Increasing Jointness and Reducing Duplication in DoD Intelligence

Today I’m publishing an important guest-essay, with a brief introduction.  Last month the Wall Street Journal published a 12-part online series about college graduates and their paths to success, featuring surveys and input from job recruiters. One thing caught my eye, at least when blogged by an acquaintance, Prof. Kristan Wheaton of the Mercyhurst College Institute Of Intelligence Studies. The WSJ’s study included a look at recent graduates’ job satisfaction in their new careers, and as Prof. Wheaton strikingly put it in his own blogpost:

“Intelligence Analysts are Insanely Happy.” 

I’m pretty sure that’s not really true by and large; Prof. Wheaton seems slightly dubious as well. Many readers of this blog are intelligence analysts themselves, so I’d love to hear from you (in comments or email) about your degree of giddyness….

We all know that the intelligence-analysis field as currently practiced in U.S. agencies bears many burdens weighing heavily on job satisfaction, and unfortunately weighing on successful performance.  Our youngest and our most experienced intelligence analysts have been battling those burdens. 

One analyst has now put constructive thoughts on paper, most immediately in response to a call by Defense Secretary Bob Gates asking DoD military and civilian employees to submit their ideas to save money, avoid cost, reduce cycle time and increase the agility of the department (see more about the challenge here).  

Gunning the Microsoft Semantic Engine

New Bing Maps Beta with embedded data layers from Twitter and other social feeds, click to enlarge screenshot

There’s a lot of information on the Internet already. Every day, more is added – a lot more. And while there are a concomitant number of new analytic or sense-making tools on the web, they butt up against the fact that the data – the all-important data – is held in multiple places, formats, and platforms.

How are we going to deal with all this? One approach is almost mechanical: ensuring that datasets can be accessed commonly, as in our new Microsoft Dallas platform associated with the Windows Azure cloud platform.  In the government realm, the anticipated reliance on “government-as-a-platform” (a meme popularized by Tim O’Reilly) holds promise in allowing somewhat aggregated datasets, openly accessible.