roin

I work with an army of very smart people who need to build incredibly complex models to drive our business. Like most companies, we turn to Excel. It's the only widely used application with a low enough barrier to entry that "non-technical" people can build legitimately complex (if not always robust) models.

But the problems with Excel and general spreadsheet modeling limitations offer such a great opportunity for improvement that would impact just about every business out there. I wish I saw more people tackling this, or I had a great idea to do it myself. The problems I see are around barrier to entry, in that it must be usable in just a couple minutes, simple enough for non-programmers to learn, and equally or more efficient to get a basic model functioning. Otherwise I just don't see wide adoption despite possible maintenance, accuracy, and reliability benefits.

James Kwak has written some smart stuff about this (http://baselinescenario.com/2013/04/18/more-bad-excel/), and I'm interested in what Data Nitro (datanitro.com) is doing.

A friend from MIT is doing something similar with a great team.

http://www.fitbark.com/

This is a real shame. Shai Agassi is a great visionary, but perhaps Better Place bit off more than it could chew. I had the pleasure of seeing him speak at MIT in 2009, and I think all of us left the room thinking that Better Place was going to lead us into the electric car future. Here is his TED talk: http://www.youtube.com/watch?v=FcoJt2KLC9k

As you noted, the problem is that the government bought debt, not equity, so they don't share in the upside that would make this a financial home run that makes up for other failures. That being said, the government isn't in this to make money, they're in it for the broader benefits that will spillover outside of the individual company receiving financing. In that sense the VC analogy could work, because a major successful electric car company in the US probably would be a "home run" for the country (and the world) on several dimensions, more than making up for losses on the way.

There is nowhere near enough information to make a judgement here. I doubt Marissa Mayer will be answering any awkward questions about this today, or anytime in the near future.

Teams that are bigger than necessary to get their job done create huge problems in large corporations. People without enough to do aren't just wasting money and other resources, they also create politics. It's difficult to figure out the optimal size of a team, but I've seen greater productivity out of teams that are a bit too small than those that are a bit too big.