The New York Times is featuring a rather empty article about data in retail whose thrust is basically more data = more opportunity. Uh yeah. The trend I am seeing with retailers — and my visibility here is more limited than it used to be — is an analytics or CRM vendor sells a retailer a data package that is tailored just enough for the purchase to make sense to the company’s executive but the package isn’t tailored enough to yield any intelligence to make better decisions. The mid-level users that need the intel are left saying WTF? That is an old management pattern but seeing it happen hurts my insides because the opportunity is really amazing but is being fumbled so badly. Creating a data-driven culture has to start with the analysts. Hopefully they know what to ask for.
Maud Newton references Richard Brody on the centrality of the director in Cahiers Du Cinema versus the centrality of the author in the Paris Review interviews of the same period.
Brody observes that “portable” recording devices (which weighed about nine pounds then) made these conversations possible, and wonders about the effect of technology on our “expectations for information and aesthetics” generally.
The expectations-for-information-and-aesthetics bit caught my attention. As we have said here before on Datachondria new forms of technology are linked to new forms of criticism. The supercut is only one such example. Now if only we could learn how to use these tools we would be laughing.
In this blog, I write about the world of online music discovery and recommendation. I look at the tools available to help people find music. I examine some of the issues that can make music recommendations go bad. I also write about things that I find generally interesting including programming, data visualization, playing games, and (of course) music.
At the first MESH conference, Chris Messina was enthusiastic about the future of the browser. Page, page, back button, address bar, page, bookmark, page. Surely we could do better? The shuffling paper metaphor needed to go.
Every since hearing Chris, I have been keen on seeing the browser evolve. In the embedded video, the folks at Adaptive Path put forward one possible iteration — the browser as data manipulator.
Frank Jacobs is publishing Strange Maps next month. Here is a sample of the data goodness inside: From anywhere in America it is Only 145 Miles to the nearest MacDonalds Restaurant
In unconnected, but related news I discovered the recently acquired Mint.com has been creating data visualizations as well. Surprisingly some topics are kind of fun.
This week’s On The Media points to a story at MotherJones.com by David Goodman about the US military’s recruitment practices. Apparently George Bush’s 2001 ‘No Child Left Behind’ legislation mandates that all high schools send students’ personal information — including address, cell phone number, GPA, and social security number — to the military for data mining. It turns out the Pentagon — not as I would have thought MySpace of Facebook — has the largest repository of personal information on 16-24 year olds in the United States. Apparently it is illegal to recruit high school students into the military so the data mining allows the military to queue up potential converts the moment they graduate.
Let the algorithm manage 80% of the inventory. Let the exception reporting manage the rest. That was the mantra of a whole office of consultants and wiz kids working on a retail supply-chain project from a few years ago. The mantra was grand but the formulas were junk. The algorithms were inherited from other business sectors. When applied to a product that didn’t sell in predictable ways all they did was suppress over-ordering. And exceptions weren’t exceptions at all because they were void of actual information.
The failure in that case wasn’t in the algorithm and it is wasn’t with the consultants and wiz kids. The failure was in the business. No one in the company — quite possibly the whole industry — new good data from bad data. It wasn’t anything anyone thought about.
Thinking back it would have be better to take a human-centred data approach by asking the inventory managers what decisions they were likely to make and what data was likely to change their mind about those decisions. Now that would have been a worthhile starting point. A little data innovation would have went along way. In fact it would have been revolutionary.
As Chris Dixon points out in a recent blog post “breakthroughs come from identifying or creating new sources of data, not inventing new algorithms.”
I wonder how many data-innovation teams are out there in the business world. Probably not many that are off wall street.
It is well documented out there that Linked-In is the Hotel California of the Internet — you can leave but they won’t delete your account. I won’t sign up for
Trent Reznor's Twitter Account is Really Gone. Mine Isn't
Linked-In for that reason but the funny thing is I am having the same problem with Twitter. When I first signed up I had a choice-three-letter username. After some experimentation — and some debate about whether to use my longish full name — I adopted a five letter username that I have kept ever since. When Twitter got really popular this past Winter I thought I should surrender my first username to someone that would want it. I deleted my account. The user info never went away. Most vexing of all — I continue to get follow notifications as spammers follow my dormant account and I can’t log on to change the email settings because the account officially doesn’t exist.
When you have a physical device that is representing a single piece of data, you get to do away with the user interface. The key word for Ambient Devices is “glance-able.”
