About six months ago, Alteryx, an Irvine-based software company, was working with a restaurant chain to help figure out why a particular region wasn’t performing as well as it should.
After a few minutes of setup, CEO Dean Stoecker said, the Alteryx software surfaced a tweet sent in the under-performing region that offered a pretty good indication.
“The first tweet that came across said a big roach crossed my table last night,” Stoecker said.
The insight, though seemingly obvious, underscores the number of sources businesses must evaluate for information to help them succeed. Alteryx is one of a growing roster of companies seeking to answer straightforward questions by sifting huge quantities of information. Last year, it received $12 million in venture capital backing and is expected to grow from 170 employees to more than 200 this year.
The refinement of data-sifting technology is allowing organizations to make smarter, quicker, decisions about everything – from which coupons to send to particular customers to who should be watched as a potential terrorist.
The key is to blend different stores of information – customer data, weather, competitors, loyalty cards and online or offline behavior – to cut the time needed to find an answer.
Data collection is fueling an ongoing privacy debate, ranging from the NSA’s mass collection of communications to the privacy of our Web surfing and the movements recorded by our phones.
That debate is likely to be hashed out for years to come. In the meantime, companies like Alteryx are building the software to help customers like haircut franchise Great Clips figure out where to put the next store.
The Register sat down with Stoecker to discuss the technology and where it’s headed.
Q. Why is there such a drive to collect more information?
A. I’ve got to consume anything that might be relevant ... to get the right answer.
If you aren’t going to have your teams become analytically minded, you will become irrelevant. Because there’s too much data that allows competitors to make better decisions, and you’ll get outsmarted every step of the way.
Q. So decisions get smarter the more data you get?
A. In data sciences, there is no precision. ... You reach that law of diminishing returns where you try harder and harder to get that final incremental improvement. And generally it’s because there’s not enough data. So you have to have a tool that allows you to ingest more of that as it becomes available.
It used to be everything was in one database. If it wasn’t (in that database), you really wouldn’t be able to incorporate that content in order to make better decisions. Now the tools have changed where it doesn’t really matter what the data source happens to be. And the tools are fast enough to where I can leverage all the possible content to improve my decision-making capabilities.
©2014 The Orange County Register (Santa Ana, Calif.)