is now mainstream, which is awesome because I no longer need to spend 12 weeks extolling its virtues early in the development cycle. Our good friends: HMTL5, Gamification and Big Data are nearing the peak too. Social analytics, it would seem, is jumping the[…]

This This is neat. What could your clothing tell you about yourself, and others, that you don’t already know? *** I’m Christopher Berry.Follow me @cjpberryI blog at christopherberry.ca

I’m equally skeptical of individual truth and of collective wisdom. We have a tough time, as a group of people, agreeing to what fundamental things mean. Like color. The XKCD color survey is awesome. The data is there and available for secondary analysis. And you’re welcome to it. The summary chart below is beautiful, and, demonstrates the actual variation in labeling between two groups. This case is interesting alone. Different populations look at the exact same thing, and report a different label for it. This variation in opinion can generate problems for a data scientist and a marketing scientist alike. The idea that objective reality exists, and what you see depends on your own bias, shouldn’t be all that tricky[…]

Something pretty neat to share. Check out HN Stats. HN, or Hacker News, is a simple news aggregation site. It features an upvote/downvote system. And, it hasn’t been ruined by becoming popular. It has its days where quality sort of erodes, but at 30 headlines on the front page, chances are good that I’ll find three of the links relevant. That’s a far better hit rate than most of the subreddits I browse. The interface is polished and there are a few design patterns that are unique. We spend so much time staring at the same design patterns that it’s hard to imagine anything else. Sometimes the ideas that help us also trap us. It’s welcomed. Thank you Nafis for[…]

Wired posted a in depth description of the power of the A/B test in April. It’s pretty good. The A/B test is a tactic that has to fit inside a strategic activity structure. The real value in repeated, persistent, A/B testing is the knowledge that you gain. It makes you a better a manager.  It can make the organization stronger.  It leads to really good results if taken over time. But it’s part of a system of management that includes a healthy attitude towards resolving uncertainty using testing. It’s tough to implement because it’s often seen as an attack on somebody’s experience as-a-something. It shouldn’t. *** I’m Christopher Berry.Follow me @cjpberryI blog at christopherberry.ca

It’s polite to let the regular readership know when posting frequency and content is changing. It was done 158 posts ago, on December 31, 2011. I’m doing so again. Thank you for reading, commenting, sharing, conversing and generating data. I’ve been testing a few hypotheses. The data set won’t be complete for another few months until the search returns are complete. There was no optimization objective and it showed. As a result: The posting frequency (and predictability) will decrease.  There will be fewer words to read. There will be more novel ideas curated from other sources. Pandering and Trolling Trolling is the act of forecasting what will likely cause drama or controversy, creating such content, and distributing only for the[…]

This series originally appeared in Eyes on Analytics on April 16, 2012 The City of Edmonton posted a pretty interesting position last month. The description is so good that it bears repeating in this space. Bolding is my emphasis. Traffic Safety Predictive Analyst Put your superior analytical skills to work in North America’s first and only municipal Office of Traffic Safety. You will be joining the rapidly growing field of urban traffic safety where the application of statistics and predictive analysis is becoming a vital decision support tool in reducing motor vehicle collisions.  Your responsibilities will be: Provide short, medium, and long-term predictions of collisions and/or speeding by considering current and historical traffic safety related data as well as other[…]

Tor.com wrote a decent summary about the Norvig-Chomsky debate. I don’t think we have a common understanding of the science, just in general. Proponents of an extreme Norvig perspective say that Chomsky’s ever complicated theories and models are proof that the traditional scientific method has failed, and that machine learning is the future. Those proponents may be misguided by how science works with models. A model is representation. It’s like looking at the shadow produced by an umbrella. It’s a deliberate abstraction so that you can understand some aspect of it. And you can learn a lot about the shadow. Why not just look at the umbrella? An umbrella is extremely complex, and really difficult to analyze if you have[…]