March 1st, 2008
I try not to write too much about my professional life in this blog; I have a hard enough time explaining my work to my wife, let alone everyone else. However, I think it's safe to say that anyone who works in an office and does any kind of analytical work also finds that they spend a lot of time in front of spreadsheets. Thanks to Microsoft, that spreadsheet is very likely Excel.
My introduction to Excel was during my first job out of college as an analyst for Payless ShoeSource. It took about a week in that position for me to realize that a good part of my success depended on my skill using Excel to transform meaningless numbers into actionable business projects. People who knew Excel got promoted, and people who didn't ended up working in HR.
It's no exaggeration to say that I spent the next two years almost wholly devoted to becoming an Excel pro. The great thing about working for a big company is that in the beginning of your career (if it's structured right), most of your time is spent learning. I think during those two years the actual amount of time I spent "working" in the traditional sense was less than 50%. The other half was spent experimenting, building, and rebuilding until I knew Excel and related technologies in and out. Since those days, not much has changed except the venue. Excel continues to be the tool de rigeur for anyone doing even marginally serious analytical work. At my current employer, I've spent a good portion of my time training the next generation of analysts how to master the secrets of Excel and VBA, and it is still the most important indicator of success in our analyst group.
However, anyone who has plumbed the depths of Excel also knows its limitations. Many people try to use Excel for jobs to which databases are much more suited; accordingly, I've had to become an expert in SQL and database design. But the user-side of any analytical tool is still going to be Excel, whether you want it to be or not. I've seen multi-million dollar systems languish because users simply copy and paste the results to Excel for manipulation, then paste them back when they're done massaging the numbers. Excel is simply more flexible than nearly anything you can think of, especially in a world of inflexible, user-unfriendly business software packages.
But Excel can't do everything. I ran into a problem about six months ago. I had built the latest incarnation of our company's item forecasting model in Excel. It was really an amazing tool, full of nuance and flexible to the n-th degree. And incomprehensible to everyone except myself. And, even for an old Excel hand, making any substantial changes required not only an expert knowledge of Excel, but hours of error-checking to find the inevitable problems. The cost of maintaining the model had escalated to where only a few people in the company would even know how to approach fixing an issue. With Excel's help, I had outsmarted myself.
Enter Quantrix. Part of my job is to keep up on the latest technologies that might prove useful for our business. One day I stumbled across Quantrix, and my life has not been the same since. I'm not kidding.
Quantrix does most of the things Excel does. But the fundamental premise is much different. For one thing, developing analytical models takes about half the time as Excel, and the time savings increases the more complex the model becomes. Need to add scenarios? Just add a new dimension. Changing the formula for net sales? Change it once, and it propogates throughout the whole model. Need to build a relationship between departments and sub-departments? Add another matrix, and Quantrix remembers the relationship and applies it to every formula. It's brilliant.
Now I'm in selling mode. Here are some key features:
Since discovering Quantrix, I use it more than Excel. For me, that's a change on the level of emigrating to a new country, or becoming a Mac user. It's revolutionary.