The Haiku of Finance for 02/22/16

Supply chain genius
Unstick every bottleneck
Six Sigma route plan

3 Crucial Skills for US Military Veterans Seeking Corporate Careers

I served in the US Army after my studies at the University of Notre Dame.  Some of my ROTC program classmates stayed on active duty for the long haul, longer than I thought would be sane.  They are now approaching their 20-year service milestones, which means some of them are considering life on the outside.  I have them in mind when I think about the references I used years ago when I started my own transition to civilian life.  The published works available to help military veterans make career transitions could fill a whole library shelf.  Most of that material is general and repetitive.  Hardly any guidance is tailored for someone with a more technical career goal.  Fear not, senior veterans, because Alfidi Capital is here to fill the knowledge gap.  

I have identified three skill sets germane to a large corporate environment.  These skills are portable to any corporation and are particularly useful in very technical fields.  Acquiring them requires mastery of peer-reviewed bodies of knowledge.  These qualifications are vastly more credible with corporate recruiters than any military-specific skills a veteran possesses.

Six Sigma certification is the first skill set that veterans should acquire if they want corporate careers.  Completing a Six Sigma project within the US Department of Defense confers a resume bullet more valuable than experience with real bullets.  The American Society for Quality (ASQ) maintains extensive references on Six Sigma and related topics.  The International Association for Six Sigma Certification (IASSC) lists options for completing the qualifying exams.  Completing the appropriate training and exams is not cheap but is absolutely necessary for official qualification.  

Knowledge management (KM) is the second skill set.  Practitioners become the go-to people when an organization translates the DIKW Pyramid into real operations.  Experts read KMWorld for the latest developments.  The American Productivity and Quality Center (APQC) defines many KM best practices.  The KM business discipline does not yet have a universally recognized body of knowledge and several organizations have emerged with competing certification standards.  I believe that mastering the APQC material through independent study is sufficient at present to claim expertise.  

Operations research (OR) is the final skill set.  The Allied Powers in World War II invented the modern field of OR, and today select US Army officers maintain qualification in the operations research / systems analysis (ORSA) specialty.  The Institute for Operations Research and the Management Sciences (INFORMS) is the US governing body for the OR profession; they have all the resources needed for someone seeking qualification.  

Mastering these skills enables a veteran to compete for corporate jobs that have prerequisites beyond entry-level experience.  Combining them with certification as PMI's Project Management Professional would make a veteran's resume very compelling.  Lacking these hard skills can be a serious handicap.  It is an unfortunate fact of modern life that business skills have diverged far enough from the generalist "soft skills" of military leadership to disqualify many veterans from white collar occupations.  Veterans who wish to avoid confinement to the low-income ghetto of permanent entry-level career paths should master widely accepted business knowledge.  This means hitting the books all over again.  

I recently attended a talk by US Marine Corps combat veteran David Danelo about his book The Return:  A Field Manual for Life After Combat.  The audience at San Francisco's Marines Memorial Club recognized that veterans' passion for a meaningful life should carry over into a civilian career once they leave the military.  Passion hits a brick wall when civilian employers find a veteran's resume devoid of recognizable prerequisites.  Veterans who master the three disciplines above prove they have the passion to carry on as relevant civilians.  

Machine Learning Needs a Common Sense School

I've been hearing from thought leaders all year about how virtualization, machine learning, and M2M traffic are going to solve the enterprise problems that the cloud and Big Data have not yet solved.  That's just great.  Those things sound terrific in sales pitches to prospects in large convention center halls.  I think these thinking machines need to learn some basic vocabulary before they start speaking to us.

MIT's ConceptNet is an attempt at making machines autodidactic.  The difference between humans and AIs is that we carbon-based life forms assemble experiential knowledge into frames of reference called common sense.  Machines have not yet generated common sense because they don't experience the world the way we do, with five senses collecting rich content.  MIT allows humans to input their own interpretations of common sense into the Open Mind Common Sense Project that feeds ConceptNet.  

Contextual knowledge is good and adaptive thinking from experience is even better.  That's what makes us human.  The thing that makes us most human is our ability to reason morally.  Humans can discover and apply first principles from a variety of philosophical traditions even if those traditions are irreconcilable.  Machines can't do that yet, but giving them the ability to reason adaptively from common sense carries the risk they they will make uncontrolled decisions.  The Laws of Robotics are more useful now than ever as a moral foundation for machine learning.  

AIs can generate the data used in social network analysis but I do not believe they can actually perform the final analysis themselves.  Human analysts must complete the task.  I have blogged before that high-level strategic decisions must be left to humans and cannot be automated away with decision management rules.  Introducing AIs into routine operations is good for business if humans update the heuristics and rule engines that circumscribe their operations.  Humans need training in knowledge management, decision management, Six Sigma, and project management before they launch AIs.  Those AIs need diplomas from machine learning schools with common sense as the core curriculum.  Train the humans first so they know how to govern the machines.  Program the thinking machines with the Laws of Robotics before they begin their machine learning.