It truly is one of the greatest contra-indicators I have ever had the pleasure of observing first hand. It's a wonder to behold.
> When expensively educated, fashionable young graduates start showing up in your field, you're in a bubble.
- Kevin Marks, http://epeus.blogspot.com.au/2005/12/key-indicator-for-bubbl..., derived from Liar's Poker, by Michael Lewis.
> This year, some 37% of Harvard Business School's graduate found work on Wall Street, up from 30% a year ago and 26% for the Class of 2004. The trend suggests that Wall Street is becoming bloated and the American economy is ripe for a slowdown.
Mr. Soifer, who retired from Brown Brothers in 2000 and now runs his own consulting firm, appears to be on to something. He advised his friends and colleagues to sell back in 2000, when 30% of the HBS graduating class took jobs on Wall Street. Before that, the last long-term sell he sent was in 1987.
> Mr. Soifer notes that the Harvard M.B.A. indicator has historically been more prolific as a source of “sell’ signals, showing strong results in 1987, 2000-02, and 2005-08, than “buy” signals. In fact, the last time it reached the 10 percent “buy” level was in the early 1980s, when the Dow Jones industrial average traded below 1,000.
The all-time low was reached in 1937, when only three graduates — about 1 percent — braved the market and ventured into the securities industry.
Note that you might have go incognito or clear your cookies if you already tried the direct link and failed (I can't believe how far they'll go to block everyone but search engines).
"Students are asking, "Where's the place that I can drive innovation? Where's the place that I can have the most impact?"
Sounds like those students are just rationalizing. They're going into tech mainly because the tech field has been on fire lately, and the risk of trying out the tech field is low. After all, they're still getting paid pretty well.
Once the tech bubble bursts, they'll be hovering around fields that pay the most.
You are not going to be driving innovation by working for Linkedin, Facebook, and Microsoft.
It's a little sad that I wouldn't mind another tech downturn, but that's where I am.
They supposedly spent 4 years studying the hell out of self-balancing trees and kernel process schedulers and then work for a Goldman Sachs like place building excel spreadsheets and writing reports.
Hopefully they'll attempt to negotiate for better salaries and more reasonable hours, but, according to all my Wall Street friends, this tends to be an effort in futility.
The best of the best will always put in absurd hours doing the tedious work you describe. They need to show off this way to win distinction. In theory, hacker types could buck the system, but that system in high finance, which awards face time and man hours like few other places, is pretty damn robust.
The tech world is also at risk of going in this direction as well as the wider economy collapses and startups actually start to look like a somewhat conservative career path. The symptoms are all around us. Look at the proliferation of accelerators and short-form bootcamp style tech programs. Google-style hiring process starts to make a lot more sense in this kind of environment.
And it also depends on just how far you go in finance - IBD at a bulge bracket is very different from some nonsense boutique
For me, banking paid better and provided more interesting work
- For pre-IPO firms: Someone plugged in to all the investment bankers and investment managers, who has both an analytical and visceral feel for how tech firms are valued.
- For firms with Enterprise customers: Someone who has a large rolodex of non-IT customers with P&L responsibility, who knows how to do their jobs as good as them.
- For medium sized firms and above: Someone who knows every last legal issue around HR.
It would be great to find folks like this who also have CS degrees and are passionate about technology. But folks with MBAs that fit these profiles but don't love the technology itself can still be valuable.
It's a viewpoint I can sympathize with. As someone who doesn't expect to get rich off an IPO or acquisition and therefore will be spending most (all?) of my working life in this industry, I'd prefer to work alongside competent people (whether that be in development or business) who aren't just trying to get rich quick.
Tech companies, which once may have dismissed business-school graduates as smooth talkers with PowerPoint skills, are warming to M.B.A.s who may be able to help lead their fast-growing operations as they mature. At the same time, Wall Street has offered fewer opportunities for ambitious young graduates.
also related> http://www.thecrimson.com/article/2013/8/8/hbs-employment-te...
such public info might not portend upside to the equity, tho
That being said, I know some from finance and marketing tyle backgrounds who are totally gung-ho about data and have track records of getting their hands dirty, so I'd say that if you're intent on finding students with non-tech backgrounds who have the cultural instincts for tech, you can find them (maybe about 3% of the class).
edit: That being said, many of my peers would be fantastic at roles like BD.
I've moved into a PM role now but still code everyday and join the dev team in deep technical discussions whenever I get a chance.
Engineers and people with tech background are the biggest single block.
I'm not buying it.
Personally as someone who has done both business and technical work, I'm saddened every time this topic comes up. The less judgmental voices get down voted and drowned out, while the posts that generalize based on anecdotal experience prevail. I wish we could just stop having this discussion, as I don't think it adds at all to the benefit of the tech community.
I graduated with a BS in Business (Supply Chain) because I knew I wanted to be involved in startups someday, but I've had nothing but big corporate jobs since then. For the longest time, I've held this idea that because all of the bigwigs got their MBAs, and they got them from top schools, that that was what I needed to do. In other words, to become the person I wanted to be, I had to go get an MBA.
My thoughts have tempered as I moved progressively towards more technical roles: Business Intelligence, Ops Research, Systems Architecture, etc. In fact, I've started to grow a disdain for the average MBA, not unlike the disdain you hear from a lot of people with backgrounds in CS. The thing is, I've never been anything but a business-end guy...I shouldn't feel that way about business-guys.
My own observation on the cause has to do with the toolsets that are given to your typical MBA. Their Root Cause Analysis tools assume that everything has a singular root cause, but those analyses fail when the problem is of combinatorial complexity, where you often have multiple root causes for a problem. Business optimization tends to fall solely on LP models, which again, fail under combinatorial complexity scenarios. Pareto analysis is fine until you have pareto'd your entire business and all that you have left are a bunch of bugs and quality flaws that only affect a tiny minority of orders by themselves, but 100% of orders in aggregate. The entire MBA toolset itself seems to be a result of pareto optimization (a set of tools to use for 80% of the scenarios you will come across as a business leader).
Furthermore, I now feel as though the wisdom of any singular person can very easily become overrated, and in the case of top level execs, is almost invariably overrated. As I became involved with Business Intelligence at my last job, I kept running into execs who always had the same mindset: just give me the data, and I will make the decision that will save the day. The problem is, the skillset to extract, transform, prettify, and graph out data is very often the same skillset that can make provably optimal decisions, or at least better-than-human decisions. Why should they spend so much of their time satisfying executive egos by giving them a precious jewel of data that they will just blow with a swagged decision, when they could be applying Machine Learning or Mathematical Optimization instead?
Your average smart guy with an MBA will continue to provide value in specific scenarios. The Technology industry (as long as "Technology" implies working with intractably difficult problems) will rarely be one of them. And just for good measure, I'll caveat that one more time, especially since my current employer has a ton of exceptions: not all MBAs ...
So, it's working for the tech-savvy using these little hacks, right? That means a certain article is going to gain traction, get people talking on social networking sites, and in turn seduce more people into wanting in on those discussions. But the people who aren't in on these hacks are met with a dilemma: be a part of the in-crowd, or just go away. As it turns out, this human wanting to be in on what everyone else is talking about is very strong, so a lot of people end up buying it. For others, it's the convenience factor of not having to google every article and find it that way... in both cases, a key force was the content not being totally unaccessible, but being there in some small way as a teaser. I should point out that it's working out exceeding well for the NYTimes. WSJ has been doing it for a long time, and the Economist just recently started doing it too. I expect even more will soon follow. It's an interesting and clever evolution of the freemium model in some ways.
There's a certain type of person whose apparent intelligence is exaggerated by the reward system of lifetime in a Victorian-era education system that emphasizes obedience and checklists. Such people whether created by nurture or nature, are disproportionately represented in the MBA world. However the type of skills developed there are all about thriving within existing systems, whereas to build a successful startup requires a completely different kind of thinking.
I'm not painting MBAs all with one brush either, there are many brilliant ones I've worked with. But there are also many who think they are hot shit because of a lifetime of being "gifted" and "elite" far out of proportion to their actual ability to contribute to a tech startup.