What Do Analytics and Travel Delays Have in Common?

I’m writing this blog post as I sit waiting for my delayed flight home from a customer meeting. No one likes sitting on the tarmac, but it’s even more frustrating when you don’t have any information about how long you’ll be stuck there. There’s a surprising amount of data out there on plane departures, arrivals, and flight patterns (did you know that roughly 18% of all JetBlue flights leave 50 minutes after the original scheduled time?). It’s too bad there’s no way to get real-time data about when your current flight will take off.

As I sit here, I’m also reminded of a related video I saw earlier this week. It was a demo from a BI vendor analyzing airline on-time data, and it stood out to me for two reasons. The first was because when we first started ThoughtSpot (before we had any customer datasets), we also demoed airline on-time data. Everyone can relate to it, like I can now. And second, because this demo was so painful that it reminded me why I joined ThoughtSpot in the first place. The demo-er was showing how he could build intricate reports and charts with his product. As he skillfully chose values from different dropdowns and navigated across sections to add attributes and refine his answer, it was clear he was a pro at the product. He was able to get the answers he needed. But I got so lost in all the dropdowns and sections that I forgot all about the problem he was trying to solve.

The truth is, not all of us are power users. In fact, most of us aren’t. Michael Lock, an analyst and VP at Aberdeen, brought up this point the other day in a blog post. He recently returned from a user conference for one of the biggest BI vendors, where he observed that everyone around him was either a power user or a data analyst, i.e., someone who spends days their days living, breathing, and thinking about data. While Lock is tech-savvy and data-driven, he doesn’t often get his hands dirty and get beyond just “consuming” the data. He brought up this question that I’ve been thinking about a lot lately: What about the rest of us? How do we become creators, too?

It shouldn't require technically-skilled employees to get answers any more than we need a specialist to get an answer from retail data at amazon.com, flight information from kayak.com, or to find the right restaurant for dinner at yelp.com. For consumer products like these, we get sub-second access to datasets made up of hundreds of terabytes of data using products we've never been trained on, yet somehow we’re complacent with highly-trained product specialists doing the same thing in ten seconds across a much smaller dataset.

It’s a problem that I see over and over again, and it isn't a product problem - it's an expectation problem. We’re so used to these products being hard to use that we don’t hold them to the same standard we’re used to in our personal lives. We’re all trained to Google almost everything, but at work we’re willing to sit around and wait for someone else to effectively “Google” something for us.

I think it's time that we started thinking of all our co-workers as creators of data vs consumers. we should expect that these tools give us direct access to our data, just like we get in our personal life. I joined ThoughtSpot, to help make that vision a reality.

Now back to my flight and delayed airplanes. We’re finally preparing for take-off. And as for all that airline on-time data, we’ve done some pretty cool stuff with it at ThoughtSpot. Stay tuned for an upcoming blog post to see how anyone can quickly bring that data to life with search-driven analytics.