Thursday, April 17, 2014

How To Get An Intel Job Using LinkedIn

Most job seekers are very familiar with job related search engines such as Monster or Indeed or, among intel professionals, sites such as USAJobs.  One of the most effective and efficient websites for finding a job, however, is LinkedIn, and it is surprising how many job hunters fail to take advantage of its powerful tools for searching and applying for intel related jobs.

There are, of course, some legitimate security concerns among some sectors of the intelligence profession regarding social media sites like LinkedIn.  However, for the vast majority of job seekers - particularly entry-level job seekers and particularly for those interested in intelligence in business positions - LinkedIn is a must-use site.

Much of the power of LinkedIn comes from the size of an individual's network.  The larger and more diverse the network, the better the results.  Thus, the first step for individuals trying to break into intelligence is to build a network.  The time to do this is not three months before graduation, however.  

Intelligence professionals are a cautious bunch and are highly unlikely to take kindly to spam-y requests to connect from unknown or unverified contacts.  A far better avenue is to start early in your academic career and to build contacts slowly.  Start with professors, alumni or others you know who are already in the business or already have contacts with intelligence professionals.  Join organizations such as the SCIP and IACA.  But don't just join them - become as active in your local chapter as you can.

Within LinkedIn, try to identify some specialty groups where active discussions take place in an area of the intelligence field in which you are interested.  There are a number of these groups and joining them, listening to others discuss the issues of the day and, eventually, contributing to them with cogent, well-thought out observations of your own is a good way to steadily build a reputation within the community.

All this is the undercard, however, to the main event:  The LinkedIn job search feature.

At the top of every LinkedIn page is a Jobs Link.  Clicking on that link takes you to a jobs page with a number of interesting sections.  First is the Jobs You May be Interested In section.  Here, based on your profile, LinkedIn tries to guess which jobs might be right for you.  

LinkedIn also looks for commonalities among employers within your network (under the premise, perhaps, that if all your professional contacts work for Company X, you might be interested in a job there as well) and offers job recommendations along those lines in its Discover Jobs in Your Network section.  If your network is still small (and it may well be if you are looking for an entry level job), this latter section may not be much help.

You can also search for jobs in the search box near the top of the page but this search box defaults to a local search.  If you live in a small town, such a narrow area search is unlikely to reveal many intelligence related jobs.

However, the search bar that always sits at the very top of the page allows you to easily conduct national level searches for jobs.  Getting good results typically depends on which search terms you use (a more difficult question in the world of intelligence in business...) but a good starting place is simply "intelligence analyst".

LinkedIn will typically generate a number of jobs from this kind of search.  If it generates too many or the search needs to be otherwise focused, you can use the filters found on the left hand side of the page.  Two of the most useful are Experience and Relationships.  Experience is easy to understand and LinkedIn helpfully tells you how many jobs there are currently within each experience level.  For example, in the screenshot on the left (taken from my profile), you can see LinkedIn found 127 entry-level jobs.  

The Relationships filter helps you understand who you know that works at the same company or organization as the job advertised.  For example, I have a first level connection to 351 individuals at companies or organizations who are currently offering intelligence analyst jobs.  Knowing that someone in your network works at a company you are considering is very helpful.  You can ping them for insights about what it is like to work at that company or, if they know you well (not always true on social networks like LinkedIn), they might be able to refer you within their own system, giving you somewhat of an edge in the hiring process.

The Job Profile itself offers similar information.  First, a simple click on the People In Your Network link (if any) will let you know who you know who works at a given company or organization.  It will also give you insight into the second level contacts to which you might be able to be introduced. More importantly, perhaps, for entry-level job seekers with smaller networks is the link to Similar Jobs.

Finally, once you have selected a job of interest, be sure to look for the Apply Now button.  This allows you to apply for the job directly through LinkedIn.  Otherwise, you typically have to apply on the company's website.  A final hint is to check LinkedIn jobs often.  In the two days it has taken me to write this post, I have seen a number of jobs pop up and disappear.

This is just a start, however.  There are any number of other tips and tricks to using LinkedIn to get a job.  If you know any, please leave a comment!

Monday, April 14, 2014

Forecasting Recessions: Economists' Record Of Failure "Unblemished"

"All my economist's say, 'On the one hand or the other.'  What I need is a one-handed economist!" -- Harry Truman.

Sorry, Harry, apparently even that won't help.

A new study out the Centre for Economic Policy Research in the UK indicates that, for the last thirty years at least, "the record of failure to predict recessions is virtually unblemished."


Take a look at the chart to the right.  It is a little hard to interpret but it starts about 2 years prior to the onset of an average of all the recessions over the last 20 years.  The top blue line represents the "normal" evolution of forecasts regarding GDP growth, that is, in a non-recessionary environment.  On average this is about 3% per year across all of the countries studied.

The forecasts from economists - the red bars - start out pretty close to this norm but begin to drop below the norm at the 8-10 month point.  While, on average, the forecasts continue to decline over the year preceding a recession, they still miss the mark (albeit slightly) even at the end of the year.  In other words, they get less wrong by the end of the year but they are still all - as in all - wrong.  The authors indicate that this paper replicates the results found by a 1990's paper that looked at the same effect over an earlier time period.  The effect is even worse when looking at recessions that develop after banking crises.
Note:  The bottom blue line which shows the actual average GDP growth is positive because, as the authors point out:  "on average, growth is not negative during recessions in advanced economies because the dating of recession episodes is based on the quarterly data and annual growth tends to remains positive during many recessions."  'Nuff said.
The authors also add that there are three schools of thought about why these forecasts are so uniformly incorrect:  Economists don't have enough information, don't have the incentive or aren't good enough Bayesians (i.e. hold on to their priors too long) to make accurate forecasts.  The jury is still out with regard to the actual reason but the effect seems like the kind of thing an intel analyst would want to account for when using macroeconomic forecasts in other than business analyses.

(Tip of the Hat to Allen T. for the link!)

Friday, April 11, 2014

Another First For Mercyhurst! School Of Intelligence Studies and Information Sciences Announced Today!

Tom Ridge, Former PA Governor and first Secretary of Homeland
Security, speaks at the opening of the School of Intelligence
Studies and Information Sciences
Today, Mercyhurst University announced that the Department of Intelligence Studies would be merged with the Department of Math and Computer Science and the Department of Communications to form the seventh school within the University:  The Tom Ridge School of Intelligence Studies and Information Sciences.

Named after former Pennsylvania governor and first Secretary of Homeland Security, Tom Ridge, the new school takes its place among more traditional schools such as the School of Social Sciences and the School of Business...

(Sounds like a damn press release.   If your readers wanted that, they should go here.  You should give them a feel for what this really means...)

This is a big deal.  A really big deal.

In the first place, there is no other University in the country (perhaps in the world) that has a school dedicated to a vision of Intelligence Studies as an applied discipline, that teaches students how to get intelligence done and not just how to talk about it.

Secondly, it is going to allow us to grow our programs exponentially.  First up is a new and complementary masters degree that will focus on data analytics - so-called "big data". My own hope is that we will soon begin to offer a doctorate - but not a PhD - in Applied Intelligence.  I don't know what the new Dean of the School, Dr. Jim Breckenridge, wants it to look like, but I want it to be a professional doctorate, like an MD or a JD, that will focus not only on intelligence analysis but also on the special challenges of leading and managing the intelligence enterprise.

Third, it validates the vision of Bob Heibel, the founder of the Mercyhurst program.  Twenty-two years ago, long before 911, before even the first World Trade Center bombing in 1993, Bob had the radical idea that academia could do a pretty good job educating the next generation of intelligence analysts.  Almost 1000 students have graduated from our residential, online degree, or certificate programs since then.  These alumni are today employed throughout the national security, business and law enforcement intelligence communities.

Governor Ridge said today that the nation owes a debt of gratitude to Bob for what he has contributed to the safety and security of the US and, through our international students, of the world.  It is a testament to what one person can do when he really believes in something.

Wednesday, April 9, 2014

Help! Where Can I Find A Job?? (RFI)

I am in the process of updating and compiling my list of job resources for entry-level intelligence analysts and I could use your help!  

If you  know of any good websites or resources, please either send them to me (kwheaton at mercyhurst dot edu) or post them in the comments below.  

What kind of links am I looking for?

  • Job links for entry-level intelligence analysts.  If you know of a company or organization that has intelligence analyst jobs on the books that can be filled by an entry-level analyst, send a link.
  • Job links for intelligence analyst-like positions.  Lots of positions within the private sector (such as anti-money laundering positions with most banks) are good fits for entry-level intelligence analysts but they are rarely easy to find through straightforward job searches.  
  • Job links for international positions (for nationals and expatriates).  There doesn't appear to be a good list of job resources for individuals with intelligence analyst skills who want to work outside their native country.  Likewise, expatriates often having a hard time finding intelligence-like jobs in foreign countries.
  • Job links for Non-Governmental Organizations.  NGO's rarely if ever title analyst positions as "intelligence" positions, yet the intelligence analyst skill set is often the best fit.

Beyond job boards or specialist search sites, what else can you provide?  Job preparation resources.  Getting a job in any intelligence position in challenging.  Any hints or tips that are particularly relevant to the intel job search would be appreciated.  What kind of stuff am I talking about?

  • Interview skills
  • Resumes
  • Social Media Usage/Presence (LinkedIn in particular)
  • Job Fairs
  • Hints and tips for breaking in
Once I get everything compiled, I will post the list here!

Monday, April 7, 2014

Want To Invest In People Instead Of Companies? Now You Can! (Entrepreneurial Intelligence)

Crowdfunding is a busy place these days.  While the largest and most popular site, Kickstarter, continues to fund a variety of creative projects (last year Kickstarter funded more creative projects than the National Endowment for the Arts...), specialty crowdfunding platforms are now available for everything from education to issues in the developing world to scientific research to, of course, porn.

For me, understanding crowdfunding is becoming an increasingly important part of what I call "entrepreneurial intelligence" - or, stuff that is outside entrepreneurs' control but is still critical to their success or failure.  Crowdfunding is rapidly filling a space left untouched by bootstrapping, angel investors and venture capitalists and understanding the strengths and weaknesses of various crowdfunding platforms would seem to me to be a critical intelligence requirement for entrepreneurs.

One of the most interesting of the new crowdfunding platforms is Upstart.  Upstart allows you to invest directly in a person.  In other words, you give them some money now to pay off a loan or to learn to code or to expand a business, and they promise to pay you a small percentage of their income over the next 5-10 years.  Repayments are capped (typically at 3 to 5 times the amount invested) so people can pay off their backers early if they make a lot of money.


Like a venture capitalist or angel investor, you could lose all of your money if the person you backed doesn't make enough.  Upstart uses statistical models to predict how much the "upstart" will earn over the next ten years based on degree, school attended, test scores, number of job offers, work experience, etc.  The amount the upstart can ask from backers is based on this model but as Upstart notes:  "Any estimate of returns is highly speculative, subject to a high degree of variability, and not based on historical experience. The pricing engine is novel and untested and relies on broad-based statistical data that may not be representative of any individual’s actual future income."

This is, however, a pretty good deal for investors if everything works out as planned.  A $300 return on a $100 investment over 5 years represents a nearly 25% annual rate of return.  Sure beats the 2 bucks your average money market fund will likely yield over the same period...