Geographical Perspectives - A Geographer's Thoughts on Business, Real Estate, and Education.

GAAS Presentation Available

As I mentioned in a previous blog post I was in Chicago last week attending the Global Automotive Aftermarket Symposium and had the opportunity to deliver a talk on the Inventory Optimization Process in the Aftermarket.

It was my first presentation to a large audience and I think it went pretty well. It was certainly a great opportunity for me and I learned a lot more about the Aftermarket during the 2-day symposium. Hopefully I’ll have more chances to speak at these types of events.

If you’re interested, you can listen to an audio recording of my presentation.

Before you begin listening you might want to download my presentation so you can follow along with the graphics that I refer to during the talk.

I’d be grateful for any feedback on my presentation, the content, my delivery, etc. I know there’s plenty of room for improvement so don’t be shy about sharing constructive criticism.

Thanks!

Speaking this week at the Global Automotive Aftermarket Symposium

I’ll be speaking at the Global Automotive Aftermarket Symposium (GAAS) in Chicago this Thursday. It’s an exciting opportunity to share some of the geographic data analysis approaches we’ve (TerraSeer) been using to help manufacturers and retailers forecast demand and make inventory assortment decisions. Here’s a downloadable brochure with more information about the conference.

Hopefully this speaking engagement will lead to more opportunities to introduce geospatial analytics to the manufacturing sector and the automotive aftermarket in particular. If you happen to be in Chicago-land stop by the Hyatt Regency near O’Hare and check it out!

I will try to share some thoughts during the conference so follow me on Twitter if you’re interested.

Spatial Career Guide is now Required Reading at USC

I was mentioned on Twitter because my post on GIS Software Developer career preparation as part of the Spatial Career series is now required reading for a graduate level GIS class at the University of Southern California. I thought this was pretty cool. I think my PhD advisor was hoping my contribution to the discipline would involve research published in journal articles …. but I’ll take what I can get.

Spatial Career Guide – Spatial Statistician

This is my fifth post in the Spatial Career series. In previous posts I’ve written about how to prepare for a career as a GIS Software Developer, as a Geospatial Analyst, as a Cartography/Visualization Specialist, and as a Geographic Information Scientist. In this post I will describe how to prepare for a career as a Spatial Statistician. This career path is similar to the GIScience path in that it’s as critical for you to want to be a statistician as it is for you to want to work with geographical data. So this guide might be reasonably helpful for anyone interested in a career as a statistician (but you’ll want to substitute specifics from the relevant application area and/or data universe, i.e., instead of geographic/spatial you’ll have to find out about the nuances in health, financial, etc). So, here are 5 steps that should put you in good position for a career as a spatial statistician.

Step 1. Get an advanced degree. I would say for this path you really should get at least a Master’s degree and a Ph.D wouldn’t hurt. In fact, one nice thing about the statistician route is that a Ph.D can open up options in private industry as well as in government and academics. Businesses aren’t afraid to hire a Ph.D type for a quantitative position whereas in other roles they will shy away from a Ph.D. So this could be a good option for someone who has a PhD but no longer wants to pursue an academic career. Also, this is another career path where you might consider at least one degree in a field other than geography. Unfortunately the market place is such that people won’t value your degree in geography in terms of the quantitative preparation you would’ve received in school. So I think you have to round out your training, ideally with a degree in math or statistics. There are several combinations that would work. A bachelor’s in math or statistics with a Master’s in Geography would work. A bachelors’ in geography and a Master’s in statistics would probably be better (you would want to minor in math or at least take a full set of courses in Calculus and Linear Algebra as an undergrad). Or, you might consider a joint Master’s in both geography and statistics. This would require some administrative effort and more time but it would be a nice combination and open a lot of doors.

Step 2. Become an expert in spatial analysis methods. Unfortunately, it’s fairly difficult to acquire this type of training. Most geography programs have a few offerings and one or two people on the faculty with appropriate expertise but most programs don’t have enough depth in this area, at least not in my opinion. There are a handful of programs that come to mind where you’ll get all the spatial analysis training you could want and more but they are few and far between. Top on my list is Ohio State because you might get a chance to study with Noel Cressie, who is pretty much the godfather of spatial statistics. He is in the Statistics department where they offer a special program in Spatial/Environmental Statistics but I suspect there are solid ties to Ohio State’s outstanding geography department. Other key programs (and key people) to consider would include UC Santa Barbara (Michael Goodchild), Arizona State (Luc Anselin) and SUNY Buffalo (Peter Rogerson). Each of these programs has a number of talented faculty and an Associate Professor might make a better advisor since they’re a bit less likely to be globe-trotting than the super stars. If you’re Canadian or interested in studying in Canada, take a look at Ryerson University – they offer a good applied graduate program in Spatial Analysis. If you’re in the UK, check out the University of Leeds. There are probably others that I’m leaving out. Feel free to suggest others in the comments section below.

Step 3. Learn the most popular statistical software programs. I would try to obtain some exposure to all of the top statistical software tools including SAS, SPSS and R. The more the merrier. Add Stata and Minitab and others if you can and you might check out free trials of newer technologies like Alteryx. You’ll probably have one go-to tool that you like best but you don’t want to forfeit a job opportunity just because you aren’t familiar with the software the target organization has already licensed. Spend enough time to feel comfortable doing basic analysis in a few different statistical computing environments. You need to be able to get past the gatekeepers in Human Resources who might toss out your resume if it doesn’t have the right buzzwords listed. Also, learn how to automate tasks in these computing environments. Let a scripting language allow you to reproduce results at a click of the button. You don’t need to take hard-core computer sciences classes, not that it would hurt, but some basic programming concepts will certainly help.

Step 4. Learn to communicate effectively. Read bullets 3 and 4 in the GIS Software Developer post and read the Cartography/Visualization specialist post. Being a statistics nerd is cool but don’t be a statistics nerd who can’t communicate with real people. Try to explain things so that a sophomore in high school would be able to understand what you’re saying. And, try to be really good at data visualization. The ability to communicate through visualization, narrative and anecdote is what will set you apart from just the regular statistician who writes equations on the white board when asked to present something to a non-mathematical audience. Instead, help your organization and your clients visualize their data in a way that leads to better understanding and collaboration. For more on this read my post on Geospatial Visualization in Business.

Step 5. Get some applied experience. You will learn a ton of great stuff from your statistics professors and other faculty. They will be able to teach you all about theory and methods. But, when it comes to applying these methods you will want to find a practitioner who has been forced to deliver answers to difficult questions with messy data under tight time constraints (think days or weeks instead of months or years). The rare professor will be good at both but don’t count on such luck. Instead, plan to volunteer to do data entry or whatever you have to do in exchange for the opportunity to interact and learn from statisticians who work on applied problems. Building statistical models that work well doesn’t involve particularly elegant mathematics, at least not in my experience. You have to be able to use a bit of “art” to get some models to work. This doesn’t make the model less useful, it will do the opposite if you do it well, but it won’t be something you can publish in an academic journal and most of your professors won’t like it. You have my permission to ignore them (unless you need their signature on your dissertation or want tenure). Learning how to do a bit of brute force modeling is a great skill to add to your tool belt. It just might allow you to actually suggest a real solution to a thorny problem. And that’s what brings in the big bucks and for some, if you’re like me, the big fun.

The opportunities in statistics/analytics are huge. If you haven’t heard the term “Big Data” by now you’ve been hiding under a rock. Use of the term Big Data may be a passing phase but a world in which all organizations are trying to make sense of enormous volumes of data has just begun with no end in sight.

Spatial Career Guide – Geographic Information Scientist

This is my fourth post in the Spatial Career series. In previous posts I’ve written about how to prepare for a career as a GIS Software Developer, as a Geospatial Analyst, and as a Cartography/Visualization Specialist. In this post I will describe how to prepare for a career as a Geographic Information Scientist.

The most important word in this job title is “Scientist”. If you love GIS and maps and geography that doesn’t mean you will love being a scientist. The most successful GIScience people are scientific researchers who happen to be interested in geographic data. So, you should love the idea of doing science as much as or more so than gazing at maps and other representations of spatial data. It also means you should be pretty good at math, an excellent technical writer and a voraciously curious investigator (so much so that you’re willing to spend hour after hour combing through volumes of scientific literature). Beyond that, you have to be highly specialized in a particular thread of scientific inquiry. You might be interested in computational methods or cognitive science. Or, you might specialize in a particular physical science or social science discipline and focus your efforts on developing new spatial methods that will allow researchers in the discipline to pose and answer new questions.

As a scientist you are most likely to find a job in government or in academics. You can find opportunities in the private sector, and the opportunities here may grow, but they are often tied to the same sources of grant funding or they involve collaboration with government/academic scientists and you’ll be judged by similar criteria as you advance within your organization. In any case, unless you become an entrepreneur (which could be a great way to go if you have the right combination of skills – probably worthy of a separate blog post), you’ll be working on building a CV (rather than a resume) and you’ll want to publish as much as possible.

I think the best way to provide guidance for this path is to study a bit about current GIS-oriented scientists who are successful in the field. Hopefully this will help illustrate some of the options available as well as some of the common threads. So, I would encourage you to learn as much as possible about top GIS scientists. Here are a few key players that come to mind for me along with links to their web pages. This isn’t meant to be comprehensive or a ranking or anything (names are listed in alphabetical order). This is simply meant to get you started.

For a more complete list of top GIScientists, take a look at the program committee for the upcoming GIScience 2012 conference. Find their CVs and read about what they studied, where they earned their PhDs, what positions they’ve held and what they’ve published. This will paint a picture and provide a set of possible road maps.

After reading about some of these successful scientists, you might note that they fall into a few different categories. You’ll want to learn about the different topics of interest within GIScience. Here’s a quote from the GIScience.org website describing the vast array of topics:

“GIScience brings together leading researchers from all disciplines to reflect the wide spectrum of scientific research areas such as cognitive science, computer science, engineering, geography, information science, mathematics, philosophy, psychology, social science, environmental sciences, and statistics.”

So what should you do as an undergrad to prepare for a career in Geographic Information Science? Well, this may not go over well with some of my fellow geographers, but I would recommend majoring in something other than geography as an undergrad and then plan to study geography in graduate school. So if you want to become a computational scientist focused on geoinformatics you should probably study computer science as an undergrad. If you’re going to focus on quantitative methods you should consider a major in mathematics or statistics. For cognitive science, perhaps you would want to major in psychology or neuroscience. If you want to follow a path like Dawn Wright, study oceanography or another earth science so you can blend an understanding of that science with GIS-related methodologies. And so on and so forth. If there is a geography department on campus I would certainly take a few courses in geography. Rather than recommend a particular subject I would try to find out who the best geography faculty are at your college/university and take whatever they are teaching. You might take an intro class and then one or two higher level courses. Or, if you’re ambitious, just ask the professor if you can register for an advanced course without the prerequisites. In advance, simply purchase the intro level textbooks and read them. Wow, what a concept – reading the material instead of listening to a set of lectures! Should save both time and money.

If you’re going to be a scientist you should plan now to attend graduate school for at least a Master’s degree and probably a PhD. For graduate school, you should choose first and foremost an advisor that does the kind of science you want to do. If that advisor is housed in a department of geography, you’ll learn all the geography you need to know. In fact, not having been taught geography as an undergrad may work to your advantage. My advisor told me that he was happy that I didn’t need to “unlearn” some concepts that are frequently taught but confusing or misleading. Furthermore, if you come to grad school with a degree in a different scientific discipline you’ll have a unique perspective that may provide an advantage when it comes time to select a research focus. Often the most fertile ground for new discovery is found at the intersection of multiple fields.

I suppose that this post is a bit less concrete than previous career-related pieces I’ve written. If you’re somewhat undecided about what to study as an undergrad but want to pursue this path and need something more specific, then here’s a recipe that should work for most:

1. Major in mathematics, computer science or physics. These majors are available at almost all universities and will provide solid quantitative training and a good base to build from regardless of your career trajectory. If you’re not interested in any of these subjects you may not be interested in a career in GIScience either.

2. Volunteer to help a professor with a research project or sign up for independent study and do your own project. Ideally, the result would be a research paper. If it’s really good, maybe submit to a journal for publication. If you get published while an undergrad you’re a slam dunk for grad school admission. The project doesn’t necessarily need to be a GIScience topic with a GIScience professor. The idea is to see if you like doing research. Same with #3 below.

3. Attend an academic/scientific conference. Even if you don’t present work, this is a good idea because it will expose you to an important part of academic life (and the “unique” social behavior of academic types). Better yet, take your research from step #2 above and present your work. Learning how to do a presentation will end up being more valuable than any single class you’ll take in college. And, don’t worry about not being an expert. Just talk about what you know and make your presentation easy to understand. I’ve seen a lot of presentations by people who are clearly intelligent but can’t manage to make their findings coherent or comprehensible. I’ve also seen a few presentations that were a disaster in all possible ways. No one humiliates these presenters and no one will humiliate you either. Gain experience early in this important arena.

4. Talk to Assistant Professors about what it’s like to become a scientist and/or an academic. Read books like a A PhD Is Not Enoughand Getting What You Came Forand other similar books. Becoming a scientist is a huge time commitment. Go in with your eyes open and be prepared for a long haul. You won’t be able to sustain the momentum necessary to charge through the PhD let alone tenure review if you don’t have some love in your heart for science and academics. Find out the real scoop. It may not be as glamorous as you think. Or maybe it’s better than you thought possible.

5. Have fun and take some classes that you’ll enjoy even if they won’t add to your scientific credentials. You’re going to be in school for a long time and you won’t make much money for several years so lighten up. Be a fun, happy scientist who loves their work and enjoys the process of discovering and sharing knowledge. Try not to be an arrogant pain-in-the-ass scientist who takes themselves too seriously and craves recognition and respect above all else. I’ve seen both types and, believe me, you want to be the former.

I hope this helps. GIScience is gaining in importance and I don’t see that trend changing anytime soon. If you dream of a tenure track professorship at a major university, I think this is probably your best bet within the discipline of geography.

Spatial Career Guide – Cartography and Visualization Specialist

This is my third post in the Spatial Career series. I’ve covered GIS Software Developer and Geospatial Analyst and in this post I will provide guidance to the aspiring cartographer and/or visualization specialist. Of the six paths that I set out to cover in this series this might be the one that I know the least about. So, you can take these suggestions with a grain of salt but hopefully I will provide a few useful nuggets.

Traditional cartographers, those who produce maps for printed material, still exist but not in large numbers and my suggestions probably won’t help if you want to go down the traditional route. Some of the legends in this arena, including Bill Loy, Stuart Allen, David Imus and probably several others that deserve to be mentioned are connected to the Department of Geography at the University of Oregon where I studied. You can probably earn a decent living this way if you’re really dedicated and find a mentor who can teach you the craft. But, I can’t help. Instead, I will focus on the more modern computer-enabled cartographic visualization, interactive map design and data graphics production side of things. I see a lot of opportunity here but it requires a new combination of skills that don’t always go together: programming and visual creativity.

The cutting edge in cartographic visualization involves developing web and mobile interfaces. So, in a sense, this path involves training similar to the GIS Software Developer career. The major difference is that you will need to become an expert in user interface design. You still need to be able to write code but you don’t have to be an algorithm guru. So, while in college, I would recommend the following.

Hopefully this is pretty obvious but take every course on Cartography that is available. Yes, take some GIS courses as well. They probably get taught together. Don’t worry about becoming an ArcGIS master. Not that it would hurt. But it’s probably just as important or more so to master Adobe Illustrator and/or other graphics software. Also, study a bit of cartography’s rich history.

Perhaps most importantly, find an opportunity to work on cartography-related projects. At the University of Oregon all the best cartography students worked in the InfoGraphics Lab and learned a ton from Director Jim Meacham and his staff of cartography and visualization experts. Ideally, you would find a similar lab at your college/university and get involved in any way possible – volunteer, get a work-study job, whatever it takes to get exposure to the people who work there.

Take a combination of Human and Physical Geography. See my post on becoming a Geospatial Analyst for more details on this.

Read everything you can on data visualization. You’ll want to read everything written by Edward Tufte. You should also check out some of the older work by authors like William Clevelandalong with some of the newer, more cutting edge ideas by new practitioners like Yau (note: I haven’t read Flowing Data by Nathan Yao but it’s on my list and even if it’s not a timeless classic you need to expose yourself to contemporary perspectives).

Learn something about remote sensing and other major sources of geographic data. Again, see my post on becoming a Geospatial Analyst for more details on this.

Also, read what I wrote about problem solving, writing/communication and teamwork (bullets 2, 3 and 4) in the GIS Software Developer post. In particular, I would highly recommend that you study as much statistics as you can. Visualization is within the domain of statistics, perhaps even more so than it is within geography. You need to be able to speak with statisticians in their language; even if you can’t do so fluently, at least pick up the basics. If you like statistics and would like to do some self-study, I would recommend learning R. It’s freely available open source software available for download from r-project.org. Aside from being free, it’s really powerful especially with all the add-on packages. Only problem may be that it’s a bit more challenging to learn than other more point-and-click oriented stats packages. There are a number of books on R programmingwith how-to guides. Find one that works for you and give it a try.

Study graphic design in the art school. You need to learn the basics of good design. This can be via university coursework, self-study or you might find good courses at the local community college with better hands-on learning opportunities. You should also pick up skills in the Adobe Creative Suite or something comparable.

Study User Interface Design. I don’t know how readily available classes on this topic would be – I think it probably varies quite a bit from campus to campus. You probably have lots of good ideas on this already because, unless you’re my age or older, you’ve been interacting with software your entire life. But, it’s not a bad idea to read about standard protocols and other people’s ideas on what makes for good interface design. Don’t be afraid to ignore the gospel according to some self-proclaimed authority. You want to cultivate your own unique style. The most successful designs seem to take simplicity to a new level. Beware the temptation to offer more options and powerful features. History has shown time and again that users prefer ease-of-use over just about anything else. I haven’t read this book by Steve Krug
but it looks like a winner and you can explore similar resources from there.

The best bet on this path, in my opinion, is to blend this with the GIS Software Developer route. The successful cartographer types that I see have taken up web development tools like Adobe Flash (although this technology may be headed for the dustbin). Maybe you’ll want to become an HTML5 expert – combining programming skills with user interface design artistry to create the next generation of cartography for mobile devices and whatever comes next.

I think the future here is very bright indeed. I believe that cartographic visualization will play a central role in addressing Big Data challenges.

Replacement Rate Models in the Automotive Aftermarket

Recently I posted an article to the Aftermarket Analytics blog about replacement rate modeling in the automotive aftermarket. It’s a sizable post, worthwhile for anyone interested in demand modeling in any industry. I’ll post an excerpt here, but head over to the post to get the full article and images.

“An important piece of the automotive aftermarket category management puzzle involves an understanding of your category’s replacement rates. Replacement rates, which are also referred to as repair rates or failure rates, are essentially an estimate of the likelihood that a vehicle will need to a replacement part due to failure or normal wear and tear.

So, how should replacement rates be calculated?

Well, it starts with determining an appropriate numerator and denominator. The denominator should represent an estimate of the total population of vehicles. The numerator should represent an estimate of the total number of vehicles that required a particular part replacement.

As I understand it currently the two most common ways of calculating replacement rates go something like this: (1) replacement rates are simply calculated using a consumer survey where the total number of a particular vehicle in the survey is used as the denominator and the number of repairs/replacements reported is used as the numerator; or (2) some data/technology providers generate replacement rates based on repair shop part “look-ups” – meaning how frequently a part is queried in an online database of parts. So the number of look-ups is used as the denominator and the number of reported repairs/replacements is used as the numerator.

I don’t like either approach.”

Spatial Career Guide – How to Become a Geospatial Analyst

In my last post I proposed 5 skills to develop during college that should help you become a successful GIS Software Developer as part of my series of blog posts on Spatial Careers. In this post I’m writing about the Geospatial Analyst career track. This one is more challenging because the path isn’t well defined.

The job title Geospatial Analyst means almost nothing unless you know what industry, government agency or sector of the economy you’ll be working in. There are several sub-sectors here and you almost have to choose one to target before you start outlining the courses you plan to take in college or the extra study you might pursue during your spare time. Here are a few categories of employer types and industry types:

Military – Geospatial Intelligence Agency, CIA, other DoD
Environmental – EPA, Nature Conservancy, other non-profits, environmental consulting firms
Retail/Commercial Real Estate – Large retailers, consulting firms, technology firms developing relevant applications for real estate decisions and real estate professionals
Municipal/County/State Government Agencies – Maintaining a GIS back-office for local government agencies to assist with tax collection, utilities, etc.
Urban Planning – Similar to local government but focused on planning and design.
Geohealth – CDC, NIH, hospitals, public health agencies.
Other commercial/business uses.
Other government agencies, e.g., Census

You can’t really prepare for all of these simultaneously. For example, if you work in the environmental sector you better know how to handle raster data and remote sensing imagery with software like ERDAS Imagine, maybe ENVI, and a few others. But, you’ll never touch any of that stuff in Retail/Commercial where you probably want to know some economic geography along with some spatial analysis, statistics, cartography and GIS (actually MapInfo Pro is more common in this sector than ArcGIS and a new software offering called Alteryx is now a big deal). If you work for the Geospatial Intelligence Agency they will teach you all the tools you need to know. I don’t know if this is still true but for some time their geospatial analysis applications all worked with an obscure data format called VPF. Anyway, hopefully you get the idea. Each sector has its own skill set.

So if you know you want to be a geospatial analyst but you don’t know what area of application most interests you I guess I would recommend that you start trying to find out. Contact people in various fields and ask them questions about how they spend their time. Do something that you’ll find fun and interesting on a day-to-day basis rather than worrying about which sector pays the best. Everything changes too fast for you to accurately forecast the future of a professional niche but you can predict how you’ll like various tasks, topics and application areas with some degree of certainty if you know yourself. And, if you’re doing something you enjoy you’ll be more successful.

If you just don’t know and want to be prepared for anything I would suggest the following:

Take a combination of Human and Physical Geography. Not just the intro level classes. On the Human side, take political, urban, economic and cultural geography course offerings. Don’t just go through the motions, read some of the big thinkers. Take a look at Yi Fu Tuan’s work on perceptions of place/space. See what Sack has to say about territoriality. Read Carl Sauer’s work on cultural landscapes. Study Christaller’s theory of central place. Think about these ideas and how they apply to modern problems. On the Physical side, take classes in climatology, biogeography and geomorphology. Pick up recent copies of the Annals of the Association of American Geographers (they will be in the library, on every faculty bookshelf and probably strewn about the department office) and browse through some of the articles on environmental issues. Take an individual study course with a professor you like and dig into a topic – maybe offer to do some research for a paper that they want to publish. Don’t get hung up on the particulars – just be sure you’re somewhat fluent in both Human and Physical geography so you know what you’re looking at when you start staring at maps 8 hours a day.

Take the standard set of Cartography and GIS courses but don’t worry about depth of knowledge with any one technology unless it’s within the context of a cool project where you’re also thinking about a real problem. Don’t forget to take cartography classes as well. GIS is not the same as cartography. You should understand how to design information graphics. Read Tufte’s work on data visualization(but don’t worship him) and develop an eye for what makes an effective graphic.

Learn something about remote sensing and other major sources of geographic data – again, ideally within the context of a project. Don’t spend months stitching together images for a cornfield in Iowa unless you have a project (and preferably a paycheck) to justify the time. Instead, just get some ideas about remotely sensed imagery and how it can be used to solve problems. Figure out how the images are processed into analyzable data. Think about the different resolutions of data available and what scales are appropriate for different types of problems. Learn about other data sources as well. NOAA and the NCDC have good stuff. Census has data coming out their ears – know the difference between a block group a census tract and a CBSA. Same with NIH, National Cancer Institute, CDC, etc. Poke around.

Also, read what I wrote about problem solving, writing/communication and teamwork (bullets 2, 3 and 4) in the GIS Software Developer post.

That’s about it. When you look to join the workforce be sure that you angle for jobs where you’ll be doing *analysis* rather than data management. Some GIS technician jobs may be titled GIS Analyst or Geospatial Analyst. But if you’re just digitizing or editing .shp files you are definitely not analyzing anything and your GIS software user skills will decline in value. If you get a job as an analyst where you are responsible for analyzing a variety of data sources and making strategic recommendations you’ll have a bright future.

If this all sounds a bit too amorphous then becoming a Geospatial Analyst may not be for you. Part of being an analyst is taking a big pile of seemingly unrelated data elements and synthesizing them into something that can guide a decision framework. If you’re not comfortable with this you might prefer a career as a GIS Software Developer or one of the other spatial paths.

Spatial Career Guide – 5 Key Skills for Future GIS Software Developers

Many, many folks in the GIS community find themselves in the software development universe and for good reason. Software development makes for an interesting career, blending problem solving and creativity, and most software development jobs pay fairly well with opportunities for entrepreneurial adventures. This is the path I took after finishing part of grad school and I have no regrets whatsoever. I loved programming and developing software tools with GIS components. Way back in the day I helped develop a map interface and GIS functionality (using VB and MapInfo’s MapX component) for a cool supply chain network design application called LogicNet. My code stood the test of time for a few years after I left but it’s long since been rewritten and dramatically improved upon. The product lives on and is now sold (for way too much money) by IBM’s supply chain application group.

This is my first post in a series on Spatial Careers. If you’re currently a student in a geography department and you want to become a GIS software developer then this post is for you. First of all you might be thinking – gee, maybe I should become a computer science major instead, right? Well, if you’re a freshman and not too far down any particular path it’s not a bad option to go with a more recognizably technical degree and it will help you get a leg up for that first job. But, I would encourage you to stay in the geography department while loading up on courses from computer science and other hard-core departments like physics, math and/or whatever interests you most. No other department will teach you to think spatially and I think that’s probably the toughest skill to learn on the job.

The cool thing about software development is that after a few years in the work force no one will care about your major or where you earned your degree. The only things that will matter will be:

Can you write solid code?
Are you good at solving challenging problems – technical and otherwise?
Can you communicate effectively in both verbal and written forms?
Are you able to establish and maintain productive working relationships with team members?
Can you learn new technologies quickly?

If the answer is yes to all those questions you’ll have a great career whether you have a Master’s degree in Computer Science from Stanford or an Associate’s degree in Geography from San Joaquin Delta College. Here are a few thoughts on each of these pieces.

(1) To learn how to write solid code it would be a good idea to take a core sequence in Computer Science. Some combination of applied programming (with a popular language like C# or Java) and computer science theory would be good. Ideally you’d also take more advanced courses on data structures and algorithms. There are probably a few others I should mention but you can’t take everything. In addition, you would do well to engage in some self-study to learn how to write solid industrial strength code. Read Code Complete: A Practical Handbook of Software Construction or something similar and The Mythical Man-Month: Essays on Software Engineering, Anniversary Edition (2nd Edition). Grab any O’Reilly book on a technology of interest. Think of a simple project and then do it – it doesn’t have to be perfect but see it from start to finish. If you need an idea I’ll be glad to put you to work. Also, learn how to test your own work – this is important! Quality Assurance is not an after-thought; it’s a critical part of software development and everyone is responsible. Don’t be one of those programmers who writes quick and sloppy code and blames QA when bugs slip through the cracks.

(2) For general problem solving, just take a wide variety of challenging courses. For me, that meant taking lots of statistics including Applied Regression Analysis in the Business School and grad-level Econometrics in the Econ Department. There were outstanding classes in the Geography Department – my favorite was Advanced Geographic Data Analysis – but sometimes it’s good to explore other fields. Take courses that interest you and will provide you with a different perspective. Don’t worry so much about how they will look on a transcript or whether or not they fulfill a graduation requirement. I know it’s difficult to finish in 4 years (or 2 for a Master’s) and you want to be efficient but it’s too important for you to learn cool stuff while you have access to such a nice variety of brilliant minds and the time to explore. [If you don’t have time/money, get a job and go through school at a slower pace. In many ways, I prefer this approach.]

(3) Write a lot. Write to your parents and grandparents (more than just text messages or tweets), if you’re lucky enough to still have them in your life. They will love you for it and it will be a good way for you to learn how to describe what you’re doing to people who may not be technical. Communicate via email with your Professors and TAs. Think of each email as an important business memo. Start a blog and write about what you’re learning. Send emails to interesting people and ask them questions about their work or for a brief phone call to discuss something that interests you. Learn how to convince people to listen to your ideas with your writing. Trust me – it will help no matter what you do or where you go. Also, take opportunities to give presentations. Volunteer to be the spokesperson for your class project or offer to give a guest lecture in a class. Attend a conference and present a paper. Learn how to deliver a presentation with PowerPoint. Everyone does it in business, academics, you name it. In person, via WebEx, over the phone. All the time. Learn to play the game. If you want your brilliant ideas to be heard you have to be able to communicate.

(4) Get along with people. This can be the most challenging piece of the puzzle. Programmers are an eccentric bunch but they’re typically very good people. They can be very quirky and are often introverted but, in my experience, programmers are usually down-to-earth, interested in a lot of different things, easy to get along with and fun to talk to. Mostly they want to have the autonomy to work on cool problems and solve them in clever ways. So give them space but ask them about what they’re doing and how they’re doing it. You’ll probably learn some good stuff. Unfortunately, you also will need to get along with other people who present more of a challenge, especially if you work for a large company. Accounting, legal, marketing, even IT – all can be a pain when they’re distracting you with corporate politics or asserting their authority while you’re just trying to write code. Just do your best. Connect with someone in Sales so you can maybe meet a real customer and figure out why it’s important to do a good job. Don’t feel like you have to be everyone’s friend. Sometimes it’s well worth it to make a stand and not sacrifice your integrity just to be seen as a team player. There are true assholes in the world. Life is too short to pretend you like them. When in doubt, candor is the most effective style but most people have thin skin so try to be respectful and kind. Maybe the best way to prepare is to take a leadership role of some kind in a college club or organization on campus. Good luck with this – I’m not the best one to give advice here.

(5) Think of all the changes to the software industry in the last 5 years. Apple’s iPhone was not yet available for purchase 5 years ago. No one had heard of an iPad. Now everyone has an iPhone, iPad or Android device and developers who can create apps for iOS or Android are in high demand. So you can’t expect to learn what you need for your whole career in college. You’ll be learning new technology every year and probably making major changes to your development environment every 3-6 years. Accept that you can’t write in the same syntax and/or within the same IDE for your whole career; instead, jump at the chance to build a prototype with new technology.

I know that you’re thinking – wait, dude, I have to know all the different ArcGIS APIs and Ruby on Rails, blah, blah. Back in the late 90s you had to know about n-tier architecture and .NET and ODBC and the different ocx controls for mapping/GIS. Now it’s a bunch of other silly acronyms and funny names. Fortunately, I don’t have to keep up with all this stuff now. I know, I know. It actually matters if you want to work with and be respected by technical people. I’m just trying to point out that it’s always changing and you’ll never know everything. Plus, college is a lousy place to learn this stuff. Only a small fraction of computer science professors stay up on the latest technologies – they can’t bother to play around with HTML5 or mock up an Android app. They’re too busy writing books and articles and preparing lectures. Same goes for GIS professors. This will vary from campus to campus but, generally speaking, if you want to be on the bleeding edge of software development you’ll need to read books and blogs and build prototypes on your own time. You won’t learn these skills in any required courses. Same goes for GIS development tools. You’ll be stuck making ArcGIS plug-ins and using all the other ESRI development tools because nearly every University has a site license and since the U. spent a fair bit of cash on that site license they’re not going to buy alternatives for the GIS lab. There’s nothing wrong with ESRI technology – they are clearly the leader – but it would be nice to experiment with a variety of other geospatial technologies. Younger students are lucky because open source didn’t really exist in the same way when I was in college or grad school. Now it’s an all-you-can-eat bonanza out there. Dig in.

Anyway, this article won’t tell you which technologies are the right ones to learn. I’ll leave that for someone else who’s deep in the technical trenches. I’m more on the business side these days and only know enough technology to be dangerous. But, I think I can still provide some meaningful guidance on how to spend your time while in school in order to position yourself for a successful career campaign in the GIS software development world. Hopefully this post does just that.

If you follow the guidelines above and can manage to land a job where you have the opportunity to work with experienced software developers who are willing to show you the ropes, I think you’ll be in great shape.

Spatial Career Guide

In a recent post I argued that Spatial is Indeed Special but that GIS software skills will soon be obsolete. Recent graduates trying to establish “GIS careers” (perhaps we should start calling them Geospatial Careers?) have begun complaining because the opportunities they were promised haven’t materialized. I recently tried to provide some guidance for those attempting to launch a GIS career. But, if you are a current undergraduate studying GIS within a geography department what should you do to prepare for one of these spatial careers? Should you continue taking ArcGIS classes or should you spend more time on other skills?